Kinaxis Stock

Welcome to the National Bank of Canada Virtual Event. Doug Taylor, you may begin.

Yes. Thanks. Hi, everyone. I appreciate you joining us on Friday morning at the end of what has been an exceptionally noisy week in the financial market, I think you'll agree. As introduced, I'm Doug Taylor with National Bank Capital Markets Equity Research. I'm happy to have the opportunity here to host a fireside chat with the management team of Kinaxis, which has been one of our top ideas in Canadian technology.

Here with us today, we've got Razat Gaurav, CEO of Kinaxis since earlier this year. And we've also got Herb Yeh, who is CFO since I believe it's this summer broadly. So relatively new faces for many of you here at the head of Kinaxis. I'll also point out that this comes on the back of the company's stellar Q3 results, which were released overnight on Wednesday, produced a positive reaction yesterday on a day when there was not a lot of green to be found on most of our screens.

Now the goal here today is not to regurgitate the quarterly disclosure and that process. But perhaps those who didn't get a chance to go through the results, it was a busy day yesterday, and some of you are otherwise new to the story. So why don't I get the management team to sort of give us the highlights as you see them, just to orient everyone, and then we'll proceed with some bigger picture questions that I get from investors on the Kinaxis story.

So Kinaxis, Gaurav Razat, over to you. Just maybe provide us a quick recap and get us started here.

Yes. We had a very strong Q3 performance. The team did a great job. We posted 22% SaaS revenue growth. Our ARR grew by 19%, 20% on a constant currency basis. And on just about every metric, we were really pleased with our performance. We had a good balance between net new logos as well as existing expansions with existing customers.

And as we look forward, given the performance we've had for 3 consecutive quarters, we felt really comfortable to further increase our guidance for the entire year. So we've increased our guidance in terms of total revenue, SaaS revenue and EBITDA margin for the year. And again, really tremendously pleased with the performance so far.

Okay. That's great. So we'll get into the Q&A portion, which is where we're going to spend the majority of our time here today. I'm very happy to lead the discussion. But for the audience, you can input questions into the portal, you're watching this through and it will hit my inbox here. And I'll try to work those questions into the discussion.

So please make use of that feature to try and make this event a little bit more interactive. So with that, let's get started. I think before we drill down into some of the nitty gritty, I want to step back a bit and talk about the market that you're servicing, supply chain as a function for many of the world's largest companies.

Obviously, there's a ton going on in the world that's stressing these functions. So I wanted to start by talking about the why for Kinaxis because I think it's one of the key arguments for a story like this amongst the broader software universe that we're all choosing to invest within the budgets for these types of solutions, the appetite for change and adoption. So you've been in supply chain for some time, Razat. How would you characterize where we are in the cycle for supply chain automation and modernization?

Yes. I've spent most of my career in building supply chain software. So you're totally right. I've never seen a time like this, both in terms of opportunities for innovating given the enabling technologies, the compute infrastructure, all the new data architectures and advance of Agentic AI. But also, I've never seen a time like this in terms of the appetite on the customer side for them to transform and truly adopt these new capabilities.

So let me first start with anchoring everyone on like what do we do at Kinaxis? What does the Kinaxis solution do, where we're positioned, and then I'll talk about what I see as the evolution of that, right? So at Kinaxis, we are the leaders in supply chain planning and decisioning. We play in 7 verticals, and we are working with leading companies in every one of those verticals.

Customers include the likes of Unilever, Qualcomm, Merck, Colgate, Ford Motor Company and several -- ExxonMobil, just all the leaders in every one of those verticals that we play in. And we help these customers in making decisions around their demand predictions, so how to forecast demand, how to plan their supplies, how to plan their production, how to plan for their inventory levels across their supply chain network.

And the way we do that is by creating a digital representation, a digital model of their physical supply chain that incorporates all the nuances and all the gory details that encompass the physics of the supply chain. So what constraints exist on a shop floor, what constraints and configurations exist on a dock door in a distribution center. How to think about the interdependencies across that supply chain network. If you make a change to demand downstream, how does that impact your production plans upstream.

All of those representations are contained within our semantic representation within the Kinaxis platform. And then with that representation, we then have curated decisioning engines for coming up with the best answers for these different use cases. So obviously, on the forecasting and demand planning side, we use a heavy dose of machine learning techniques.

On the supply planning, production planning, inventory planning side, we use a heavy dose of very complicated and sophisticated optimization algorithms and heuristics algorithms. And of course, in the last few years, we've been leaning in on using the reasoning capabilities enabled by LLMs or generative AI. And more and more, we've been leaning in on developing agentic capabilities as well.

So we've been heavy users of predictive, prescriptive and then more recently, generative and agentic AI. So that's an overarching picture. What we have done is we've created this platform, a single code base, a single platform. So it's not something that has just grown through a mishmash of acquisitions. We have a lot of proprietary technologies for a company of our size, we have a very rich patent portfolio and some deep tech surrounding this.

For how we represent concurrency in the supply chain, how we enable an in-memory architecture that is very foundational to what our customers do with us, how we enable scenario planning, which is super important, especially when things are changing so much in the supply chain and with all the volatility and the variability that has existed in the supply chain and that volatility keeps growing, by the way. And with all those technologies, we bring it to life with our teams, our field teams, our partner ecosystem. And that's what really sort of forms the shape of both our innovation cycles, but also our go-to-market and customer delivery cycles.

So hopefully, that gives you an overarching view of where we are. The key thrust we have is we are continuing to stay focused on our core of supply chain planning and decisioning -- we feel there's plenty of room for us to continue growing in the 7 verticals we operate in. And then the second layer to that growth really is in expanding beyond just planning into how do you action those plans, how do you operationalize those plans.

And that's where we've announced earlier this year our vision and our game plan for operational orchestration that is leaning in and harnessing the power of new semantic and ontology architectures, agentic AI and a composable platform, and we are bringing that to life with forward deployed engineers. And the reception and the interest level we are seeing from our customer base is very encouraging. And while we are early in that journey, we are definitely seeing a lot of need and demand and interest from our customer base. So that's where we're at. I'll stop there.

And Herb, I don't know if you want to add to that.

No, I think it's well said.

Yes. Don't worry, Herb. I've got specific questions for you coming. Yes. I mean -- so you mentioned a lot about the product and the tech there. And I want to get to all of that in a little bit. But I'm just going to stick on the theme here of the demand and the appetite just for a little bit longer here.

I think those of us who have covered Kinaxis for a while, longer than the 2 of you that have been at the helm here, we've seen in recent cycles where there's been major impacts on supply chain, some degree of disruption. I mean, whether it was tariffs or fuel costs, which are current, or things like COVID, that was certainly an example.

You saw a bit of this period where the customers focused on putting out the fires and there was a little bit of a lag and then a wave of adoption of new tech in the wake of that. I think I'm characterizing that accurately. And the question to you here is, given everything that's going on and the timing of all this, where do you feel you are if you picture Kinaxis adoption in waves right now?

Look, I think we are still early in that journey, right? We have less than 450 customers. But most importantly, let's talk a little bit about what's happening in our customers' operating environments, right? And some of it is situational to industries. But in general, both the demand and the supply side is becoming more variable, right? So I'll give you some examples of that.

Obviously, when it comes to the high-tech value chain, there's been a surge in the whole build-out of the data center, which is creating significant pressures and constraints in the entire value chain, right? Constraints shift all the way from wafer capacity on the semiconductor chip side to energy and utility companies being able to power them, and we're working with that entire value chain.

On the other hand, you look at industries like pharmaceutical and life sciences, where the velocity and frequency with which new products are getting introduced are growing very rapidly. And that's causing for new supply chain models to come into play, right? For example, one of our customers has one of the GLP Mounjaro offerings where perishable fluids, vials and syringes had to come together in a supply chain, which is seeing unprecedented demand, right?

And we had to build a new optimization solve for how to bring these things together for this pharmaceutical company. That same company, by the way, also has a tablet version of that, that is going through FDA approval, right? Now all these shifts and changes create a bigger need for the Kinaxis platform. In the CPG industry, in FMCG, for example, we have some large global players where there's a generational shift happening in consumer behaviors.

It's sort of like some -- a certain generation, like my mother's generation does grocery shopping once a week, once in 2 weeks. And my nephew, they shop for the next meal. And the supply chains required to service those different generations look very different from each other, right? And there are other examples that are caused with changes because of geopolitical shifts, the wars that are happening around the world with the different tariff regimes, the regulatory changes.

So as the world is getting more and more variable, right? And as Ray Kurzweil taught us, the pace of change is not linear. It's only getting exponential. The key thing supply chain professionals are trying to grapple with is -- I mean, change is an input. They don't control that change. But how do they deal with all this change is the key question. And how do they minimize the latency between picking up these change signals and making smart decisions and then from the latency between making those smart decisions and actioning them, right?

That's the space that we are playing in. And we see the sense of urgency from our customers and the discussions I have with Chief Supply Chain Officers, with the digital transformation teams of our customers, where we are continuing to see significant prioritization for solving for these problems because they're at the very core of what these companies do.

Not to do that, we have to make sure we have the best technology, the best platform, but we also have the smartest people to solve these really complex problems. And from an adoption perspective, we are still very early in that journey.

Yes. Let me dig in a little bit on that. I mean, yesterday, you talked about the new customer momentum was very strong, the 40 go-lives in the pipeline. I do get questions frequently in trying to understand the significant amount of white space that's still within your existing customer base as you open up new growth vectors and work through your product development initiatives.

You talk about an NRR of over 100%, pretty big figure, if I could poke at you a little bit on that. I just want to generally just visit and ask about that white space within your customer base. And if you could maybe provide us with a sense of the amount of room left to go. I don't know if you've got any numbers or anything that you could share or range as you think about the penetration rate of your solution even within your existing customer base?

Because when I go to your user conferences and other supply chain events, I'm often struck by how fragmented the deployments are within some of these organizations.

Yes, it's a good question. So I'm going to start with your last point first and then sort of talk a little bit more about the white space. Supply chain management is one sort of term, but it's made up of a lot of different subprocesses and a lot of different underlying systems that underpin that.

There is no one single system of record for the entire supply chain. We are one of those systems of record for planning, but there's a whole plethora of other systems like transportation management systems, warehouse management systems, order management systems, sourcing systems, manufacturing execution systems that are also systems of record for various other subprocesses.

So just keep that in mind. I mean it sounds very simplistic to say supply chain management, but there's a lot of different subprocesses and systems that underpin that. When it comes to our customer base, your question is a good one, Doug, because we've been doing some really granular analysis on the white space available within our customer base. And the conclusion we've come to is the opportunity is significant for us to expand within the existing customer base.

And that's obviously coming to bear as you've seen some of our results in Q2 and Q3, where expansions within existing customers have been a growing share of our overall net new ARR, right? And there are different flavors in terms of what those expansion opportunities are. In many cases, we may be working and we may just have license with one business unit. And now we can sort of expand to additional business units. So we may have been working with a subset of the product lines or we may be working with the aftermarket service repair parts of the organization.

Now we are working with the finished goods part of the organization. So all kinds of expansion in terms of business units. The same kind of expansion may exist regionally, like we may start in North America or in part of Western Europe, and then we may be rolling out to other global parts of their organization. Sometimes those create significant expansion opportunities for us.

And then third flavor for the white space is as we've been adding additional modules to our R&D and innovation cycles, we just have a lot more to take back to our existing customers and cross-sell to them. Examples of those include we've all within the same platform, but we've recently added a whole production scheduling capability that is net new, machine learning-based forecasting capability. We're in early adoption with our advanced inventory optimization capability that we're going to scale out as we go into 2027.

All of our agentic capabilities. These are all cross-selling opportunities within the existing customer base above and beyond what they may have deployed with us. And then the last thing we've done here is we've created a dedicated customer -- current customer-focused farming sales team, right? And that team is becoming super productive because there's all these significant expansion opportunities within our existing customer base.

So we tend to agree with you that there's -- that's a significant growth opportunity for us. And then as we lean in and build out this operational orchestration footprint to operationalize the plans, again, that will even further expand the TAM within the existing customer base in a very profound way.

So if I could -- yes, I mean, lots to take into consideration there, but summarizing, significant TAM within your existing customer base that is yet untapped. You've done work on it. You're perhaps not going to give us any numbers or anything around it, but early in the evolution of what Kinaxis could be within any single customer. Is that fair?

Yes. What I'd like to tell my team is we can be double the size we are within our existing customer base, right? That's the size and scale of the opportunity.

And that customer base continues to grow every quarter.

That's right.

So all right. Let's get into the AI type questions. You can't avoid them these days, not that you want to. And I want to start, I guess, another question I find myself constantly fielding, I mean, really with every software company, but in Kinaxis specific, even as the term SaaSpocalypse fades from everyone's mind here a little bit in the last couple of months.

A big picture question for the generalists out there, they're seeing all these unbelievable advances in these models and their abilities to quickly optimize outcomes. And they'll sit there and Kinaxis is not a tool that they use day-to-day and many of -- most of us don't. But it is a tool for optimizing outcomes as well. And so I constantly find myself fielding the question, even with all the growth and success you're continuing to show why a sophisticated customer can't jam the same data into some horizontal frontier model and a supercomputer and have it solve those.

And I know that's a very crude way of asking the question. But honestly, as I say, I continue to get it. So I just want to attack that head on with you so that you can make it clearer for everyone why Kinaxis is necessary in the future, agentic future.

Sure. Well, firstly, we love AI, right? And we love every advancement in AI, and we want to be at the forefront of applying the latest in AI to our domain of supply chain planning, decisioning and orchestration. So I'll start with that.

The second thing is when it comes to -- I think what you're talking about are LLMs, so Claude, OpenAI, I don't think you're referring to optimization models, machine learning models, right?

That's what the investors see, right?

Yes. And look, we love harnessing the power, the reasoning power of LLMs. And these LLMs, which are built on these multi-tiered neural networks, they are creating new opportunities for us to provide a conversational interface to our platform. They are allowing us to expand and democratize the usage of our platform across a much broader set of stakeholders.

And Agentic AI is creating all kinds of new possibilities for us to create new automations that drive a lot of productivity improvements, but also to help reimagine the flow of work, the ways of working and decisioning for our customer base. So all that is really good. Now what these LLMs don't do is a few things, which will continue to be within the purview of what we have to invest in incremental to applying these LLM models and agentic models, right?

The first part is what I talked about is representing the physics of the supply chain. That context is very important, right, for the LLMs or the agents to really be able to do anything smart, right? And building out that context and that semantic model of the physics of the supply chain network is something that we've spent decades honing in on, and it's complicated. And I want to make sure you understand why it's complicated, right?

Supply chains are not in the ether. They're in the physical world, right? It's on shop floors. It's in warehouses, distribution centers, dock doors, pallets, containers. And there are constraints. There's constraints around material availability, parts, capacity of production sites. There are ships that need to operate that you need to understand. So representing those constraints at the minutia and granular level of detail is very critical before an LLM or an agent is able to really make sensible decisions.

The other thing that's really important is the supply chain network, part of the physics is that you have to understand the interdependencies in that network, right? If you have a shortage in incoming parts into a manufacturing plant, what is the impact of that to a customer order that, that particular finished product is sent to?

Or if you make a change to downstream demand, how does -- how should that change your upstream production plans? Those kinds of bidirectional network-wide interdependent kind of understanding, what we think of as the concurrency representation of that supply chain network is very critical for these agents to understand. And I've used those examples with some of the investors just to give you the scale of the complexity in the domain we play in.

When Merck makes a change to the expiry date of a single ingredient, it results in over 18,000 recalculations in Maestro, right? That's how connected these things are. And that's also why we -- across our customer base, we're doing over 300 billion to 400 billion calculations a month, right? So this is not a simplistic domain. I remember a former executive, CEO telling me Razat, a SaaS CEO telling me in the Silicon Valley, Razat, why are you in the supply chain domain? This is really hard stuff, right?

Like all these hard problems. Why do you keep spending all their time and solving these hard problems. We are [indiscernible] for that at Kinaxis. We love solving hard problems. And thank God, we're solving hard complex problems because they don't just go away with vibe coding or with using LLMs. I think LLMs have a very important role to play in that stack, right? And we are leaning in and embracing the use of LLMs and agents in our platform, but they don't replace the need for this model representation of the complexity and the minutia details of the supply chain. So that's the first part.

The second part is with that representation, we are making decisions around what to manufacture in what quantities, in what locations, in what time frames for customers that may have anywhere from 5 to 100 different manufacturing sites. And they may be manufacturing anywhere from 2 or 3 products to tens of thousands of products, right? And so when you look at the explosion of the permutations and combinations of what an optimal plan looks like, it explodes into hundreds of millions, sometimes hundreds of billions of permutations and combinations.

So you need advanced mathematical models where we are using Linear programming and Mixed-Integer programming techniques with solvers that providers like Gurobi and NVIDIA are providing or with machine learning constructs or models that Google DeepMind is providing to us to solve those in a very mathematical way because these decisions our customers are making, they are to the tune of -- they impact tens of millions to hundreds of billions of dollars of inventory decisions and product decisions. So they have to get it right, and they have to be very deterministic, right?

And by the way, those calculations don't get done by LLMs that are designed for predicting and looking at patterns based on text and image data, right? That's why a lot of the things we're doing we are leveraging the models from Google DeepMind, Gurobi, NVIDIA and the open source world in addition to layering on top of that LLMs from a reasoning, from an inferencing and from simplification and explainability of what these models are doing.

So it's an important part of the stack, but it doesn't replace the need for these advanced mathematical models and these decisioning engines, right? And if you don't believe us, go and talk to Google DeepMind and go and talk to NVIDIA because they're investing in these solver models, and we are applying those to our domain, right? So that's -- those are the things to keep in mind. So we love the advancements in LLMs. We are big users of these LLMs even within our own operations, and we've seen significant productivity in our coding velocity, in our engineering velocity and all kinds of internal functions.

We're embedding that into our platform, and it's part of our agent harness as we're building out our composable architecture. But they don't replace the need for the supply chain context and the model representation with all the complexity and they don't replace these advanced mathematical models that need to underpin the decisioning engines for our customers for the use cases we service. So that's what's important to keep in mind. I know it's all very confusing for a lot of people because it's a technical discussion. But the way to think about it is that is in terms of a stack.

Yes. Well, I just -- I mean, maybe I want to simplify that a little bit just to make it maybe I'll talk about -- so there's the data that is customer proprietary to your customers, and that is -- I mean, not yours. And then you've got all this advancement on top, LLM, the compute power, the calculation models, all that, that's being built by others. And your position sits in between. And that is -- and I get...

Yes, can I say something -- we have one of the systems of record as well. So for our customers, when they need to understand what is the forecast for a given product or SKU or a unit, that gets computed and derived from our platform. Or if they want to know what is the supply plan or what is the inventory policy in their network for different segments of products, the system of record is ours. That gets derived and computed through our platform. So we are at the system of record level as well. So just keep that in mind.

Yes. I just wanted to illustrate that. And then your 20, 30 years, whatever, of developing the sophisticated physics of the supply chain models is very proprietary to you and not replicated easily even if someone was trying to with some new technology that's coming out or coding it, as you say.

Yes. And in fact, what we are seeing is in the world of agentic capabilities, a lot of those proprietary capabilities we have like our versioned database, like scenario planning, it's becoming more important, right? And so as we think about sort of the next 12, 18, 24 months, customers will be building agents on our platform, and we have an agent harness to help enable that and an agent studio to help enable that.

I fully expect that there will be third-party agents that would be part of a different stack, but that need to extract data or that need to ping our scenario planning engine or doing iterative replanning on our platform, right? And so -- and that's why that was one of the big reasons why we've evolved our pricing structure to the activity unit. So it gives us a fair and transparent way of monetizing those use cases and still being very relevant in that go-forward future where there will be multiple agents from multiple providers, all doing different bits and pieces of the way that an organization functions.

So yes, I was going to say you kind of led me to the next area I want to move on to, which is I think we've covered the big picture and now really moving on to how you are monetizing this because a lot of this change has necessitated a change to your revenue model and how you're pricing certain new elements that you're developing on behalf of customers and getting away from seat-based licensing and all that.

So maybe this is where I can get Herb activated here. You were asked a pile of ways yesterday on the earnings call about MAUs and how that new pricing model is being accepted by your customers. But maybe just do you want to talk through where you are in the process of evolving your revenue model to be more reflective of the value that you're adding to customers versus some of the legacy models that you had in place, maybe even as recent as a couple of years ago.

Sure. So Doug, maybe just to take a step back one, Kinaxis as a company, pre-AI even or -- excuse me, pre-generative AI has never been a company where growth was dependent on a seat-based license model based on the number of human beings using our product, right? It's not like a classic CRM or HCM type of system. So I think that's something that's important for the investors to understand.

You're ahead of your time there.

Yes. Yes, we were ahead of our time there. Look, it's the nature of the way -- it's the nature of the value of what we provide, and this ties directly to what was just being discussed. The value that we provide is in answering for -- helping the client answer a very fundamental question, which is what should I do? What is the action that the organization should take? It's not what's the value to one individual user, okay?

So I think you understand that. Now the way our next-gen pricing model works is there is a platform fee, then there is a module fee, okay? So think of modules as just whether it's our advanced demand forecasting, our advanced inventory optimization, okay, our scheduling, any of our modules, okay? There's an additional fee based on how many modules you use. And then what has been introduced is that the client also gets an allocation of Maestro activity units, the MAUs, okay?

Now something that it's important for the investors to understand is that with the MAU model and what I've just described, you can see that with the platform fee and the module fee, those are predictable recurring revenue for us and it's predictable recurring cost for our client, okay? Now on the initial allocation of the activity units, those are set and discussed with the client based on what their anticipated usage is going to be. So this isn't a model that is a pure consumption, hey, for every time you use the platform or a module, there's an incremental bill or dollar cost to you, okay?

So it's within the package. So something also that people have to understand is if we and the customer get the initial sizing right on the allocation of the MAUs that's a part of their subscription package, it shouldn't be the case that 1 month later, 1 week later, they're coming back to us and saying, "Oh, you know what, I'm out of activity units, I need more, okay?" That's not what the clients want, okay? And frankly, for us, we like the predictability of a subscription model as well, okay?

So what happens is, let's say, a client for consecutive quarters is using more than their MAU package allows, then there's a conversation with the client that says, hey -- and by the way, they have full visibility into what their MAU usage is as do we. So then there's a conversation that says, "Hey, you're using more than your package now a few quarters in a row, whatever the duration of the time period is, okay?" It's time to upsize your package. Or are there ways for you to make your usage or change how you're using the product so that you're back within your package. So I'll pause there, Doug, and just see if there's any questions about NGP.

Well, I've got one from one of the attendees related to this. And there was a bunch more about how the process of converting your customer base, how that's going to unfold here, timing, whether upon even having that conversation and moving to this new program, I'll call it, is there a natural lift there as that happens? Maybe you could just explain how you've witnessed that work you've done so far.

Yes. So a few things, Doug. So NGP for us is relatively new, right? We just announced it earlier this year. So if you think about, let's say, our average contract duration is somewhere between 3 to 4 years.

So it's just on renewal.

Exactly, right? So there's one element, which is as our clients are renewing, okay, every new proposal that goes to an existing client on a renewal, they are getting the NGP package or the NGP proposal. The second thing is that now all new proposals to new clients, they are also going out with NGP, okay? So this isn't something that is just go to the client base and just you flip a switch and now everybody is on NGP, right?

So it is something that's going to take time as we migrate customers over to. Now on the question of whether there's an uplift, there's an uplift just in the sense that any time there's a renewal with the customer, there's an expansion opportunity, okay? Because when we are at renewal, we're taking a look with the customer even before NGP, you're having a discussion with the customer about, "Hey, what are you using? Do you need more sites, et cetera, et cetera, et cetera? There's more modules."

So there's always an expansion opportunity on renewal. And as part of this discussion around what is the right MAU package for you, okay, on a renewal or we are looking at what their usage is likely to be.

Yes. And just to add a couple of more things to that. Obviously, any new proposals going out are leveraging the next-generation pricing, this MAU pricing structure. And also, as we are positioning the agentic capabilities to our customers, existing customers, they are with the NGP construct in place.

Okay. All right. We've got a little over 10 minutes left, and I've got 100 questions left. So let's try and do some quick hitters here. I mean I want to her just because you're a newer face around the story.

And I guess I'll start with a question I've got here, which is Kinaxis for the last 3 quarters has performed very well against guidance, against expectations. I think every single quarter, you've been -- I've heard the term conservative with your guidance get thrown out there by either me, investors, some of my contemporaries and...

Quarters.

I know, but even before that. And I guess what I think would be helpful for investors is to just understand your philosophy around guidance. That could be for both of you, but I'll pick on Herb. Just we're going to come into a new annual guidance period here, I guess, in a few months.

And I think it would just even qualitatively to understand your process in building up so that we -- and with some of these new revenue model items and things that we're considering, I think it would help us just to frame up when we do see that initial guide, how you've arrived at it.

Sure. Well, Doug, thank you for asking the question. And I did try to talk a little bit about this yesterday in the context of Q4. So the beautiful thing about our recurring revenue model is that you and we have a high degree of visibility, especially sitting in Q4 with 2 months left. You take the Q1 through Q3 as reported SaaS, you add the RPO to that just as a starting point.

Now we did have people ask us, okay, well, we did that same math and geez, that wasn't even the bottom of your SaaS growth, okay? But we do have -- yes, you asked that as well. And I think what I said or I know what I said was we do have to take into account FX volatility because we are guiding on an as-reported basis, not a constant currency basis, okay?

The second thing that we look at is we look at the renewals that are upcoming, which you don't have the benefit of seeing. We look at renewals, renewal timing, right, because there's only 2 months left in the year. We look at what is in our pipeline. Again, we also don't have visibility -- perfect visibility to be able to predict, does that new ACV deal come in on December 30, and therefore, we get 1-day rev rec? Or is it going to come in on November 15, right?

So there's variability there. So we take that into account as well. And that's how we build everything related to software that we have that RPO type of visibility. Services, we take into account that Q4 is -- there's seasonality there just because of the holidays and so on. So we take that into account as well, and that's how we get to the total revenue guide.

Okay. Well, I mean, I think I understand the 2 months left in the year, it's very tight. I was asking the question more in the context of a full year and how you might go about starting just so we know where the points of upside and -- where they can come from. Maybe we'll move on from there. I've got -- again, I've got a question from myself, and it ties in with one from the audience here about partners at size.

I think people are looking at some of the behavior of some of the Accenture and other stocks here in the services. You've got this FDE model. I'm going to try and tie 4 questions together here. You've got this FDE model -- you've seen Accenture with other software vendors, Workday, for example, say we're going to do the FDE part as well. And I just don't -- I think there's a lot of confusion as to ultimately what the FDE model will look like as all these software companies talk about it now.

And the services partners are obviously not going to be willing to just give up all that potential revenue. And you were early to this. It's probably a little earlier for you to say. But if I can get you to prognosticate maybe, Razat, on what you think the end state will be, at least quickly. That's a big expansive question, but your thoughts.

Totally understand. And look, we are mobilizing our FDE parts, and we've mobilized it now in North America, Europe and India and we're beginning to work with the early adopter cohorts of our customers for this operational orchestration expansion that we're doing. But we have a lot of interest from our partners, and we are absolutely going to be involving the partners as we scale up, right?

In fact, some of our partners are already beginning to join some of our boot camps for our new operational orchestration platform, which is the composable platform that we've been developing and building on. They're already training on that. They're doing boot camps, actually providing us good input and feedback into that as well because we want them -- I mean, to scale this, yes, initially, we want to make sure we know how to use it ourselves and leverage it to deliver value to our customers ourselves.

But the only way we're going to be able to scale that business is through our partner ecosystem. So the likes of Accenture, EY, Kearney, which is a former A.T. Kearney, other more niche providers like Trillium and others, we've been having discussions with them already and involving them in some of our operational orchestration discussions with customers. And in some of those early cohort of customers, we are already working jointly with our partners.

So the FDEs are not only coming from Kinaxis, they also encompass skill sets from our partners to jointly develop the solutions for our customers, right? So I don't look at this as either/or or sort of a competing fight with partners. We'll be -- we are developing the platform, the composable architecture, and we want to kind of mature that to a state where our partners can use that to develop and build the orchestration use cases and solutions for our customers through their FDE resources. We just had to have a starting point, so we knew how to do that ourselves. That's all.

Okay. I'm going to bounce around here just to get a couple more in. The competitive landscape, I mean, some of it because of the fact that these are owned by bigger institutions, we don't have great visibility into what they're doing. But I mean maybe I love what you've said in previous conversations, Razat, about how SAP, for example, as a primary competitor is taking a bit of a different tack with respect to openness and around the AI.

Is that still the case in your mind? And maybe you could just talk about where you've had the confidence to embrace AI versus other approaches and maybe delineate that for us a little bit.

Yes. Look, I think we, as a company, have been early users of applying AI of every shape and form. I've personally been a user of and a student of AI and applying it to the supply chain domain for 28 years of my career. And one of the things I've learned and particularly given the way that enterprise and systems architectures are evolving we have a strong belief system around the need for interoperability.

We fully are committed to innovating on our platform and really creating additional capabilities and IP using AI. But we also fully understand that our platform and our system and whatever we do is not going to be sitting on an island anywhere, right? We have to interface and interact with other systems and agents from other enterprise stacks.

And all this is moving quickly and rapidly, but it's all in still in very early stages, right? And we know that there's change afoot in the enterprise stack for our customers. Exactly where will be the landing point of that I don't think anyone can -- we can all speculate on that, but I don't think anyone knows the answer to that. And frankly, the decisions will not be made by any of us on the technology side. It will be made by our customers, right?

And so given where we are in that cycle, we see -- we are, of course, building agent harnesses and semantic intelligence layers and agentic capabilities. We also have a core system of record with that model representation that I talked about in decisioning engines. But agentic capabilities are being developed by SAP, by ServiceNow, by Palantir and others. It's -- they're being developed by niche upstarts, early-stage companies.

They're also being brought to bear in our customer base with large enterprise AI platforms like Google Gemini, like Databricks Genie, like Anthropic Claude, now even Meta has announced that they're going to be coming into the enterprise space. And so we, as Kinaxis, we have to remain agnostic. We have to be able to interoperate with multiple of these platforms. And the good news is the new MCP protocols, A2A protocols, all the integration architectures, they allow for that, right?

We showed demos together with Microsoft at our Kinexions Barcelona event, where the interface into Maestro was a conversational interface through Microsoft Copilot. So no one was even logging into our own platform. They were able to interact and in natural language, engage in all the things that they need to do with Maestro. We can do the same thing with Google Gemini, with Databricks Genie, with Claude, Anthropic, right? And so given the extent of our customer base and given that their enterprise stacks are emerging and evolving and fluid, we have to maintain optionality.

I'm a big believer in maintaining interoperability because it allows for us to have optionality. It also allows for us to leverage our core platform, which is all the things I described earlier with agents that are coming from other platforms, from other right, and still be able to monetize that through that next-generation pricing and the MAU infrastructure we have. So that's the way we're working through it. And there's a lot of twists and turns with what other vendors are doing, what other companies are doing.

But ultimately, we want to stay focused on the first principles of what are the customer pain points, what are the outcomes they're trying to achieve and how can we stitch that together into the fabric and the landscape that our customers are engaging in.

Okay. I'm going to get one more in because some of these U.S. clients won't forgive me if I don't ask it, just your updated thinking on a U.S. listing and your commitment to that in the coming year. That might be a quick hitter, but I thought I'd just dispense with that one before we close down the call.

Yes. Doug, look, we and the Board are always focused on finding ways to expand our investor base. At this point, we haven't made a decision around any timing for potential U.S. listing. But when we have an update, we will update all of you.

Okay. Well, I promised I'd ask the question. We're up -- it's 11:00 Eastern anyways. So we've run out of our allotted time. And so I'm going to conclude the call here. So for the attendees, thanks for joining us. To the Kinaxis team, I appreciate you giving us the opportunity to help educate investors on the Kinaxis story and maybe step back a little and look at the bigger picture here. It's obviously an exciting future for this name. So to both you and the attendees, have a great weekend, and thank you for your attendance.

Thanks, Doug. Bye.

Thank you, Doug.

Good morning, and welcome to the Kinaxis Inc. Fiscal Third Quarter 2026 Results Conference Call.

[Operator Instructions] I'd like to remind everyone that this call is being recorded today.

I will now turn the call over to Victoria Hyde-Dunn, Vice President of Investor Relations at Kinaxis, Inc. Please go ahead.

Thank you. Good morning, and welcome to the conference call. Joining me today are Razat Gaurav, Chief Executive Officer; and Herb Yeh, Chief Financial Officer and Chief Strategy Officer.

Before we begin, we have a couple of reminders. We will be discussing our third quarter 2026 results, which we issued after the close of markets yesterday. The earnings press release and slide presentation are available on the Investor Relations website at investors.kinaxis.com.

Some of the information discussed on this call is based on information as of today, November 5, 2026, and contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those set out in such statements. For a discussion of these risks and uncertainties, please review the forward-looking statements disclosure in the earnings press release and in our SEDAR+ filings. Additionally, we will discuss IFRS results and non-IFRS financial measures, including adjusted EBITDA. A reconciliation between adjusted EBITDA and the corresponding IFRS results is available in our earnings press release and MD&A, both of which can be found on the Investor Relations section of our website and on SEDAR+.

With that, it is my pleasure to turn the call over to Razat.

Thank you, Victoria, and thank you all for joining us today. I will start today's call with my observations on the third quarter. Herb will then review financial results and updated guidance before we open the call for questions.

First, Kinaxis delivered a strong third quarter, driven by new customer logos, renewals and expansions across our customer base amid healthy demand as organizations manage increasingly complex and volatile supply chains. Second, we are executing on our five strategic priorities as one connected approach to building and scaling the business, investing in Maestro, building an agentic framework for operational orchestration, executing our new FDE motion, providing training and enablement for our growing partner ecosystem and staying focused on customer success to deliver value. Third, after three consecutive quarters of outperformance, we are pleased to raise our full year guidance for total revenue, SaaS revenue growth and adjusted EBITDA margin. We have momentum heading into the fourth quarter and remain focused on execution. Let me discuss these topics in more detail.

Turning to our third quarter performance. SaaS revenue increased by 22% year-over-year. This marks our third consecutive quarter of 20% or better SaaS revenue growth. We achieved a new record, surpassing $1 billion in remaining performance obligations. Annual recurring revenue grew 19% year-over-year and 20% year-over-year on a constant currency basis. We are on track to exceed $500 million in annual recurring revenue by year-end, an important milestone. New business was healthy again, driven by expansions with existing customers and new customer logos. Specifically, 40% of ARR additions came from new customers. ACV bookings for quarterly expansion from existing customers grew more than 60% year-over-year. This quarter, we set a new company record with the largest incremental ACV expansion deal. We also closed several large enterprise new wins and renewals under our next-gen pricing, our hybrid pricing model that incorporates Maestro Activity Units or MAUs.

Now let me turn to our customers. New customers are selecting Maestro to replace manual fragmented planning with connected real-time decision-making. We are pleased to welcome Biogen to Kinaxis as they advance a major end-to-end planning transformation across their global pharmaceutical network. With Kinaxis, Biogen will connect planning across demand, supply, inventory, clinical and distribution, giving teams greater visibility and the ability to evaluate complex trade-offs concurrently. Maestro will enable Biogen to make faster, more resilient supply chain decisions while maintaining the service levels that matter most, getting critical medicines to patients around the world.

Dr. Squatch, a fast-growing American personal care and grooming company, is a new Kinaxis customer. As Dr. Squatch manages demand across multiple sales channels, it is turning to Kinaxis to create a more unified and responsive planning environment. By moving away from manual spreadsheet-driven processes and leveraging real-time scenario planning, Dr. Squatch expects to improve forecast accuracy, better balance inventory across channels and reduce lost sales during peak demand periods.

We're also pleased to welcome WAI Global, a global manufacturer and distributor of automotive aftermarket components to the Kinaxis community. WAI Global selected Maestro to strengthen its S&OP processes, leverage advanced simulation capabilities and explore the significant potential of agentic AI. A major manufacturer in the life sciences industry has selected Maestro as its long-term supply chain planning platform. By improving inventory exploration management and integrating production and distribution planning, the company is building a more agile, responsive supply chain with a scalable foundation for future global growth. And we displaced a competitor at a global consumer health company that is adopting Maestro to gain a holistic view of demand, supply, production and inventory.

As I mentioned earlier, this quarter, we signed the largest incremental ACV expansion deal in our history. This automotive customer significantly expanded Maestro across the business unit as part of its global supply chain planning transformation. Its goals include operating with greater agility, making more precise end-to-end decisions, responding faster to disruptions and capitalizing on emerging market opportunities. We are grateful for the trust they continue to place in us.

Next, I'd like to provide an update on the five strategic priorities we outlined last quarter. First, we are investing in core Maestro platform capabilities. It was a pleasure to welcome customers, partners and prospects to Kinexions EMEA in Barcelona last week. Registrations more than doubled at this year's event and partner participation nearly tripled as supply chain leaders from across the region joined us to explore practical ways to turn AI-driven planning and orchestration into tangible business outcomes. At the event, we outlined the next phase of our product and agentic AI strategy across two connected areas: advancing Maestro with intelligent agentic capabilities for planning and decisioning and extending our reach with a broader AI-native composable operational orchestration platform.

We're expanding how users interact with Maestro through richer conversational AI and semantic understanding, while embedding agents and LLMs directly into workflows so they can interpret context, evaluate information and support decisions as part of the operational process. At the same time, explainability is being extended into advanced optimization, helping users better understand the factors behind recommendations and strengthening trust as predictive, prescriptive, generative and agentic AI become more deeply embedded in decision-making. Underpinning this is Kinaxis Data Fabric. It provides governed data pipelines for AI, analytics and decisioning while extending that information into the customers' broader data and analytics environment.

Our second priority is building a composable agentic framework for operational orchestration. Operational orchestration helps customers act on decisions, not just make them. It is a composable, interoperable and extensible stack that includes multimodal data ingestion using the same data fabric, a semantic intelligence layer for the context graph, a decisioning layer that leverages Maestro and other third-party engines and agent harness and a democratized experience layer.

We've seen customer engagement with agents continue to deepen. Agent sessions doubled over the last month. Token consumption per agent continues to rise, indicating that agents are performing more work. Agents are executing increasingly sophisticated workflows, averaging about 15 steps per session and in some cases, exceeding 50 steps. Together, these trends show that customers are increasingly engaging agents to turn decisions into action. At our recent Maestro agent hackathon, customers build agents on our composable platform. Examples include a network aware demand investigator, and order feasibility and constraint resolution provider and a supply shortage root cause investigator. These examples demonstrate how Maestro agents can transform time-consuming planning tasks into actionable insights.

Our third priority is scaling our new forward deployed engineering motion. As enterprises move from AI experiments to deployments, the opportunity is to transform how work gets done and deliver measurable, sustained business outcomes. To do this, our forward deployed engineers bring together deep supply chain expertise with data engineering, data science and solution development expertise. Our teams work alongside the customer and our partner ecosystem to shape the opportunity, co-build the solution, deploy it, drive adoption, measure the value created and continue to evolve the capability in an agile, iterative way as the customers' needs change. The model also creates a learning loop back into Kinaxis. What we learned from solving real customer problems can inform reusable technology capabilities within Maestro and our operational orchestration platform, helping turn successful customer innovation into increasingly repeatable approaches that benefit the broader markets.

Kinaxis is now operationalizing FDE parts across North America, Europe and India. A growing number of customers are engaging with us on AI-driven supply chain transformation. We expect to share more about this, including customer use cases and additional details during our Q4 earnings call.

Fourth, our doubling down on training and enablement for our growing partner ecosystem. Partners are increasingly helping us create demand, enter new markets, accelerate large enterprise opportunities and scale customer delivery. Year-to-date, customers have been involved with partners in about 75% of our software bookings. We've launched a new learning and sophistication platform and are running boot camps focused on enterprise scheduling, Maestro Agent Studio and supply chain optimization. 14 partner firms participated and workshop attendance increased 24% quarter-over-quarter.

Our global systems integrator relationships are also evolving. Historically, partners were often viewed primarily through an implementation lens. Increasingly, we are engaging with firms such as Accenture, Deloitte, EY, PwC and Genpact earlier in the customer life cycle, focusing on opportunity creation, transformation strategy, AI and delivery. Additionally, partners such as Accenture, Kearney, EY and Trillium have leaned into our FDE motion by participating in our AI and operational orchestration boot camps. Our relationships with Google Cloud and Microsoft are increasingly shifting beyond infrastructure to broader go-to-market and joint innovation partnerships. As we build out our operational orchestration strategy, we believe hyperscalers and enterprise AI platforms can become increasingly important channels to customer buying centers. These investments expand our partner reach and strengthen customer engagement alongside our direct field teams.

Lastly and most importantly, we are focused on customer success to deliver value. Complex supply chains face constant disruption from supply shortages and shifting demand to fluctuating lead times. We see a much larger opportunity to help customers reduce the latency between signals to decisions and decisions to actions. We are seeing momentum in value delivery among customers. As a proof point, global scenario planning activity increased 29% year-over-year in the third quarter. A few customer examples include the following: a medtech customer that improved forecast accuracy by 7% with our machine learning-based forecasting solution, avoiding $28 million in inventory and a petrochemical customer who leveraged Maestro to reduce demurrage costs by 15%, inventory by 14% and supply chain emissions by 90%.

We completed over 40 successful customer go-lives in the third quarter. For example, Asahi Beverages, a leading beverage company leading -- recently went live with Maestro, bringing demand, supply, capacity and inventory planning together across their businesses in Australia. By replacing disconnected planning systems with a unified concurrent planning environment, they can now better anticipate supply constraints, optimize inventory and evaluate scenarios to make faster, more informed decisions across their manufacturing and distribution network.

As I wrap up, we are very pleased with our strong performance this quarter. We are harnessing the power of new data architectures and Agentic AI, and we are adding top talent globally in critical areas such as machine learning, operations research and FTEs, all to create value for our customers. Supply chains power the world, and Kinaxis is the operating system for supply chains. Thank you to our global team for your continued execution and to our customers, partners and shareholders for your ongoing support.

Let me turn the call over to Herb.

Thank you, Razat, and good morning. Let me start with our third quarter 2026 results compared with the prior year. Unless otherwise noted, all figures are reported in U.S. dollars under IFRS.

Starting with revenue. Total revenue was $160.3 million, up 19%, driven by strong SaaS and professional services revenue. Foreign exchange rates negatively impacted total revenue by approximately $1.1 million. SaaS revenue was $112.3 million, up approximately 22%. This represents 70% of total revenue, up from 68% a year ago. Growth was driven by momentum from new deals, strong net expansion and renewals among existing customers and healthy retention rates. Foreign exchange rates negatively impacted SaaS revenue by approximately $800,000. Subscription term license revenue was $1.2 million and above expectations. Several expansion deals with existing on-premises customers drove this growth. We expect subscription term license revenue to be about $7 million for the fourth quarter and about $33 million for the full year.

Maintenance and support revenue was $4.6 million, down 16% as expected due to on-premises to SaaS migrations. We continue to see interest among on-premises customers looking to migrate to our SaaS offerings, which gives us the opportunity to help customers modernize. Professional services revenue was $42.2 million, up approximately 14% and above expectations, with realized rates reflecting the value of our premium services. We continue to expect mid-single-digit full year growth as we shift more implementation and support work to systems integrator partners.

Turning to remaining performance obligations. SaaS and total RPO balances and growth remained robust with total RPO surpassing the $1 billion mark, an important milestone for Kinaxis. Total RPO grew to $1.03 billion, up 21%. SaaS RPO was $979 million, also up 21%, highlighting the strength and visibility of our recurring business. Over the last three years, SaaS RPO has a cumulative average growth rate of 21% and total RPO has a CAGR of 20% Next, annual recurring revenue increased to $483.9 million, up 19%. ARR grew over 20% year-over-year on a constant currency basis to $486.8 million. Ongoing strength in our $1 million-plus ACV contracts and net expansion with existing customers drove $77 million in net new ARR growth year-over-year and $18 million in net new ARR growth sequentially. Approximately 40% of additions to ARR were from new customers and approximately 60% of additions to ARR were from customer expansions. Most customer growth came from enterprise or large enterprise customers, reflecting our continued upmarket focus.

Now I'd like to move on to our third quarter profitability metrics. Gross profit grew 22% to $104.5 million. We delivered a gross margin of 65%, up 1.3 percentage points. This was driven by a higher professional services margin and a more favorable revenue mix as professional services as a percentage of total revenue declined. Our subscription software margin was 77%, down from 79% a year ago. As we noted on our Q2 earnings call, hosting costs are temporarily increasing as we migrate from private data centers to the cloud. We remain on track with the migration and still expect to complete it by the end of 2027. Professional services gross margin was 32%, up significantly compared with 24% a year ago, reflecting higher realized rates in the quarter. Operating expenses were in line with expectations.

For the full year, we expect sales and marketing to grow in the high single digits, R&D to grow in the low to mid-double digits and G&A to grow by approximately 20%, inclusive of stock-based compensation compared with last year. Excluding stock-based compensation, G&A is expected to grow by approximately 15% compared with last year. Adjusted EBITDA increased 24% to $42 million, reflecting strong revenue growth, healthy gross margins and efficient operations. Adjusted EBITDA margin was 26.2%, up 1 percentage point year-over-year, positioning us well to raise full year guidance. Profit rose 19% to $20.1 million with an effective tax rate of about 22% for the quarter.

During the third quarter, we repurchased more than 244,000 shares for approximately $29.5 million. Since that program began last November through the end of September 30, we've repurchased more than 1.4 million shares for $163 million at an average U.S. dollar price of $11.12. This reduced the total outstanding share count by 3.5% on a net basis. Yesterday, our Board of Directors approved a new normal course issuer bid plan, subject to TSX approval that allows us to repurchase up to 2.7 million shares during a 12-month period ending November 11, 2027.

Turning to cash. We ended the third quarter with a strong cash position. Cash flow from operating activities was $34.4 million, up 2%. Cash, cash equivalents and short-term investments were $317.9 million, down from $324.7 million at the end of last year, even with $138 million from share repurchases. Free cash flow margin was 21% in the third quarter, down 3.1 percentage points year-over-year. Trailing 12-month free cash flow margin was 24%. Higher revenue and a reduced share count led to diluted EPS of $0.72, up 25% year-over-year. That sums up the Q3 review.

We delivered better-than-expected top line results over the past three quarters and remain confident in our Q4 trajectory given the momentum we are seeing among new and existing customers and across go-to-market opportunities. As a reminder, our new FTE motion is not expected to contribute meaningful revenue to our full year 2026 results. With this in mind, we are raising guidance for the full year ending December 31, 2026, as follows: we now expect total revenue to be in the range of $640 million to $650 million, an increase from our previous guidance range of $625 million to $640 million. This represents approximately 16.8% to 18.6% year-over-year growth. We now expect SaaS revenue year-over-year growth to be in the range of 20% to 21%, an increase from our previous guidance of 18% to 20%. This represents a range of approximately $435 million to $438.5 million. Lastly, we now expect the adjusted EBITDA margin to be in the range of 26.5% to 27.5%, up from our previous guidance range of 25% to 26%.

For full year modeling purposes, I'd like to provide some additional details. First, we expect foreign exchange rates to remain a headwind for the rest of the year given the strengthening of the U.S. dollar against the euro, the British pound and the yen. For the full year, we estimate FX-related headwinds to total revenue between $3.5 million and $4 million and to SaaS revenue between $2 million and $2.5 million. Second, we expect full year basic weighted average shares outstanding to be approximately 27.3 million shares and diluted weighted average shares outstanding to be approximately 27.9 million shares. These share count forecasts do not include the impact of any future share repurchases we may pursue.

Thank you to our global team for delivering another strong quarter. As we head into the final stretch of the year, our focus is straightforward: to continue to execute well, serve our customers and partners, innovate and finish the year strong.

Operator, we're now ready to take questions.

[Operator Instructions] Your first question from the line of Thanos Moschopoulos with BMO Capital Markets.

Your Q4 guidance seems quite conservative if we look at the RPO that you have for Q4 heading into the quarter. Is that just a function of -- are you expecting a sharp sequential step down in PS revenue? Or are there other factors to call out?

Yes. So Thanos, thank you for the question. Look, we delivered a strong Q3 across revenue, recurring revenue growth and profitability. And that performance, together with the increased visibility we now have into the balance of the year allowed us to raise our full year outlook. And you're right that we do have a high degree of visibility into full year revenue. At this time, we're 10 months through the year. The thing I'd point out, though, that we factor in is that for a new SaaS booking following this earnings call, at most two months of the associated annual contract value would be recognized in the current year. Professional services for the balance of the year is also largely visible. So the primary or principal timing variable is really subscription term license transactions, where a greater portion of the contract value is recognized upfront.

The other thing I'd point out is that our guidance is on an as-reported basis, and it incorporates our current FX assumptions while allowing for some normal FX variability through the year-end. So overall, the updated outlook reflects continuing to invest for growth without a significant change in our spending trajectory. So that's the point around how we thought about margins.

Thanos, just to add one more thing to that. Sequentially from Q3 to Q4, just from a seasonality perspective, PS is typically lower in Q4, just given the holiday schedule, which is pretty normal, and we factored that into our guidance.

Your next question is from the line of Doug Taylor with National Bank.

This is Mike Stevens on for Doug. Congrats on a very strong quarter again. I wanted to dig into the MAU and the pricing model. You mentioned a lot of the enterprise wins were including that. Any sense yet? I know it's early days on what kind of impact that will have on margins in the future? And even revenue growth, is that expected to sort of be an accelerant on revenue growth? Or any insights into that?

Yes. So one thing to underscore about MAU and next-gen pricing is that it's a usage-based model. So meaning the customer as part of their package will have a certain allocated number of MAUs. And as long as they stay within their MAU usage for the quarter, that provides them predictability around what their cost is, and it gives us predictability and visibility into what the recurring revenue is. As the clients grow their usage, if they go through the allocated MAU usage, then it's not that they get a surprise bill that says, "Oh, by the way, you blew through your cap and therefore, there's a bill. But it's a conversation with the client that says, "Hey, your MAU usage is trending above what's in your allocated package. So it's an opportunity to grow into a larger MAU package. We are still early in the adoption of MGP and MAU. We are seeing traction, as Razat mentioned on the call earlier. But what we're trying to balance is giving the client visibility and predictability on what their growth is, while providing us that same visibility on the revenue line, but also capturing usage that comes with Agentic AI.

Your next question is from the line of Kevin Krishnaratne with Scotiabank.

This is Richard on for Kevin. Congrats on another strong quarter. Just a quick question on M&A. So looking ahead to 2027, are you able to talk about capital allocation? Any thoughts on M&A? Are there any key areas of focus or gaps in the portfolio that could be supported by acquisitions, either tuck-ins or transformational one?

Yes. Thank you for the question. So our philosophy and approach to M&A, no change from what we discussed on the last call, which is we're very, very focused on executing against our strategic road map. You heard Razat talk about our priorities around continuing to invest behind Maestro, continuing to invest behind our composable operational orchestration platform, the FDE motion -- so any M&A that we think about and that we would do would be things that accelerate the plan that we have, okay? So that's one very critical important point.

The second is that, as we've discussed previously, our thinking around M&A is not M&A for the sake of cost synergies. It's not M&A for the sake of just buying revenue. It is for the sake of accelerating road map that our product road map that ultimately translates into more value for our customers and revenue synergies that we can execute on and thereby deliver value for our shareholders. We don't foresee anything that I think you might -- or shareholders might think of in the transformational range given what I -- or size, given what I just said about the types of things we'd be looking at. There will be things that would accelerate our own organic road map. So these are things that are much more likely to be of the aqui-hire tuck-in types of transactions. Does that help?

Your next question is from the line of John Shao with TD Cowen.

I think it's interesting to see a global consumer health company moved away from a competitor. I believe you also won Asahi Beverages. So is this some kind of new normal that you're gaining momentum in the consumer vertical, which has historically been dominated by competitors like Blue Yonder?

Yes, we're definitely seeing a lot of traction in the consumer packaged goods, FMCG, food manufacturing space. So we play on the consumer manufacturing space in general. We're definitely also seeing a lot of opportunities to replace old legacy systems, old legacy deployments as organizations aspire to a different paradigm when it comes to supply chain planning, decisioning and orchestration. So it continues to be a really strong vertical for us, and we see continued traction in this space.

Your next question from the line of Mark Schappel with Loop Capital Markets.

Nice job on the quarter. Razat, as customers move into the newer MAU-based pricing model, what are you seeing in terms of like adoption spending? Is it just making it easier to get more users on the platform and then grow revenue as it expands as usage expands? Or is it just mainly the benefit of simplifying the initial sale?

Yes. I think as we are getting into this MAU-based pricing structure, which, by the way, is structurally similar to what a lot of other enterprise software companies are doing, right? What we're finding is, it just allows for the customer and for Kinaxis to really be able to service and employ a broad variety of use cases, right? And what I mean by that is a lot of our deployments now involve automated workflows, agentic capabilities or in some cases, even like headless deployments, right? So through an MCP server. So we're able to kind of meet the customer in the way that they want to deploy our solution and work with our platform and interface with our platform in the way where they're already working.

And at the same time, we are the system of record for supply chain planning for our customers, right? And so when not only our agents that are developed on our platform are leveraging that data, but also third-party agents that are leveraging that can access Maestro data are pinging our platform, it allows us a way to really be able to monetize the access to that data. So it's a multifold approach. I don't look at this as a way for us to grow the number of users on our platform necessarily. If anything, supply chain planning and decisioning use cases have never had a very large user or seat-based count, right? And it just allows us to deploy the solution and be able to monetize and provide predictability to our customers in the world of Agentic AI, which is becoming more and more prevalent in the use cases and deployments that our customers are working with us.

Your next question is from the line of Paul Treiber with RBC Capital Markets.

Just a question on the sustainability of growth momentum here. You've seen growth accelerate -- ARR growth accelerate for a number of quarters now. The comps are getting tougher. How do you think about the growth going forward remaining in the 20%-plus range?

Yes. So of course, we're not providing guidance for 2027 yet. We will do that on the next earnings call. But what I can tell you is, with all the continued volatility and uncertainty in supply chains, it's creating a higher sense of urgency across our customer base to lean in and make investments in Kinaxis, right? And customers are prioritizing the funding and the provisioning of investments in Kinaxis. And so that's a very encouraging sign. And as we do that and as we invest in our Agentic AI platform and we expand further into operational orchestration, we are seeing tremendous interest from across our customer base, right? For example, we've held hackathons. We've held boot camps at our Kinexions Barcelona event. We're going to do the same thing at our Kinexions India event coming up in about a couple of weeks from now. And these are all oversubscribed, right?

So all of those indications point towards the fact that we have a strong demand environment. Our pipelines are continuing to grow. So we feel really good about this. But our goal here is to do everything possible to continue to sustain really high growth rates while maintaining a disciplined approach to margin performance, right? And we'll definitely provide more details on this in the Q4 earnings call in February.

Just on the investments with the raised EBITDA margins, it's now above, I think, previously, you had a 25% medium-term target. Does that -- for the performance being better than a target this year, what are the drivers of it? Was it just investments taking a little bit longer to ramp than you expected, or was the outperformance on the term license side?

Yes. I think -- thank you for the question. It's an important question. I think a big driver of that, if you think back to the beginning of the year to where we are now, is a much a higher STL number than we had anticipated at the beginning of the year. And you'll recall STL, it's a significant pull forward in revenue recognition versus our SaaS revenue, but you don't have the same pull forward on the cost to serve on the COGS. So there's a very direct flow-through from a higher gross margin through to the EBITDA margin. So that's been a big driver of that relative outperformance in the EBITDA margin. That being said, we continue to invest for growth, but in a very efficient manner. And that's also been a part of it, which is just operating efficiently while investing behind the innovation that Razat referenced earlier today. So it's a combination, but STL is a very important driver of it.

Your next question from the line of Suthan Sukumar with Stifel.

Congrats on a very strong quarter. For my first question, I just wanted to double-click on the FTE model. Can you speak about -- or rather, can you share a little bit more about some of the initial traction that you're seeing with this model? And in general, how do contract values for an FTE-led deal compared to a typical deal?

Yes. No, thank you for the question. we launched the FDE motion just a few months ago, and we've been mobilizing the pods in North America, Europe and in India. And as I mentioned in my prepared remarks, these pods involve a mix of deep supply chain domain experts, process experts, data engineers as well as data science and solution development expertise, right? So the interest we are seeing in -- from our customer base is quite significant. We are involved with a number of our existing customers that have deployed Maestro and are now looking to extend beyond the planning and decisioning into how they operationalize those plans. And supply chain systems and supply chain processes are very complex. They're very fragmented. They have multiple systems of record. And as we thread together different outcome flows through our FDE engagement model, we are finding all kinds of opportunities in helping our customers go above and beyond just stopping at planning.

So the early indications are very encouraging from our point of view. And it's also a great opportunity for us to leverage the base we have for Maestro customers where we have the trust, where we have an understanding of the customer supply chain and then extend beyond that into threading together these outcome flows. So that's what's happening there. Obviously, we're working with some of the early adopters and are creating MVP solutions. And I'll be sharing a lot more details on some of the example use cases in our Q4 earnings call in February, but early indications are, again, very, very encouraging.

Okay. On the net new ARR added this quarter, can you guys speak to the attach rate of AI offerings on these deals? And you guys did flag some encouraging agent and token usage stats in the opening remarks. What do you expect MAU usage, the whole usage component to become a more meaningful component of this AI monetization as I believe that AI is still being -- your offerings are still being sold as a premium proposition.

Yes. This is Herb. On that question, it's still early in our transitioning first of clients on to the next-gen pricing, which includes the MAU usage component of the subscription model. We don't have right now sitting here, the data points to share with you that says exactly how much uplift has come or resulted from the introduction of this. We've just started now with every -- we talked about it last quarter, but we're still relatively early. Every new proposal that's going out is next-gen pricing that has the MAU subscription component. So we'll update as this continues to evolve for us.

Yes. And just to add a little bit to that, just kind of level setting here, right? We have always been leveraging in 100% of our customer base, predictive and prescriptive AI, right? And then more recently, we've been adding generative and agentic AI capabilities. So 100% of our customer deployments include AI, right? So I just wanted to mention that, firstly. When it comes to Agentic AI, it's becoming a bigger and bigger factor in customers, both net new logos making a selection of Kinaxis is becoming a bigger and bigger factor and in existing customers expanding with Kinaxis. So we're seeing really good and strong uptick in Agentic use cases. There's a whole broad variety of Agentic capabilities. We've obviously added a conversational interface to our entire Maestro platform.

We have got a Maestro Agent Studio, which we launched earlier this year, which creates a composable studio for customers and partners to build agents. And we are seeing a lot of creativity around that at Kinexions in Barcelona, several customers like Jabil, like Sanofi and others talked about examples of use cases that they've leveraged our Agentic Studio for. And then as we expand beyond planning and decisioning into operational orchestration, they very much lean into leveraging both the semantic intelligence layer, but also Agentic capabilities that traverse a context graph. So AI is very native to the Kinaxis platform. And what I want to make sure people understand is there is no Kinaxis solution without AI, right? So we've been AI native from day one.

Your next question is from the line of Stephanie Price with CIBC.

It's Sam Schmidt on for Stephanie Price. I wanted to ask around the pipeline. Can you give an update about what you're seeing in terms of pipeline conversion and comment on your level of optimism about RPO levels going forward? I know Q4 is typically seasonally strong for bookings. Can you share any color on what you're seeing so far?

Yes. Thank you for the question. The pipeline is trending strong. We're definitely seeing as we -- as our sales and go-to-market teams get more and more disciplined, the quality of the pipeline is improving, which shows up in the yield rates. Our win rates have been improving, like I mentioned previously in last quarter's earnings call as well. And so we're really happy with the progress we're making both in terms of the quantum, but also as importantly, on the quality of the pipeline. And the key sort of industry verticals that are driving a lot of the growth in the pipeline include some of our core verticals like in life sciences, especially in pharma and med devices, aerospace and defense, the whole high-tech value chain as well as in industrial manufacturing and consumer products. So in every one of these key verticals, we are seeing increased traction in our pipeline and also better win rates. I'll let Herb talk about the RPO questions you had.

Yes. I think we continue to feel good, just as Razat mentioned about the demand environment that we see. The RPO growth that we've seen in the last few quarters, we are very, very pleased with. And we're not giving forward guidance for 2027. And as you know, we don't guide on our forward RPO or ARR. But I'll leave it at we feel good about the overall demand environment, the quality of the pipeline and the win rates that we're seeing.

Yes. And look, really proud of the fact that RPO crossed $1 billion, which is fantastic. Obviously, we continue to be focused on signing multiyear committed deals, and that hasn't changed and will continue to be the case going forward.

[Operator Instructions] Your next question is from Lachlan Brown with Rothschild & Co. Redburn.

Congrats on the quarter. I was wondering if you could expand on the Kinaxis Data Fabric a bit further. Specifically, how much does it improve data ingestion and that contextual understanding of supply chain data? And also, how are you monetizing? Is it included in the core Maestro platform? Or is it sold as a separately craft module?

Yes, Lachlan, thank you for the question. I hope you're doing well. Data Fabric has been an important development initiative. We've built it on the Databricks platform. And really, there are multiple use cases for Data Fabric. Primarily, of course, it's for the data ingestion and the integration into a variety of systems where we source the data from for our customers' data. Also, Data Fabric is very important as we think about the machine learning pipelines we have that feed into a lot of the algorithmic capabilities that underpin, for example, our demand planning and forecasting solution. And also Data Fabric is the same data fabric that feeds both our Maestro planning footprint as well as our extending into operational orchestration. It's the same data fabric, right?

So it's an important part of our core platform that enables us to have a common data foundation across everything we do and allows for multimodal ingestion. So what I mean by that is, it can extract ETL data. It can have structured data, unstructured data as well as streaming data, right? So it really allows us a lot of flexibility and a lot of scale for us to be able to leverage with our customer base. It's also allowing for archiving since we are the system of record for supply chain planning for our customers, a lot of our customers are now going to be able to use our data fabric to also archive scenarios and worksheets and other things like that. So it's a really core component. In terms of the way we are packaging it, Data Fabric is a core part of our platform fees. It's embedded as part of that, and we are not pricing for it separately. And of course, based on the usage metrics, it feeds into our MAU pricing structure, as you would expect. So that's the way the pricing and the packaging works.

That's very helpful. And if I could also ask, did those 40 customer go-lives in the quarter, did they come in faster than expected? And if so, was there any contributing factors to that, like, for example, quicker deployments from AI efficiencies with your SI partners?

Yes, that's a really good question. We continue to be very focused on making our customers successful. As you can imagine, we are solving really hard problems for our customers, right? And a lot of these deployments involve significant amount of process changes, operating model shifts. And so there's a lot of change management that underpins our deployments. Having said all of that, we are seeing incredible opportunity to improve the time to value using Agentic AI as part of our deployment methodology, right? And we'll talk more about this in 2027, but we are doing a lot of work in a focused way to further accelerate the way we integrate our solution to other systems, the way we configure it, the way we test it and go to the QA environment as part of the implementation cycle.

So every step in that deployment cycle can be made more efficient and can be accelerated using Agentic AI, and we're leaning in on that, right? And that's really a welcome sort of shift from our customers' perspective. So more to come on this, but early signs are that despite all the work, there's always an advantageous approach to taking in the way we implement. And Agentic AI is helping us reimagine our approach to implementing our solution as well.

There are no further questions at this time. I will now turn the call back to CEO, Razat Gaurav for closing remarks.

Thank you so much all for joining. And again, a big thank you to the entire Kinaxis community, our employees, our partners, our customers. We really appreciate all the support and the momentum we have and looking forward to speaking to you in the new year. Thank you so much.

This concludes today's call. Thank you for attending. You may now disconnect.

Welcome to day 2 of Citi's Global TMT Conference, starting here right after the lunch hour with Razat and Herb from Kinaxis. Welcome.

Thank you for having us. Thank you.

Maybe just to start, Razat, if you could just -- for anyone newer to the name, if you could just talk us through the journey Kinaxis has been on, how do you think about positioning the company today?

Yes. So Kinaxis, we're a software technology company headquartered in Ottawa with a global presence. We're the leaders in the supply chain planning and decisioning space. And we have a long history in working across 7 verticals with some of the leaders in our industry. And we've been really focused on helping companies make decisions across demand, supply, production, inventory using predictive and prescriptive AI. And of course, as we speak and as we are investing and going forward, more and more, we are expanding, which is a very significant expansion for us into agentic orchestration. So going beyond planning and decisioning into really operationalizing those plans. And we're doing that with strong leverage of both generative AI and agentic AI embedded as part of our platform.

Got it. Let's dive into that shift from supply chain planning to a broader orchestration platform. Can you kind of help make that a little more concrete when you think about the operations of your customers? What is changing on a day-to-day basis?

Yes. So look, our customers tend to be leaders in CPG, life sciences, pharmaceutical, automotive, high-tech, aerospace and defense, those sort of verticals. And they use our core Maestro platform, the Kinaxis Maestro platform to help inform their planning decisions. But there's a gap that exists between establishing those plans and then to execute on those plans to operationalize them, right? And that's where in the supply chain domain, there is a plethora of functions or subfunctions, people and different systems that are involved in that operationalization of those plans.

Leveraging modern data architecture, semantic architectures, leveraging agentic architectures, we have a strong capability to really be able to stitch together and compose those orchestration use cases while leveraging our planning roots as the brains to how orchestration happens. And that's a pretty exciting expansion opportunity for us. It's something that we've been working on with different components of an expanded platform stack. And we're also mobilizing because in this engagement model with our customers, a lot of our customers have pain points and they have outcome aspirations, but they don't really know exactly what the feature function requirements are.

So it requires a forward deployed engineering engagement model that allows us to do the discovery with our customers and prospects, establish what the feature function capability should be and then to co-build with them leveraging our composable platform and architecture.

Got it.

That's really the path and journey we're on. And obviously, we have a core planning business that continues to grow and do very well and has been gaining momentum in the last several quarters. But then we have a very significant expansion opportunity with orchestration as well.

I think the traditional framing of the supply chain software world has been this split between the planning side versus the execution side. Do you -- when you conceptualize orchestration, does this imply you moving into the execution side? Do you view this as some sort of a bridge between the 2 worlds? How do you kind of think about that?

Yes. If you were to ask me this question, let's say, 3, 4 years ago, right, the decisions we have had to make in terms of our product strategy would be to build or buy execution systems. Given the new semantic architectures and given agentic AI, we don't have to do that anymore to get into the execution time horizons. We can ingest data from the plethora of execution systems that exist. We can map it into a common semantic and ontology layer and then that feeds into a context graph that we then are able to traverse our agents with, right?

So it's definitely with operational orchestration, we are getting into the more execution time horizons without having to develop or buy all the execution systems that exist because there's a whole plethora of them, right? There's systems for sourcing, for order management, for transportation management, warehouse management, et cetera, et cetera. And the other unique thing about being in that operational time horizon is the orchestration use cases can take lots of different permutations and combinations. So you've got to be interoperable with these different systems, but you've also got to be composable. And that's a very fundamental design principle we have in our platform.

Got it. Maybe, Herb, we can bring you in here on this idea of -- it sounds like some of these specific execution categories are not something maybe at least today that you're considering buying into. You brought in not only as the CFO, but you have the strategy piece as well. When you think about adjacencies that make sense from a potential tuck-in standpoint, what comes to mind?

Yes. I think, George, the way to think about it is twofold. One is there are a set of, I'll call it, core underlying enabling infrastructure technologies that could potentially be interesting to us. But to be clear, these have to be things that accelerate our own internal product and technology road map, right? So that's one thing. The second thing is there is a difference in terms of how we go to market in some sense and interact with customers with the FTE motion, right, with the operational orchestration offering because it's not a get an RFP, get an RFI and respond to a list of requirements that the customer has given you. So it requires a different type of capability.

So to the extent that there may be opportunities for us to, again, accelerate the organic investments that we're making in building out that type of capability, those are the types of opportunities that could be interesting to us. But to be very, very clear, everything that we're thinking about right now, whether it's organic investment or through the M&A lens, these are all things that are designed to drive very clear revenue growth, revenue acceleration types of scenarios for us. We're not focused on the, I'll call it, the consolidating types of acquisitions that are cost synergy driven.

Got it. On this movement, again, to a broader orchestration platform, do you feel that changes your competitive landscape that you play against? Maybe just to start, if you could frame kind of how you think about your competitive differentiation? And then is it -- do you feel like that's evolving in terms of the landscape of players you're up against?

Yes. Let me answer that question first. I mean if we think about the evolution of Kinaxis and our Maestro platform, there's some very core differentiators, and I'll list out 3 of them, right? We are the richest digital representation of the physical supply chain and how it operates. And that's very complex because it's highly interconnected. It is highly constrained because supply chains exist in a physical environment on dock doors and shop floors and pallets and containers. And we incorporate all of that into the Maestro model, right, and also all the policies and the governance that happens in how these supply chains function.

And with that digital representation and we have a core principle around concurrency because if you make small changes in demand downstream, how should that impact your production plans? You have changes in inbound component parts or materials, how will that impact your ability to fulfill orders to customers that may be pegged against those items, right? Those kinds of concurrency bidirectional interdependencies are reflected in the Kinaxis Maestro platform in a highly differentiated way and it's one of the big reasons why customers work with us. So that's the first reason.

The second is in having a very sort of a patented and a proprietary in-memory database architecture that really allows for high fidelity and significantly high performance with complex compute and algorithms because a lot of the use cases we have and actually, almost all the use cases we have involve some form of machine learning, optimization, heuristics or a combination thereof, right? And that in-memory architecture is incredibly powerful. And the third one, as part of that is, we have a very differentiated database architecture that's our own. That's pretty deep technology that allows for versioning in a way that scenario planning is a highly differentiated capability. Most of our competitors will say they do scenario planning.

But when our customers -- when we are able to get customers and prospects to take a look at the way we have architected and the way scenario planning functions in our platform, it's the speed, it's the flexibility and the propagation of these scenarios across that concurrent network, a combination of those things are highly differentiated, right? So those are the existing differentiators. Obviously, we are continuing to invest in R&D. We invest roughly 18% of our revenue back into R&D. We have a very rich patent portfolio, over 100 patents. We've got over 200 patents that have been filed that are pending.

This year, we've already filed close to 50 patents. 46% of those are in AI use cases applied to the supply chain. So it's a very sort of a rich and a thriving R&D and an engineering and a product development function. In terms of how that competitive landscape is evolving, obviously, there are traditional players that we compete against. There are new and emerging entrants.

And of course, our footprint is also growing, both in planning and now with orchestration. And so it's a fragmented landscape. What I can say is we're very focused on the first principles of our customers' pain points, how we create value for them, making sure we can do what we say we're going to do and deliver the value, and that's leading to a strong flywheel, which is resulting in very high win rates, all-time high win rates in the first half of this year.

Got it. I think specific to maybe the competitive landscape, many of the players you play against have broader product portfolios across maybe ERP or supply chain execution or other areas of the stack. When you think about competing against those relative to the competitive advantages you just outlined, how do you -- what's kind of the playbook there?

Yes. Look, we've competed against ERP players who've been in the supply chain planning space for more than 25 years, right? So SAP and Oracle had supply chain planning footprints. We, of course, coexist with their ERP layer. But our differentiation and our positioning is very specific to the complexity of our customers' supply chains.

When customers have scale, complexity, global multidivisional elements, complexity could be reflected in the network, in the complexity of the bill of materials, in the level of variability and change in the volatility in their supply chain operations. We just have a very highly differentiated capability, which is why the likes of Unilever and Ford Motor Company and General Motors and Qualcomm and Merck and hundreds of other customers work with us.

Got it. On that point, you just listed off a great list of strong logos. There's many more on that. I think about the total customer base, 400-plus customers, it is relatively tight relative to the size of the business. You have very deep relationship with large enterprises. When you think about the new logo opportunity, where do you see the most opportunities? I think about the data center build-out, maybe some of the oil supply chain shocks is maybe introducing some new opportunities. What comes to mind for you?

Yes. Look, we have expansion opportunities with existing customers, and then we have a ton of net new logo opportunities as well. The way we go about servicing that market and covering that market is in a very disciplined, focused way. We play in 7 verticals. For each of those verticals, we've got specific use cases and templatized capabilities. We've got great reference bases. And we are seeing a lot of growth in the high-tech value chain, obviously, with the surge in the data center build-outs. And that is extending beyond high tech into like manufacturers of cooling units and energy and utility companies that are seeing a massive surge in demand. And so they've got much more complex supply chain needs and are becoming customers of ours.

So organizations like NextEra in North America, Ansaldo Energia in Europe, they're customers of ours today, historically, we hadn't really targeted them, right? So that whole high-tech and the data center value chain is a great driver for growth. Aerospace and defense is another one. We're seeing a lot of demand and need for our capabilities in the aerospace and defense industry where there's a surge in demand and sort of the need. And they have very complex bill of materials. They've got fairly fixed capacity. And to add capacity, there's a long lead time and massive CapEx investments. So they are, for the first time, really trying to focus on understanding how to build out demand supply planning, sales and operations planning, integrated business planning capabilities, also getting more sophisticated with thinking about their inventory strategies, both for finished parts, but also in many cases, for service and repair parts, right?

So aerospace and defense is a great vertical for us. We are working with the likes of Raytheon and Pratt & Whitney, L3, Bell Helicopter, Rolls-Royce Engine and Lockheed Martin and several others, right? In that sector specifically, we've also initiated our FedRAMP certification, which there's a lead time to that. But by the end of next year, that should be completed. And that will further expand our ability to service the aerospace and defense industry, and it also opens up the window for other federal and DoD sectors that we have historically never covered, right? So what doesn't keep me up at night is the addressable market or the net new logo opportunity.

The more thoughtful element is how do we go about attacking that in a sensible, profitable way and in a way that we can continue to deliver successfully to our customers, not just sell to them, but to actually deliver the deployments because the problems we're solving are complex problems. They're not simple problems. And that's a good thing because it was very simple, somebody would vibe code it, right? And so we want to make sure as we scale up, we're able to continue with that strong track record of trust in delivering what we sell.

Maybe on that point, if we could pivot to the agentic products, kind of talk us through where customers are at, how the journey has gone and getting them into production. You have the FTE model. How has this played out?

Yes. It's a good question. And look, I'll divide up sort of the journey in 3 phases, right? The first phase was pretty -- like, I would say, pretty straightforward, but also table stakes now, which is we took standard LLMs. So we support Google Gemini, ChatGPT and Anthropic Cloud. And we built some RAGs around data sets and documents around these LLMs. We built some agent skills, and we provided a conversational interface to our application, right, to our platform. And that's available now. It's getting good usage. Frankly speaking, the customers almost expect that going forward. So that's in place.

The second phase really was in being thoughtful about building agent skills. And now we have 6 packaged agents and creating within our Maestro platform, an agent studio that customers and partners could compose and build their own agents, having access to all the data and resources available in our Maestro platform. That's something that we initially worked in the beginning of this year with 7 early adopter customers. Since then, we've made them successful. Several of them actually presented at our Kinexions event in June. Now we've opened up the aperture. And as we disclosed in our last earnings call, about 10% of our customer base is in active paid trial mode or in full deployment mode with these Maestro agents.

These Maestro agents are really designed for improving productivity with the usage of our platform, improving usability. There's all kinds of interesting use cases emerging on the demand side, supply side, risk side that we are continuing to support and see with our customers. So that's off the ground, and we're beginning to get some good traction with that. The third phase, which, in my view, is most likely the highest value-generating element for our customers and also as a result, could be the largest growth driver for us going forward is in really expanding into operational orchestration, right, where we are not just stopping at planning, we are extending beyond planning into interfacing with execution systems and really agentically orchestrating the realization of those plans and all the replanning that happens in that operational time frame.

And there, we are just early in that journey. But frankly, is exciting because in my humble view, in enterprise software and definitely in the supply chain domain within enterprise software, the big value is not just going to come from using a conversational interface or a chatbot or in just shaving off 2 hours here, 6 hours there from a user. It's really going to come from transforming the ways of working, rethinking how decisioning is done, rethinking how orchestration is done. That's what's going to lead to business outcomes that our customers really care about because our big value proposition is not to go from someone -- a customer using our application having 200, 300, 500 planners down to 5, 10 planners.

That's -- I mean there's value in that, but that's not going to be the primary driver. The primary driver really is in how we enable our customers to reduce hundreds of millions of dollars of -- billions of dollars of inventory, right? And that only happens when you're able to transform the ways of working, reengineer the processes and to identify a lot of those orchestration use cases.

Got it. Maybe that leads me into my next question of the ROI you've seen delivered by some of these agentic products, I think has been kind of a theme debate at the conference. When you look at the most kind of tangible proof points that you've seen maybe from your leading-edge customers, what does that look like?

Yes. Look, I think organizations are early in that journey in my view, right? The low-hanging fruit has been in just productivity, right? So what could -- what would take 5 days can be done in a few hours, right? And there's value in that, and that impacts headcount and sizing. And of course, our customers are taking advantage of that, and there's plenty of good examples of that happening. But frankly, it's not the biggest revenue driver, right, or value driver for our customers. right? Because our customers, like in the planning and decisioning use cases, they don't have tens of thousands of people and that they can reduce the workforce, right?

We're not in the project management space, for example. That's the case in a different domain. However, in our domain, customers have -- across our customer base, there's over $500 billion of inventory in their supply chains that we are helping plan, right? If we impact that by 5%, 10%, 15%, that's a massive unlock. Customers care about what is the cost to serve from a supply chain perspective. What are the operating costs stuck in the supply chain. Those are in hundreds of millions, billions of dollars as well, right, in many organizations. Or they care about how can I improve my service levels, my on-time and full service levels to our customers, so they can increase their revenue. That is of tangible value to them, right?

So the business outcomes that our customers are focused on from a supply chain perspective are really around cost, cash, service level and risk. And that's where this journey we're on with identifying the planning plus execution life cycle with operational orchestration is going to be the big prize at the end of the day. But to do that and to achieve that, it's not just a technology change. They've also got to make changes to their operating models to their underlying processes. And it's truly transforming the organization, and that takes time, right? And I think enterprises are early in that journey.

Right. I think in addition to time, it seems like it also takes resources like I'm thinking of the FTE model that you guys recently announced. Maybe if you could walk us through what exactly is the scope of an FTE when they go into a customer? Is there a teach them to fish dynamic where once you're up and running on a couple of agents now, they can start to run on their own? How is that working in practice?

Yes. Look, so the FTE engagement doesn't start with a capability or a feature or teaching them about how to fish. It starts with really understanding what is the pain point and the opportunity or value unlock for the customers, right? And so if I'm a large pharmaceutical company with $3 billion, $4 billion, $5 billion of inventory in my supply chain. And I want to reduce that by 5%, 10%, 15%, understanding the picture on where the inventory is stuck in terms of finished products in my distribution network, work in progress in my manufacturing network or inbound materials in terms of raw materials, right?

And then understanding how do you segment that? So the FTEs are really doing the discovery first. And then based on that discovery, identifying how to prioritize the use cases and the tie-in to the outcomes and then using the different components of our platform, being able to build the solution for our customers to really be able to operationalize and realize those business outcomes. In terms of the actual skill sets of the FTEs, really, they are structured in pods. And there are 3 broad skill sets that typically get mobilized. It's a combination of a supply chain process architect, someone who really can understand the domain and get into the guts and the details of the underlying operational elements of the supply chain, typically a data engineering lead because the data is sitting in all kinds of fragmented systems and then also somebody who can really figure out how to bring the system -- the data, not just in terms of the data transfer, but also in architecting the right semantic and ontology layer. So data engineering becomes a very important skill set.

And third skill set is typically data science because you are typically tuning or feature engineering algorithms, could be optimization algorithms, could be machine learning algorithms, could be heuristics or a combination thereof, right? And in many cases, all of those working in concert with the LLMs. So we've got a lot of interesting research happening with Google DeepMind right now, where it's an ensemble of these techniques being used to apply to the supply chain use cases that we enable. So those are the pods that we've mobilized now in North America, Europe and in India. Over time, we'll take it to other parts of the world as well like Japan. But it's these 3 skill sets of supply chain process architects, data engineers and data science coming together and co-building with the customers using our platform.

Got it. Herb, maybe we can bring you in here just in terms of as you start to scale up this FTE model, how much incremental investment is required versus maybe reallocation of resources? Any margin implications we should think through?

Right now, George, we're -- we don't see any degradation to our margins at all. We are investing prudently behind this effort, making sure that the investments are synchronized between the platform being ready, the FTEs being ready, making sure that customer demand is there. So we are not in a mode of build it and they will come, right? The operational orchestration platform was announced at Kinexions. And when we announced it and before we announced it, this was through dialogue with customers knowing that there's a demand there, there's a real business problem to be solved, having the internal expertise on people who have, in fact, led FTE motions, okay? So yes, we're making investments there, but these are all prudent, well thought through investments, and we don't see any near-term degradation to margin from this effort.

Got it. Makes sense. Maybe I'll quickly pause if there's any questions from the audience for Razat or Herb. Okay. Maybe if we could touch on kind of the near-term demand situation. Kinaxis has had good momentum in recent results, kind of beating, steadily raising the outlook. When you think about your initial guide from the start of the year, how do you frame what has gone better than that initial framework?

Well, I think as you point out, George, we've -- we had a very strong first half of the year with roughly approximately 20% growth on SaaS, 20% growth on roughly ARR, better than 20% on a constant currency basis. The guide that we gave for the full year or the updated guide, we did raise guidance. But I would say it's a prudent guide that reflects a few things. One is just we've been in an environment where we have had volatility in FX, and our guide is not on a constant currency basis. There is volatility just on the overall macro environment.

And then the third thing is that because we do, do very large transactions with large enterprises and enterprise, there's always this you can have a swing factor in terms of timing of deals, okay? So the guide reflects that. But we continue to see strong demand. The demand signals are strong, whether that's for new logos and/or expansion. We have a lot of success in cross-selling a lot of the newer applications that we've introduced, things like optimization, demand forecasting and so on. So I think the way to read our updated guide is that there's a degree of conservatism built in, but one that we think is prudent, but there are upside levers.

Continue to land the new logos, continue to expand our direct selling motion. All of you can look at what our productivity metrics have been if you look at it on a magic number basis. That continues to be strong. So sustaining that and then seeing the benefits of the investments that we're making in partner enablement, right, to extend our reach. So there's -- we see upside as well.

Yes. And look, I think in the first half, if you think about our growth, like Herb outlined of 20% in SaaS revenue year-over-year growth, roughly 20% in ARR growth on a constant currency basis, even higher. That's about 500 basis points higher than 12 to 18 months ago. So that's a significant acceleration, right? Now personally, I'm not an expert in stock markets, but I don't think we're getting the credit for it given what's happened with the whole market sentiment towards software companies. But there's a dissonance between that concern in the investor market versus what our customers are telling us, not just verbally, but in the substance of what they're transacting with and how they're trading with us, right?

So we're seeing growth and acceleration. And part of what we're working on right now is how to sustain that over a long period of time as we scale up and grow the business, right? And we have a high degree of confidence that we can hit the revised increased guidance we provided, but it's pretty exciting with the momentum we have. We just want to make sure that as we take on more business, we can continue to deliver successfully to our customers with our organization and with our broader partner ecosystem as well.

Got it. Maybe just with our final minute, any closing thoughts on what gets you most excited about the future for Kinaxis?

Look, I think we're on this journey to reimagine and sort of reshape the future of supply chain planning, decisioning and orchestration, right? And I've been in this space for 28 years now. And I've never seen a time like this to innovate. And that's super exciting for a product person like me. And I'm excited about the impact we can have in terms of business outcomes with our customers. Of course, as we pursue that opportunity as we innovate. We're not just innovating or delivering by ourselves. We've got a thriving partner ecosystem.

And the partner ecosystem includes hyperscalers like Google and Microsoft, but also includes technology -- deep technology relationships with the likes of Databricks and NVIDIA and others like that. And then we have a delivery ecosystem made up of the largest consulting firms, SI firms, strategy management consulting firms that play a really important role in our ability to scale up and deliver in a predictable way. So that's the journey we're on, and I'm excited to be scaling the business up and having massively greater impact going forward.

Great. I think we'll leave it there. Thank you all for joining. Thank you both.

Thank you.

All right. Hello, everyone, and welcome to our webinar today. Our topic today is the next phase of supply chain AI from promise to accountable outcomes. So I'm excited about the topic today. My name is Justin King. I'm Field CTO with Kinaxis, and we have the privilege of having some interesting support, a Research Director from IDC, Eric is joining us with some really interesting research that he's done.

And this isn't across a couple dozen of respondents. This is thousands of companies or thousands of responses across companies around the world, different industries, different geographies. So really excited about the perspective that we're going to get today.

So as we kick off, Eric, why don't you introduce yourself to everyone? And maybe just give us a little bit of perspective of what you guys do generically, and then we can dive into this particular research project that you are working on.

Yes, of course, excited to be here, excited to talk about, gosh, what's really kind of a front-of-mind concept for all of us. So for those that don't know me, I actually kind of come more from the practitioner side of supply chain. I worked at Nike for 21 years, just kind of navigated all parts of the company, different geographies and functions. And as you can imagine, you might do in that amount of time.

I have a pretty deep background in supply chain planning, in particular, and have kind of brought that over to IDC, where we -- as you mentioned, we research across just about every company in the world that has a supply chain, and we kind of dive deep on data and information and just bring that sort of practitioner side that I bring, but also IDC brings some really heavy data and focus throughout supply chain and gives us an opportunity to kind of spot trends, have some insights. We work with a lot of people who kind of look like customers of people like yours. So just nice to be here and excited to chat.

Yes, absolutely. So this is not going to be a sales pitch, right? This is really a research-led discussion. I'm going to give some perspective on -- from what our customers have been talking about and asking. And of course, opinions -- there's no shortage of opinions in AI and what it means and what's real and what's not, what's hyperbole and how organizations can start to be successful with AI. And I think that's really where some of your research starts to uncover where supply chain leaders are, where their heads are at.

And we're going to talk today about what comes after initial adoption of AI. And it's the stuff that's not as exciting and sparkly and shiny, right? It's the things like trust and governance and data readiness and guardrails and human oversight and maybe most importantly, how do we get to real measurable outcomes, right, that are aligning to our business objectives and our KPIs. And I think there's a lot of nuggets of important information that we can extract from the research that you guys are doing.

So let's jump right into that. Eric, why don't you kind of set the stage in terms of who was this -- what was your out? Who are you reaching out to? Who's responding to this survey? And I think what you found is that in terms of AI readiness and adoption, most -- everyone was saying they had started something, but at the same time, no one was really saying that they were a leader, right? Everyone was kind of clustered together somewhere in the middle.

So I'm curious on what's your perspective in -- what does that tell us, right? Where are companies on their journey? Do you think we're overestimating, underestimating where you're at? Do you think that's fair in terms of where the market is today with AI? So why don't you start with painting a picture of this research project and who your respondents were and some of the basic learnings in terms of the pool of responses?

Yes, yes. Great point. And actually, before I even answer that, maybe I'll even go back because you just triggered kind of a thought to one of the many roles I held at Nike. I was a Strategy Director for a little while. And I like the way you just worded something, which was sometimes maybe we're not talking about what sounds like the glamorous and exciting stuff. And that was the way I viewed that.

There were times where people would come to me and say, oh, you're a Strategy Director, that's really cool. How can I get that kind of job? And I would often tell people actually, a lot of it is the discipline. A lot of it is building a strong foundation. And when you do that, then you have something you can really build a larger structure on top of a strong foundation. So sorry, you just kind of reminded me of that thought. I thought that was worth underlining because I think it's going to show up through our conversation today, too.

I mean you just mentioned adoption. And I mean, probably most of our listeners today, I mean, are like us, we've all been dabbling with whether you're using ChatGPT or you're using Claude or whatever other tools you're using. And then, of course, supply chain vendors are now embedding these tools within our supply chain functions. We've all kind of played with it.

So to your point, we were asking, I think it was over 2,000 respondents around the globe, kind of all geographies, all industries, different levels of companies, executives, directors, different functions like logistics and planning. And we had almost 98% of people say on some level, they're touching AI or AI is touching their supply chain, let's say. And so the question isn't really adoption per se. It's just kind of how much, how far.

And then in particular, are we realizing value from it. And I think you maybe said too, so maybe forgive me if I'm repeating, but we saw through this data that only like 12% of the respondents, almost barely more than 10% kind of say, hey, we're kind of in the lead here and would -- I think back to my Nike days, we were very competitive. We wanted to be at the leading spot of a lot of things we did. And so there's only like 10% of companies saying that they view themselves as a leader in the space. So it's clearly something emerging and people are still figuring it out.

And then something else we saw, and forgive me for maybe throwing around a few numbers, I'll flash up some slides here in a minute to try to land home on those. But like 50-plus percent, more than half of companies are saying, what's actually slowing us down from going farther and really becoming a leader is just a trust issue with our data, with our systems. Do we even think as we play around with, say, agentic AI, is it really going to do what we want it to do? Is it going to give us the outcomes we want? So kind of seeing all of that.

So okay. So you hit on a really interesting topic, right? And that's trust. And what we're seeing and even as a software company, what AI has enabled is it's so much easier for us now and for our customers themselves to do a pilot, right, to do a POC and to kind of do some vibe coding and say, look, this is the realm of what's possible. Which is amazing because it's democratized access to our data, it's democratized access to mathematical solves and even like machine learning routines and such. So we can quickly and easily see what's in the realm of possible.

But of course, that's being built with no security in place, no governance in place, no logging, no -- none of that structural stuff that I was talking about that's going to enable that trust, right? So as you look at your response, I think you said about half of them are saying, hey, trust is a real barrier. What do you think companies are most concerned about, right? Do you think it's like a technology issue? Or is it more of a, like, process, governance, operating model, that sort of thing?

Yes. And I think back to those days when I was maybe a Strategy Director, one of the issues with really realizing value from your systems is, is your organization even ready? Do you have the skills? Do you have the ways of working even across functions?

You mentioned democratizing, I mean, as agentic AI, as large language models, different things like that, as they help us to cross functions, if I'm an executive at a company, I'm asking, well, okay, but if I unleash all of this, are my teams even going to work together? Are they going to get the right outcomes? What's happening to roles? How do we shift roles? Do I have the skills to leverage all of this?

So I think that's just part of the conversation. And if I may, maybe I will share something. Give me one moment, apologies. Hopefully, this is showing now. Can you see that on your screen?

I do, yes.

Okay. Well, so I think one of the things -- I'm going to come back and answer your question, too. But -- so we see -- we talk about everybody's piloting. And I like that you said proof of concept, whether you want to call it walk before you run or whatever it is, but companies are saying, well, let's at least start to see what we can do in that sort of art of the possible.

But what's interesting is today, if we ask these 2,000-plus respondents in companies all around the globe, like I said, every geography, every industry, every company size, even we looked across, we get consistent answers. You might think maybe some more mature companies might answer differently than others.

But we actually got pretty consistent data where we see that companies are kind of saying, today, in terms of automating things, having autonomous supply chains, we have these conversations about always on supply chains and lights off warehouses and things like that. But the actual autonomy right now, companies are saying it's only like maybe 6% have any form of, sort of, I'll call it, real autonomy.

Meanwhile, 40% say in the next couple years, they aim to get there. So that's a heck of a jump. And so the question then if they're telling us out of one side of their mouth, they're having problems trusting the data, trusting the tools, maybe even trusting themselves to get the outcomes they want. But then they're also saying, yes, in the next couple years, we plan to just, kind of, 7x the amount of autonomy we have.

So one of the things I think, and here's where I'll kind of come back to your question, is if we look at it through the lens of governance, I'm asking even from my old roles, people I know, I'm sort of challenging even -- it's not just the technical side that needs to solve this. I would suggest even there's sort of a 3, I don't know, legs to a stool or something like that, that the capabilities are coming. The tech is advancing perhaps faster than we've even, sort of, prepared ourselves to use it.

Now that -- there's an optimistic side to that because that then means, wow, there's a lot coming that I can really improve my supply chain and improve the outcomes. And so I think what needs to happen is there's sort of a business strategy. Where do we think we want to even use these tools, where do they best apply? And by the way, I know this slide says agentic, but we're talking AI overall, even. I would even almost expand out and talk about a complete AI strategy.

Where do we believe from a business lens, and there's even force ranking from time to time. Are we going after logistics? Are we going after, I don't know, warehousing? Are we going after supply chain planning? Where do we think we really want to sort of place our bets here in terms of the business side? And how are we working together? That matters.

But then also, what I'm suggesting is there's 2 other pieces. One is the technical side of things, where even -- what are the guardrails for these tools? What are they allowed to do? When is human-in-the-loop? We talk about that. How are we going to allow autonomy versus where do we actually want to engage, like I said, with, sort of, human insights. I think it will be something we may talk about today, too, where are we bringing in domain expertise from the humans and things like that.

And then I think an under sort of, I don't know, an undertracked side of all this, we all know that there's some kind of economics emerging here in terms of the use of compute power, whether it's tokens, whether it's value-based pricing, all these things that we're starting to see emerge.

So what are the guardrails even around -- I myself, the first month in my company gave us the sort of, let's call it, Claude tools. I tapped out my tokens within like the first few days because I was just trying to do all kinds of things with it. So how do we put guardrails around even where is the spend and how much are we spending?

So I think -- forgive me for rambling a bit there, and maybe I'll even stop sharing here for a minute. But I think, just, companies maybe contemplating their governance around these issues and how do we even -- what's our own internal strategy? Because then that informs even, what are the partners we work with? And how do we work with them? And all of that.

Yes. I think to -- from what we're hearing from our customers is the magnitude of the impact of the decision can change even inside of supply chain, right? And so you could have thousands of decisions made maybe inside of a warehouse that are much lower risk, and you can look at that in an aggregate and say, okay, is efficiency increasing? Is accuracy increasing?

But then you can pivot to the polar opposite side and say, well, in planning, if one decision means I'm cutting $1 million purchase order, well, the risk and the trust behind that decision has to be -- are both much higher, right? Because there's real constraints in play. If they were not considered, then I cannot produce the finished goods. There's customer commitments, like if I miss this customer shipment, there's financial trade-offs. There's operated -- all these different things that are behind one decision versus just being able to roll it up and look at it in a consolidated number.

So planning is a really interesting one, I think, because of the magnitude of information that's behind every decision, the context that's behind every decision. And in turn, the risk of making the wrong decision. So I agree with you, I think trust is a big part of it. And I think that then leads a little bit into the data side of it, right? So does your agentic system have the right data to make a decision that you can trust?

And I think, if I'm not mistaken, your data had some pretty strong opinions from your responses on how important -- well, not only how important data readiness is, but maybe it being a bit of a barrier, right, and kind of holding companies back a bit. So what can you tell us from what your respondents are saying about maybe their readiness and how they saw the importance of their supply chain data in order to move into more agentic decision-making?

Yes. I think that question definitely came out pretty strongly in the data, Justin. It's where we look at -- and I would even go back. Data quality has just kind of -- it's an evergreen field. It's something we always need to focus on in supply chain. We have data management teams in my time at Nike. I'm sure it's still there. It's something we need to keep focusing on.

So I almost look at it as a coin with 2 sides because, on the one hand, this survey work that we did in the field would say 62% of people, almost 2/3 of our over 2,000 respondents are saying that better data quality, better integration would actually be an accelerator for AI. So there's certainly a focus we need to have on data.

And I would even say, again, from that sort of business practitioner lens, we need to find the right partners, too, that are helping us with that and have contemplated these issues and thought that through. But on the flip side, I would also say -- and now just personal opinion, this is not necessarily the data. I wouldn't say that we should use that as an excuse to not move forward either because sometimes at IDC, I think we find -- some of us have a personal point of view that even the act of moving forward with projects in this space, sometimes itself creates improvements in our data quality.

And so it's kind of, like, it's a chicken or the egg kind of discussion. Do I have to clean up my data to use AI? The answer is yes. But does the act of moving towards these solutions also kind of yield, sort of, data improvements? And the answer is also yes. So I guess it's something that absolutely the sort of survey findings have sort of fleshed out in terms of AI readiness. It's kind of a what's my data quality question. But I also think it's not this, like, go/no-go checkpoint. It's just something we need to really solve and continue to move forward.

Yes, that's a good point, Eric, because AI can even help us with our data quality issues, can it not, right? So you've heard concepts like the self-healing supply chain where maybe you're working with a certain lead time, and you can look historically and figure out, am I building my supply chain plan based on accurate information? AI can help us project it, detect seasonality, all these different things.

So I couldn't agree more, and it's -- I think there's 2 ways to look at it. One is more traditional data quality, like is the data there? Is it proper in the field within some sort of bounds? And then is it, is the context correct, right? I mean, are we defining our constraints correctly, our dependencies correctly, our demand signals correctly?

And then you got the unstructured data side of it, where there's just having unstructured risk signals available, right? Which can give us directional guidance to picking alternate suppliers in those sorts of cases. So there's a lot of use cases where AI can use not clean structured data to help guide decisions in the same way that more structured data and operational context is important as well.

So as we -- so we kind of covered the data side of it, right? And now we're looking at the foundations that are in place, and now we're looking for decisions to come of that. But then we need to balance that with measurable outcomes, right? It's not just better decisions, but it's about the right KPIs, the right business objectives and making sure we're just not using technology for the sake of technology, but we're actually achieving our business objectives. So in a way, AI needs to be accountable to the business, not just accountable to technology that checked the box, we successfully deployed it, right?

So I think some of your findings were kind of highlighting the clear ROI, one is important; and two, would be a driver to accelerate that investment, right? As we look at it less about decision-making and more about achieving business objectives. Did you glean that from the data as well? What are you hearing from the [indiscernible]?

Yes. I think both from a data standpoint, yes, and then even anecdotally for myself, it's -- as executive teams or, let's say, execution teams are clear on your -- whether it's your metrics, your KPIs, your strategic imperatives, whatever it is at your company, when we clearly defined the goal, we had a lot better chance of achieving it. And I think we've even seen that -- I'll just even again say for myself in my own piloting with AI. When I don't get the outcome I thought I was going to get, I often find, oh, okay, I didn't make it clear what I even really wanted from you. I'm sort of using quotes as the AI as a person. But -- and so I've learned to better articulate what the thing is that I want out the other end.

And so now that's back to that governance and that strategic role of are we aiming at days in supply chain? Are we aiming at speed? Are we aiming at cost? What is it exactly we're solving for? And of course, we've got tools now that are starting to even maybe solve for more than one variable at a time, but there's still, what's my strategic priorities? What are the real outcomes I want?

And so you're right. I mean -- and I'm just kind of looking down at my notes, we had more than half were kind of saying, hey, if I'm going to move forward with these tools, I want to have what's the clear return I'm getting. But also there's a lot of folks who are saying, I'm sort of not sure what my business case is just yet. And so that's causing me to maybe slow down a little.

And so there, again, I think whether it's through the lens of business governance and knowing clearly what my strategic priorities are so that I can even inform the AI itself to try to solve for those. And that's how it becomes accountable. I have to even know what my goals are to hold it accountable to my goals. And then besides that, even having a clear business case, why am I implementing these tools? Am I trying to have better execution across functions? Am I trying to reduce my days in inventory? It's just important to know what we're even trying to solve for.

Yes, that makes a lot of sense. So would you say that have we just not figured out how to measure the impact of AI the right way yet? Is that what it boils down to?

That's hard. I mean -- and that -- let me be fair almost to AI. I used to manage strategic projects and measuring the real impact of them has always been a big issue. Like can we really define ROI of a specific project. And there's ways we all got around doing that, and there's best practice, of course. But yes, I think it's a good question you asked, like how do we even rightly assess what the AI did and what the outcome of it was.

And I just think that continues to be a part, again, if I could, sort of, belabor the point of governance, like, okay, how am I going to measure this? How do I look at it? How do I determine if it did what I wanted it to? These are just kind of the things I need to be thinking about.

Yes. No, that's really good. Yes. I think -- so if I were to summarize, right, I think it's better insights, faster recommendations, increasing that speed does not necessarily correlate to getting better results, right? And so there's an opportunity here for organizations to, I guess, close that gap between just making a decision and genuinely achieving those business outcomes and objectives, right, that move the needle.

Well, it's interesting. And here, I'll be fair to people in your role, for example. We all ask on the business side. I want to do it faster, I want to do it easier, I want to do more. And so those are specific outcomes. You just talked about, can I get to a decision quickly? I don't remember your exact words, so I don't want to put words in your mouth.

But I might measure from, oh, wow, it used to take me a week to come out of an S&OP cycle and answer an executive's question. I've literally been in those meetings and you go back and you have meetings to follow up from the meeting and you have slide presentations you're building and questioning and now the data's stale a week later. So it's certainly a value from some of these tools to get to information quickly, get to decisions quickly.

But I think there's something underneath what you just said. And again, I don't want to put words in your mouth, but just because I get to a decision quickly doesn't always mean it was quality. And so there's both sides of this. And I can imagine from your side of the world, we're not so consistent on the business side, let's say, of demanding tools that give me automation, give me speed, help maximize my resources.

But then on the other hand, am I really actually testing for, oh, was this the decision I wanted to make? Maybe it would be worth waiting a week if I took 2 days of inventory out of my supply chain, there's a real value to that. So of course, we're all going to say we want both hands. So give me tools that are fast and accurate.

Yes. So we're ambitious, right? I think that's what you're saying. And you talked a little bit ago about, I guess, the ambition a bit outpacing readiness and seeing that in some of the data. So as an organization, like, how do I decide when AI should come in and help me just recommend and give me guidance, when AI should help me act, right? And go ahead and do things autonomously.

And maybe somewhere in the middle, like when humans should take the recommendation and take some guidance, but always be approving each step, right? That's kind of the governance side of it and the gaps there. So what's your view? And maybe did the data tell you some things about, kind of, ambition versus readiness? And how do we land on deciding where to inject AI in this process?

Yes. Part of it is that governance for sure. It's -- I'll go back. If you had -- maybe there's some monetary guardrail, for example, like if I'm making a decision to purchase $1 million of product versus I'm making a decision to start a $1 billion project or something, if I was in project manufacturing. Well, that's very different.

And so there's some sort of scaling of decisions and deciding for each company and each industry, that's going to be different. So I can't necessarily be over prescriptive about that. For your company or your industry that it needs to be contemplated. Where are we okay allowing some automation? Where do we feel like we need to be involved in the decision? And that's actually just kind of a roles and responsibility discussion.

So if we kind of look at it that way, these are conversations we've had for decades in business. What are the roles and responsibilities? When does something need to escalate up the chain? When can you make a decision at your desk if you're a junior person, a middle executive, a senior executive? Now we're just making that decision with agents, in a way, having the role.

And so there's sort of a roles and responsibilities and, I don't know, size of decisions governance piece. And then I will just kind of circle back on the data quality part again that I think there's a testing or there's some kind of internal effort and an effort with partners, too, to say, am I getting the outcomes I expected? If I do -- if 9 times out of 10 the proposed something like a small PO change, let's say, okay, you're going to change the mode to airfreight on something, something like that. Or reduce this purchase order by x units.

If there starts to be a certain sort of statistical acceptance rate on some of this stuff, then if I was back in my roles leading teams that were planning around the globe, I'd say, hey, if we -- 90 times out of 100, we've accepted the recommendation, maybe we need to start thinking about automating that, too. So there's a lot of elements of roles and responsibilities and data quality that are just going to keep being in every part of this conversation, I think.

Yes, absolutely. Yes. We don't want to slow down because the opportunity is certainly there. But in all of our development and rollout, we have to make it safe. We have to make it explainable. We have to make it useful. We have to make it tied to a real operational environment. And someone said, autonomy without governance creates risk, but governed autonomy creates confidence, right? And I think that's what we're looking for, for our team.

And by the way, and forgive me for interrupting, too, but you've just reminded me something that I think is really important for anyone listening to us today. And I'll, sort of, like, come from the place of having had roles like this. I -- it's become my perspective, it's an evolving perspective, that we give humans grace and we give machines a lot of judgment. And the reason I bring that up, you just mentioned explainability, and that is very important. We need to understand why it was a decision. But I think we're starting to, kind of, embrace the notion of acceptability, too.

And let me say what I mean by that. Like, take a Tesla automated car. I literally have 2 teenagers in my house. And so we've moved to the place of their driving and it's like, okay, as a dad, you wonder, are they safe and have I trained them well and all of this. And if you look at perhaps automated driving, when we notice it making a mistake, it's headline news. On the other hand, if we looked at it statistically, it might actually be safer than my teenage drivers.

So what -- where is the level where there's some kind of acceptance, let's say, back to these PO changes. If it turns out that it can do it more accurately, then maybe I'm freed up to do higher-level thinking and rather than sort of use fear-based thinking on, well, it got this one wrong out of 1,000. I might look at that and say, actually, that's still 99.9% accuracy. Maybe I can accept that. So just sorry for kind of tangenting on that. But I think on all of this, as part of the governance, there's even a contemplation of what's our rate of acceptability or something, what's our accuracy? And if it's within these guardrails of accuracy, I'm good.

Yes. No, that makes sense. Yes. So let's dive into that, kind of, the human side of it, right? As we're evaluating and as we're -- and maybe even evaluating our changing roles, right, as this technology comes in. I think some of your survey questions leaned heavily into, like, how it's going to change individual roles and such. Did any of that surprise you? I think I saw all the way as much as 80% seeing it more opportunity than threat, right, which I think that's a good thing. Did anything surprise you about the data that you saw coming back?

Yes. And so much so that myself and some others at IDC have even kind of wondered if we need to shift some of our perspective. We've talked about, sort of, I don't know, role dis-ease and discomfort coming with AI. Am I going to lose my role in these kinds of things? We're starting to wonder if it's more like role clarity questions because to your point, we saw in this data, and we've seen in a couple other areas where the level of optimism is actually higher than I've expected. And I even think that I've experienced this myself, where I've done some projects using agentic AI, and it's actually kind of moved me into doing the higher order thinking of being a supply chain domain expert, let's say.

And there was even almost -- this sounds kind of funny to say, but there was almost a joy for me of, oh, I got out of the mundane work, and I actually really got to use my higher-level thinking. That was kind of fun. And we're seeing that in the data that people are not so much saying that I'm worried about the future as saying, oh, this is kind of interesting. I'm sort of anticipating being able to do more of the things I'd rather do.

And I don't want to sort of sound Pollyanna here. We all know there's a discussion around our roles changing, how is AI scaling? What does that mean to the workforce? And I think we have to have those conversations. But definitely, if I just take an objective view of the data, it absolutely came through that here's over 2,000 people overwhelmingly saying, like you said, it was north of 80% saying they have a positive outlook of where AI is going to take their roles and how they're going to interact with it. So I found that pretty interesting.

Yes. I think when you position it the right way, and you did a great job of that, it should build excitement about what you will be able to do in the future and how you're going to be able to leverage your skills in the best way for the organization and be recognized for that. What skills do you think are going to matter most as AI becomes more embedded in planning, decision-making, all these supply chain areas?

Yes, I'm really glad you asked that question because in my head, I was thinking, do I interrupt him again? Because I had another point I wanted to make. So perfect question. I kind of glossed over the word domain. I really think it puts a premium on specific expertise, like I'm a logistics expert or I'm a supply planning, demand planning, inventory expert. I know maybe supply chain and finance, so I can really work in S&OP. Things like this.

Because at least so far, I'm finding the ability to supercharge oneself in a way to take these tools and now bring my brain to it and kind of come up with whether it's ideas on shifting my supply chain, building a better plan. And how would you even know what outcomes to seek if you don't understand your area of supply chain? And even things like, well, we made that decision before and that didn't work out so great. Like where is the knowledge of some of these kinds of things?

So I think the combination, and that's -- here, I'm really guessing. This isn't data. Let me kind of preface this as a guess. I'm guessing a lot of the optimism comes from that place of, oh, I can bring domain expertise. These tools are going to, kind of, add horsepower. They're becoming -- I'm becoming more powerful at my job if I partner with these tools. And there's some kind of partnership outlook, I think, on these.

But so forgive me for rambling a bit, I'll come back and just -- I think your question, really, was what are the skills. I mean, can I think analytically? Can I guide tools to the tools themselves realizing a good outcome? Can I sort of input my domain expertise as I partner with these tools? I think these types of skills. And so it's like an AI skills.

But if you only had AI skills and didn't know supply chain, I think the marrying of those 2 is very important. And that, for me, comes back to that business governance of what's my organizational plan? What's my skills plan? What's my training plan? How am I going to accomplish these outcomes by preparing my organization?

Yes. Yes, absolutely. So I like that because we're kind of getting into real practical guidance here. Maybe as we wrap up the discussion, we kind of land -- we land here. We talked with a lot of different things. We've talked about how agentic systems and agents are valuable when they're grounded, right, in the business context, the supply chain context? Good, trusted data when you give it clear guardrails, when you give it defined work to do, right? So you need to surface issues and evaluate these different options, coordinate next steps, support my decision-making, that sort of thing.

And we're moving away from just, kind of, blanketly saying, okay, how do we throw this AI and automation thing at this? But we're saying, okay, where is the opportunity? Where is the outcome where I can apply AI safely and help my teams move towards outcomes that are tied to KPIs and business objectives, right? Meaningful movements of the needle, if you will.

So with all of the hype that's out there, but now some of the practical things that we've talked about, how do you think leaders should think about AI agents, automation, without getting caught up in the hype? Like how do we keep this rooted in practicality and what we can do to scale our organizations responsibly?

Yes. I think there's a piece here where unless someone really thinks you're going to build everything yourself, and that's, personally, I wouldn't recommend that, then there is kind of a step of finding the right partners, too, who are doing the type of work that you feel achieves those supply chain outcomes. And I've got certainly a biased view here. This is both in the data, but then also because of my background. That you could pursue, let's say, strictly AI type of partners, you'll get some gains there. I think there's something there, especially in terms of productivity.

But for me, what I feel like we're seeing in the data, what I hear when I speak to -- I get inquiries from different businesses around the globe. I feel like I'm hearing that there is a desire to find technical partners who understand supply chain. And I personally think that makes a ton of sense. I would be looking for that if I was a decision-maker in those spaces.

And so I think that's probably part of the next step of even understanding, okay, what exists now? What is in the road map the next couple years? How do I prepare for that? How do I prepare my organization and my budget? But also how do I have the right partners who are going to, kind of, get me there?

And I thought through all these same things we're talking about. Have they thought through data quality? Have they thought through outcome-based thinking and actually having tools that are not just helping things go fast, but are actually achieving the right outcomes? And maybe even tools that start to incorporate the guardrails that we've talked about. So I think that's a big part of just finding the right partners to kind of, I don't know, go on this journey with.

Yes. Okay. So you mentioned something really interesting there. And I think your survey data had this as well because you were asking the respondents to rank how important like the, call it, the math side of their skills, right? The optimization, the AI capabilities, these sorts of things.

But then you asked them about deep supply chain expertise, right, the domain expertise. And they were scoring like almost the same or very, very close, right? Why do you think that is? Because some people would say, you know what, hey, we're just going to go and find the technology partner that has all the tools, and we'll just build whatever we want. But it seems like folks are balancing that with deep domain expertise. And of course, we're talking about supply chain here.

Yes. I think there's been some lessons learned in the last couple years. And here, I want to be thoughtful. And so maybe I just won't name names, but there are large technology players who thought, well, we'll go over to supply chain and I don't know, like you said, bringing kind of a technical expertise.

And there were some -- I don't know if you want to call it stubbing of toes or there are some lessons learned in terms of, well, you can't just throw tools at supply chain and expect these outcomes we've talked about. And so that's even part of the guardrails is companies -- and to your point, it's an opinion of mine, but in this case, it's also in the data where these 2,000-plus folks in supply chains around the world are saying, they feel like they're finding better success when yes, we need the technical expertise, we need the tools. We all understand AI is this big wave we're riding right now. But supply chain AI specifically is what's going to solve supply chain needs.

And again, I'll just sort of own my bias there, being a supply chain guy, I even have a master's in supply chain. But I do think it makes sense that if I was finding a partner, I want someone who has, sort of, been in the weeds of supply chain and understands what it takes and understands how to solve for the outcomes I'm looking for. And understands multi-echelon inventory optimization or understands having -- I don't know, if I was a large company, having dozens or even hundreds of distribution points, even thousands.

What does it take to plan all of that and manage that well? And so I think to your point, people are saying it's a both and: I really want someone who can deliver me technical expertise and I really want someone who can come and be my partner who understands my supply chain. And that definitely has shown itself in the data.

Yes. That totally makes sense to me as a technologist because if I'm working with AI, one of the first things I have to do is if I'm going to throw a bunch of data at it, I have to give it the semantics of my data, right? I have to get it my -- the ontology and how all of these things relay. AI has to understand how my business works. So it only makes sense if I'm going to find a partner to help build some of this stuff out.

Likewise, they need to understand the complexities of supply chain. Like how my decisioning actually works, how our business workflows operate, how our people work and ultimately, what it means when I say I need these outcomes, right? They have to understand those things. Otherwise, you're going to get...

Well, I can tell you, too. Well, expertise just matters. I mean, we're back to expertise a little bit, too. Like I had an example recently where I was experimenting and building kind of a deep analysis of a company just thinking about should I even invest, for example. And it happened to be a company in an area that I'm an expert in because of my time at Nike.

And so I was challenging the AI with, well, did you think about this? Did you think about that? And it was consistently coming back to me saying, oops, you're right, I should have thought of that. And I'm sitting here going, well, okay, so clearly, you're not to the place where you have that domain expertise in this particular field. And I don't want to name the AI or part of the work, but I think it just continues to illustrate everything you just said, where if I can bring someone who can -- I think you used the word semantic. I think that made a bunch of sense to me, where there's context, I can get better analysis.

Yes, 100%. All right. So as we kind of round this out, let's assume for a moment that those that are listening and watching are just like those that responded, right? Because it seems that the respondents were all starting, but not experts, right? We're all in this place where we're trying to figure this out how to best adopt.

So based on your research and all of these responses and the trends and all this work that you've been doing, if the supply chain leader has to take one thing away from this research if they can action, what would that be in your opinion?

Boy, one thing. I think the biggest thing is just approaching these tools and your own business. And I think this is just learned business wisdom anyway with that outcome-based thinking. What are the goals I'm trying to achieve and then work right to left in a way of, okay, what's -- how am I going to, kind of, work on achieving those?

And I mean, we've talked about -- now I'm cheating and giving you multiple answers just to warn you here. But we've talked about, okay, I got to strengthen my data. I've got to think about my organization. I've got to think about, sort of, a multi-tier governance. It's procurement and spend. It's technical governance, it's business governance. I've got to think about my organization and prepare my people. And even whether it's the tools or the people, let's evaluate ourselves based on outcome and performance and all of that.

So I think it's just the tools are coming. I think I personally am very excited about what's coming. The question is, are organizations preparing themselves so that these tools can really deliver the outcomes that you're seeking?

Yes, 100%. I could not agree more, and that's not just because we're having this conversation. But when you look at Kinaxis as a software provider, we're not immune to how our business is changing based on AI. And for us, it is -- if you look historically, software companies would develop a solution that would have feature and function. We present that to a prospect and we say, look, this is what the software can do. We can do it better than anyone else, and they would adopt it.

And now we're seeing the same thing where in many cases, customers are using our software already and they're coming back and saying, hey, this is great, but we have this particular outcome, and we don't know how to get there, how can AI help us get there, right? And exactly what you're saying, it's working. I think it's working right to left, kind of working backwards from what we traditionally look at things and say, what is that goal and how do we get to that goal? And how do we use the tooling that we have, like Maestro in the case of Kinaxis, use that decisioning engine and AI to get us towards that outcome.

But I like the response, and I think it's okay to cheat a little bit. I don't know that you can pin one thing to take away. That's a little difficult, maybe unfair challenge for you. But I think the name of the game is thinking about this differently, right? You have to think about it from an end state and work your way -- kind of work your way backwards.

So this has been a really great discussion. I think that what we've learned is that AI adoption, it's happening. This isn't just hype. This isn't just hyperbole. It's happening, it's real. But just because companies are adopting, it doesn't mean they're achieving the impact and the outcomes that they want, right? And that type of AI is going to depend on all the things that we talked about: trust, data readiness, governance, human oversight and outcome-based solutioning. So I think it's about closing that gap.

So we're going to do some Q&A here. We can get that pulled up if we can. And while that's happening, a couple things that all of you watching can do. One, there is an IDC info brief called Making Supply Chain AI Accountable. That's available to everyone who has been watching. You can see that either on your screen or as a follow-up via e-mail. We'll provide that.

And then Kinaxis is also providing a companion report on how to move from AI-enabled decisions to those measurable business outcomes that we just talked about. So we've got some follow-up material that you can read that will not only help you in going on that journey, but also ways that Kinaxis can help you on that journey as well.

So all right. So let's see. We've got time. We'll try to do maybe 2 or 3 of these.

First one I have, what are the most important data readiness steps that supply chain teams should prioritize before we move into more autonomous or agent-based AI? Okay. Good question. So I'll give a perspective, Eric, and then would love to hear what you think.

I think before you can trust AI agents to make decisions, you have to make sure that, that agent can see the same truth, understands the business the same way that you do, and operates within the same guardrails that you do, right? So it's the stuff that we've talked about leading up to it.

Those 3 pieces are key to be able to trust that the agent is going to come back with the right answer. I think there's a misconception that autonomous supply chains lives in, kind of, the data quality realm. And actually, it's a decision quality problem, right? Before deploying these agents, you have to have the trusted data, the business context, you have to do something maybe you've never done before, and that's codifying some of your decision policies, like things maybe that are physically on paper or in people's brains and just how teams have been operated that needs to be codified so that an agent can follow some of those same processes.

Because it's not about -- I mean, the agents and AI can on their own kind of look back and see what's happening -- what's happened in the past. What you need is for AI to -- or to teach AI, I guess, how your business makes decisions, right, so it can follow that same path. Yes. So Eric, what are your thoughts?

I have to underline something you -- well, I actually -- I love something you just said. And so again, forgive me, but I want to underline it, actually, because I couldn't agree more.

One of the methodologies we used at Nike was lean methodology. And so most people will be familiar, whether you use, I don't know, the Toyota Way or Lean or Six Sigma, they're all kind of variations of a theme. And one of the things I found is the act of even asking yourself what are the decisions we're making, and like you said, codifying that can itself actually improve your organization's performance because you're spending time asking the why.

That's the key part is, well, why are we making that decision? How did we -- oh well, because we always did. This is the old answer, right? And so I think even for me, I would personally be excited if I was still in some of those roles to lead an organization through, hey, we need the agents to run. So they need to know what decisions they're making. But now we've got to ask ourselves, are they even the right decisions? And are we doing the right thing? That in itself is also governance because you're going to have to take the time.

And it's a bit of, I think, going all the way back to the beginning of this discussion, you said something about like it's not the glamorous work. And that's right, but it's actually the important work because then we say, what are the decisions we're making? Why are we making them? What was the goal we were trying to accomplish? And a lot of times, that brings actually improvement.

So if I was -- some of the folks sitting listening to this, thinking about your first steps, I wouldn't let that either be sort of a barrier. I would actually embrace that because what you're probably going to find is the very process of looking at all your decisions is going to actually improve the decisions you make.

Yes, that's good. All right. Okay. We got someone asking, how do we decide which decisions are appropriate for automation, which ones should stay human-led and which ones need human-in-the-loop?

That's a good question. I would say when -- you can kind of look at the cost aspect of it, right? So you can automate decisions where the cost of being wrong is low and the decision logic is well understood. Keep humans in control when the impact is high, the trade-offs are more strategic and to be thought through, and I guess when the context is more difficult to define, and it's outside of the data that agents would have access to, right? So that's great when humans are in full control.

And then human loop kind of fits in the middle, if I think of it that way, right? And I think that it will morph. I think that's a picture of where we are today with technology where it sits today. I don't know, Eric, would you have a view on that?

I would just jump off where you said morph. I think that was good. Because over time, there's -- we go back to this trust factor. A lot of what we talked about today was trust. And if over time, I'm seeing, I don't know, an agent, a tool, a bit of analytics, whatever it is, is giving me what I would call the right answer or the desired answer or whatever. Maybe even sometimes it's itself getting creative and thinking of something I missed.

Over time, I'm building trust. And a lot of these tools will kind of ask me like, hey, do you want me to proceed? And if I'm clicking yes all the time, eventually, I start to kind of say to myself, okay, this thing keeps being right. I'm good with this. Go ahead and now work quietly and just interrupt me when it's something that really bubbles up.

So I think that word morph is good. This will evolve. And so even if on day 1, okay, we spent that time thinking about all the decisions we're making that we just talked about. And now we move forward, it's still going to keep evolving. Like, oh, actually, let me pull this one back in. Let me kind of release that one. We just have to treat this as -- I mean, and that's business.

Every day, we're learning. 20 years ago before we had these tools, we would evolve. You want to keep growing and learning and shifting or -- I mentioned Lean. There's a saying in Lean: check and adjust. And so all right, let's do that. And that's going to happen with these agents where I'm going to say, I thought I was going to automate a certain process. It turns out I'd rather actually get in a room and discuss it with my peers. I didn't think I was going to automate this other thing over here and actually turned out pretty easy too. So I think we're going to have those learnings along the way, too.

Absolutely. Yes. All right. Let's do one more here. Okay. How can we prepare our teams for AI workflows without making them feel like AI is being imposed on them?

That's a good one. I had someone tell me one time, I think how you said it. The best way or the fastest way to create resistance is to deploy AI as a technology project. And the fastest way to create adoption was to roll it out as an empowerment project, right? So I like that.

And I think the message to the team, to our planning team should be clear that, look, this technology is coming in, Eric, you mentioned this earlier, is handling that repetitive work, the mundane work, the things that where your value is just clicking a mouse and dragging and dropping and exporting to Excel and doing some of this mundane stuff, so that you can focus on the high-value decisions that require judgment, creativity and your experience, right? The fact that you've been doing this for a decade, right?

That's really your value of the organization. Imagine stripping everything else off of your plate and you being able to do your high-value task all the time and really moving the needle. I mean who would walk away from that not excited and ready to adopt this new capability? That's my point of view.

Eric, I don't know, what do you think? And again, some of the data in the report, right, was highlighting that there is an excitement, right? So I think we just need to harness that and lean into that and not play into some of the fear mongering that's...

It's just incumbent on leaders in particular, whether you're a project leader or a tech leader, a business leader, there's a certain level of authenticity and honesty we have to have that I wouldn't want to promise my teams, this is about empowerment and then really end up doing something else.

And so as long as I think we're being real about it, but I do think if that is really happening on your team and you have the opportunity to be authentic and say it and not just be pitching a story, absolutely, because that's even happened to me in my own role now that there was stuff, honestly, that I kind of hated doing. Like, if you're more of a creative and a strategic person, which I am, then the mundane is painful sometimes. And so when I got to set some of that aside and do that, like I said, the higher order thinking, honestly, it's been more fun.

And so there is a path for that. I guess I'm just saying, I'll couch that in. Executives need to make sure we're not telling fairytales either. And so let's just pitch that in the honest place, but I do agree with you 100% that if this is about, hey, we're going to give you tools that sort of supercharge you, that give you horsepower.

And we have -- honestly, it's back to thinking about the organization. We've contemplated what roles perhaps look like in this, I don't know, new shape, then you have a future to tell someone about versus just like you said, here's some technology flopped on your desk now go.

Yes, absolutely. All right, folks. I think that's all we have time for today. Again, make sure you download that IDC info brief, Making Supply Chains AI Accountable. And that Kinaxis companion report is available as well: moving from AI-enabled decisions to measurable business outcomes.

Eric, great pleasure to have you on the webinar with us today. Thanks so much for joining us and all of the insights that you brought.

Yes. Thank you. It was great talking. I appreciate the opportunity.

All right. You bet. All right. Thanks, everyone, and we'll see you next time.

Very well, thank you all for joining. My name is Thanos Moschopoulos. I'm a research analyst at BMO, and we're happy to have Kinaxis here with us today. Joining us are Razat, the CEO; and Herb, who just joined the company as CFO.

Kinaxis reported strong Q2 results yesterday with accelerating SaaS revenue and ARR growth, and we'll hear from management about some of the factors that are driving that. And if anybody has any questions, feel free to submit them through the webcast portal. I'll be keeping an eye out on those throughout the discussion.

So, Razat, to kick things off for investors who are newer to Kinaxis, can you explain very briefly what your software actually does and who some of the clients are that use it?

Yes, sure, Thanos. Thank you so much. Look, we at Kinaxis, we're a supply chain planning, decisioning and orchestration platform -- software platform. And we are continuously sensing all the changes that are happening in the supply chain. We've got very smart predictive, prescriptive, agentic-driven capabilities to help companies make decisions in navigating through all those changes. And now as we're expanding our footprint, we're also getting into how do they then action those decisions and orchestrate those decisions in a way that achieves their outcomes.

So that's what we do. We play in 7 verticals with companies that have physical supply chains. So we are working with the likes of Ford Motor Company, General Motors, Qualcomm, Chanel, Merck, Unilever. So lots of large companies with complex supply chains. That's sort of our sweet spot.

And we're a company who really is -- we're very focused in getting data from the outside-in signals and across the enterprise. But really our core competency and the value we add for our customers is really oriented around making these complex trade-off decisions through scenario planning, through deep optimization, machine learning algorithms, heuristics and, of course, more and more through agentic workflows. That's really sort of our bread and butter. We're not kind of a regular SaaS company that is scaling based on the number of users or seats. It's really a planning and decisioning engine and more and more going forward an orchestration engine. That's what we do. We're headquartered in Ottawa with a very large global footprint around the world. Do you want to add to that, Herb?

Yes. I think -- thank you, Razat. The only thing I would add, Thanos, to what Razat said is I think one of the things that really drew me to the company is that what our customers use the product for is to make decisions that have very real direct measurable impact to their financial statements. So always trying to understand how much demand do I have? How am I going to supply it at what cost that has a direct impact on revenue versus margin, working capital. So these are very complex problems and importantly, problems that have very measurable ROI if you solve them the right way. And that's what excited me about what the company does and why I see tremendous value that it provides to the customers.

And to clarify, for the customers you mentioned, you're like system of record for planning, right? Not some -- not some add-on, you're like the system for supply chain planning within those...

We are -- so when any of our customers, they need to understand what is their forecast for a given product or what is their production plan for a given factory or what is their supply plan for the network. All of those are derived and calculated using our algorithmic engines, and we are the system of record for that. We're also the system of record for all the costs and constraints and all the operational details of how the supply chain functions, right? So -- and we model that in our digital model.

And to Herb's point, we are planning over $300 billion of inventory across our customer base, over 0.5 billion parts get planned. So a lot of our customers are highly dependent on our mission-critical platform for making those high-stake, big-stake decisions that lead to hundreds of millions of dollars, sometimes billions of dollars of impact for our customers.

Great. So growth has clearly been accelerating in recent quarters, and you raised your SaaS guidance yesterday. It seems like part of that is a healthy demand backdrop for what you do, just given all the macro volatility. Part of that, I think, is Kinaxis specific. Maybe let's just touch on the demand backdrop first. So with all the supply chain constraints, macro volatility and so forth, does that mean quicker sales cycles? Does that mean clients have more budgets? To what extent are they open to doing something big and transformative versus looking for like a cheap band-aid solution to address their problems?

Yes. We've seen only a small marginal reduction in our length of our sales cycle. So I'm not seeing that change a whole lot. But we're definitely seeing a sense of urgency from our customers. So Q2 was a good example of that. We saw the same thing in Q1 as well and frankly, in Q4 of last year, right, is that customers are prioritizing their investments in our platform because of all the changes that are happening in their supply and demand. And again, it's also important to understand what is causing all this volatility and uncertainty. Of course, a lot of that is regulatory and tariff and geopolitics and wars, but those are not the only factors, right? There are other factors that are driving the changes in demand and supply volatility.

Like, for example, the whole build-out of the data center value chain, right? That's impacting energy utility companies, cooling unit manufacturing companies, semiconductor companies and so on and so forth, right? We work with all of them now, right? Or for example, what's happening in the consumer manufacturing space with shifting consumer expectations and consumer buying patterns that are requiring new fulfillment models or what's happening, for example, in the pharmaceutical industry with new drugs and new introduction of new medicines. And all of these different things, as much as we'd like less change in the world, the reality is there's always more and more change happening. And as a result of that, there's more demand for the need for a platform like ours that is able to sense all those changes and then make smart decisions that are very consequential like we talked about.

I think the second reason for the demand, I think, profile is just the substance of our offering and our product offerings has expanded significantly, right? We've had an aggressive product road map. We've increased our R&D spend coming into this year significantly as well. And that's allowing us to not just land net new logos where we have much larger deal sizes that we are closing, but also it's leading to us being able to cross-sell to the existing customer base as well.

So things like all our agentic capabilities are great cross-sell opportunities for us right now. Our machine learning-based forecasting capabilities that we've introduced, advanced inventory optimization capabilities, enterprise scheduling that is using genetic algorithms, right? All of these different things are important ways for us to expand in existing customer base, but also to close larger opportunities in net new logos.

And then the third reason is we've just transformed our go-to-market engine in a very significant way in the last 18 months, as you know, Thanos, right? And that has led to us transforming our ways of generating demand, managing pipeline, executing on pursuit cycles. And we're just winning more business. Our win rates, our competitive win rates are at an all-time high. Our pipeline yield rates have been subsequently -- sequentially improving every quarter. And so I think it's a combination of these 3 things, the macro environment with all the changes happening in the world, the substance of our product offering expanding and growing and our execution in the field as well.

On the win rate to drill into that, I mean, the industry feedback I heard, including some of your partners is that your competitive position is essentially the best it's ever been. So why would you say that is -- I mean, why has this company had such a durable competitive moat over the last few years when you're competing against some larger well-funded businesses and yet your lead seems to be increasing. So why has that been the case?

Yes. A few things, right? One, the business we're in, we're solving really complex problems, right? I mean we're not solving simple problems. So you need a lot of depth of domain knowledge and understanding of the physics of the supply chain. And that domain knowledge is not just in our people or the talent we have, it's also embedded in our platform that we have, right, which is the richest representation of the physics of the supply chain and all the constraints and operational considerations and policies and interdependencies. That's a big moat for us is in being able to reflect the physics of the supply chain in our platform.

And I think the third reason is, I think, just our focus on customer success and value delivery, right? We just had a much better track record than our competitors, several of our competitors in not just selling, but really innovating with new products, selling, but also delivering value to the customers. And that's built trust over time. And that -- by the way, that trust is super important as we're getting into the agentic era.

I think my observation would be that just with the increased volatility, it's become more apparent what platforms work, what doesn't? And then maybe that's played to your strength. Would you agree with that?

That definitely works to our strength because if supply chains were just very static, nothing was changing in the demand and supply profile, it would be questionable why you would need Kinaxis. But frankly, that's not the environment that any of our customers are living in right now.

And if we just talk about, I guess, the overall market, sometimes it's surprising to see some of these logos that you're signing, they're coming to you, they didn't already have a sophisticated solution in place. When you look at the market and what proportion are still using Microsoft Excel versus having maybe a configure platform or legacy platform, how much runway and opportunity is left versus people already have a solution?

Yes, that's a good question, Thanos. Look, I mean, even when we are replacing old legacy systems for planning from other players, even there, what we find is, over time, the organization has been using spreadsheets to do their planning, right? So they may have a planning engine in theory, but in practice, where the planning is happening and all the scenario analysis is happening is in spreadsheets, right?

And so it's a journey. We've got several organizations that are surprisingly large and complex that still have been running on spreadsheets, right, where we are putting in place for the first time an integrated demand planning, supply planning, inventory planning, S&OP sort of capabilities. Those are foundational. But there are also many examples of companies that have done that, but are looking for the next wave of productivity improvements as well, right? And saying, look, we've done the basic demand supply planning. One, our systems are too rigid. And two, we want to get into the agentic era, and we want to transform our ways of working. We want to transform our ways of decision-making and governance.

So I think in those situations also, we do very well competitively, right? Because we've got a modern platform that's a single architecture, single code base, single data model. So we're not a mishmash of acquired assets with different tech stacks like a lot of our competitors are. But also in addition to that, we have really ingested Maestro -- agentic capabilities within Maestro, which is our platform. And that's becoming a bigger and bigger factor as we're competing for net new logos because that's becoming a bigger part of the evaluation process, not just to put the basic foundational planning elements in place where we have leadership position and Gartner and others have validated that, but also we can bring them on the journey to transform into the agentic era.

So they don't want to just replace a legacy system with a legacy process. They also want to future-proof their innovation because it has a big impact on their working capital efficiencies, their operating costs, their cost to serve, their service levels with their customers. So all of those reasons are important as we are winning new business.

Let's segue to AI since you raised that. So on the call yesterday, you said 10% of your clients are now using Maestro agents whether paid or trials. What are some of the initial use cases where clients are getting the most value? Give us some examples maybe in that regard.

Yes, sure. So just to back up a little bit. So as you know, earlier this year, we launched our agentic capabilities within Maestro. We had a more controlled sort of plane with 7 customers. We talked about that in Q1 of this year, right, where we were working with early adopters and we made those customers successful. And we went through a lot of learning cycles on the customer side and on our side as well. And then more recently, in the last few months, we've really opened the aperture to make it available to the broader customer base as well. And we're getting a lot of good traction, and that's what's led to roughly 10% of our customers are in trial or in paid mode.

By the way, even a lot of those trial periods are all paid. So most of those are paid customers, just to be very clear. But in terms of the use cases, look, there's a whole plethora of use cases that are emerging, but I'll give you a couple of examples, right? So one of the largest fashion companies, health and beauty companies in Europe, they've got a very volatile demand profile, right? So their consumer base is constantly making changes. They're very promotions driven, but they're also very social sentiment driven.

So if a celebrity uses their lipstick product, for example, and makes a post on social media, that can lead to a massive surge in demand, for example, right? And then they have to plan all their inventory and their supplies to service that demand as an example. So we've worked with them, and they were already using Maestro for demand planning and supply planning. And now the agentic capabilities we've enabled is really scanning the different social media feeds and is transforming what elements from the news items that are coming in are relevant that will impact or surge demand. And by the way, it's doing it not an hour a day or 8 hours a day, it's doing it in an always-on mode because the agent works 24/7, right? And then with that sort of sensing logic, it is also then defining what is the plan versus actual deviance because they have a rolling 12-, 18-month demand profile and a demand forecast.

But with these surges in demand, it's quickly assessing what is the impact of that demand. And then it is surfacing the impact of the plan versus actuals to say, here are some scenarios of how we can best service that demand because we have that scenario planning framework. So all the supply plans and the inventory is also residing in Maestro. And it's by the way doing that in an automated way. And now that is getting surfaced to the human user who can say, you know what, I know that this is going to surge demand because somebody has posted this on social media. I know what the impact is. And now here are the 3 options I have to take remedial action as a result of that. Doing all of that would be -- would take 10x the amount of time in the past and 10x the number of resources in the past, right? And now all of that can be automated through the agentic capabilities.

So that's an example on the demand side, right? There are other examples on the supply side because a lot of our customers, they're highly dependent on getting component parts or raw materials from their suppliers to do their manufacturing, their assembly, their testing, right? And so we've done some analysis where some of our customers want to have an understanding of what is the inventory on their supplier side. And what is -- what are the shippers that are coming in. And there, they're constantly scanning what is the risk profile. And in the past, they would have teams or armies of analysts doing that. Now you -- we can identify that.

Again, that agent on the supply inventory risk side is modeling the risk and then surfacing that to the human personas. And also, again, saying, based on this risk, this is the kind of production or the supply plans that are going to be impacted. And oh, by the way, it can take it all the way down to the orders that are pegged against that supply plan, right? So this customer's potential delivery date could be impacted as a result of that. Again, those are needle in the haystack kind of problems given the plethora of systems. But because we have that entire network modeled in Maestro, now these agents are able to do that in a very seamless way on an ongoing -- again, in an always on mode.

And there's a whole bunch of other scenarios. Now what we are doing is we are developing agent skills that are relevant to the planning and decisioning platform we have. But we've also embedded within Maestro an agent studio. So customers and partners and our own teams can compose the agents as well, right, on their own, and they have access to all the data and resources that resides within Maestro.

We had a hackathon just last month on this with our customers and partners. It got massively oversubscribed. We've had to schedule 3 more hackathon sessions just to accommodate the interest level. So while it's in early days, I'm super excited about -- and in many cases, our customers and even our partners are surprising us in how they're using our solutions to model and compose these agents to drive productivity, to drive better decisioning, to drive smarter risk analysis, to drive better approaches to sensing and responding to these changes that are always going on in their supply chains.

And so the reason that I would be building agents in your agent studio or using your Maestro agents versus some third-party agents is because fundamentally, you are the system of record, you have the planning engine, you understand all the interdependencies in supply chain, correct?

You're right. But just to be clear, right? So yes, we have a system of record. But more important than that, we have modeled the physics of the supply chain. So it's like, let's say you drop a Tesla car in a jungle. As with all the automated automation, that Tesla cars aren't going to go very far, right? You need pave roads, you need guardrails, you need traffic routes. And then that autonomous vehicle performs really well, right? It's the same thing in the world of agents. If you just land agents in the jungle and plethora of data that exists across these organizations, it's not going to go very far.

And so we are providing in our platform, the ability for organizations and these agents to do smart things because we have reflected the physics of the supply chain, right? And at the same time, I fully expect that customers will use the agentic capabilities we have using our platform, but also customers will use agents from other systems or their own DIY mode. But again, using our platform and the brains and the planning and decisioning engines we have in our platform. But that's the good news. And even when they do that, we have a way to monetize it given our Maestro activity unit-based pricing structure.

Maybe my last question on AI before we move on is just how do we think about the potential revenue opportunity from these Maestro agents? I mean, maybe early days, but could we be thinking about like a 10% to 20% uplift to your existing contract size? Or is it just too early to say?

Yes. Look, I think I would segment that into 3 parts, right? The first part of our agentic journey has been just in taking the LLMs, creating RAGs, retrieval-augmented generative capabilities using data and documents, building agent skills. So now customers have a conversational interface to our application. They don't have to point and click. They can do a lot of that through a natural language interface. To me, that's table stakes. And I don't expect that to generate a whole lot of incremental revenue because our customers are almost like expecting that going forward, right? So that's the first part. And we've already done that now.

The second part, which is in really packaging agents and having this agent thick studio, that's leading to all kinds of interesting productivity improvements, all kinds of interesting use cases like the ones I just mentioned earlier. Those have incremental value, right? And there, we definitely see a lot of cross-selling opportunities. And more and more in most of the large deals we are closing, we're having a bundle of activity units dedicated to agents as part of the sizing and the pricing and the licensing to our customers. And that's pretty exciting because that's incremental revenue.

But then there's going to be a third piece of this, which to me would be, frankly, the -- in my humble opinion, would be the largest revenue driver for us, which is what we're doing with our agentic orchestration platform, right, what we are building out together with our FDEs, where we're saying we are not just going to stop at the planning and decision-making, but we're going to help bridge the gap between planning and execution using this agentic framework. But in order to do that, we've got to be able to ingest data from other systems, other execution systems like sourcing systems, transportation management systems, warehouse management systems and ingesting data through those systems, mapping it into a common semantic layer and then the agents then traverse the graph that has that semantic context, right?

And so that, to me, is going to be leading to the biggest value generation for our customers because it's going to transform the way that they achieve their outcomes for getting working capital efficiencies, getting operating cost reductions, improving service levels in a very profound way and it's going to allow us to engage with them to stitch together these orchestration use cases using the different LEGO blocks we have and this agentic infrastructure that we have, right, while leveraging all the brains we have of the supply chain and while leveraging the physics of the supply chain that we've modeled. That third phase, we are just starting, right? We launched it, as you know, at Connections in early June. We've been mobilizing our FDE capacity and infrastructure. We're also working with partners to scale up the FDEs even further. We are building out this broader platform.

And by the end of this year, going into next year, we want to make sure we have some early reference customers. But those are going to be far more high value-generating larger deal opportunities than just the incremental cross-sell that we're doing right now.

So is the right way to think about it is you've got your existing planning market where you're the industry leader, you're taking share, lots of runway in demand. But now this is kind of this whole new addressable market opportunity that orchestration is going to open for you. Is that the right way to think about it?

It's a significant TAM expansion for us, Thanos, right? And we discussed this with our Customer Advisory Board, by the way, a couple of months ago, and we sort of put the rhetorical question in front of them and say, look, do we earn the right to expand into orchestration? And the resounding answer was absolutely yes because you cannot orchestrate without having the brains, which is in the planning engine, right? And so the lines given the new data architectures, given agentic AI, the lines are blurring between planning and execution and planning and orchestration.

We are still going to have multiple systems of record underpinning it, right? In supply chain, there is no one single system of record. There are multiple systems of record. But how you evolve into the systems of intelligence and system of action is what we are doing. We are one of those systems of record today for planning, right? But the opportunity we have as we expand into orchestration is to become a system of action as well. And that's a really significant TAM expansion opportunity for us.

Let's talk about the go-to-market because I think it's also been a key part of the story over the past year or 2 in terms of some of the investments and initiatives there. I mean, so you're looking at expanding the sales force. You talked about investing further in partner enablement. You're launching the FDE strategy. Maybe just give us an update in terms of what you're doing on each of those fronts?

Yes, absolutely. Look, the first thing I'll say is, again, we are in the business of solving really complex problems that generate a ton of value for our customers. So as we are expanding our field team and our go-to-market team, we're being very thoughtful about the skills and the caliber of our teams to make sure that we are able to continue engaging with our customers in a way that creates value for them and creates those long-term sustainable sort of relationships with them, right?

Our sales team has transformed significantly, I would say, in the last 18 months. And we are in the process, and that's a big reason why we are executing so well in terms of our win rates and pipeline new rates. But now we're also adding quota-carrying capacity. We're being very thoughtful about where we're doing that. We still play in 7 verticals. We think there's plenty of room for growth in those 7 verticals. We are seeing a little bit of expansion there given some of the challenges in value chains like the data center value chains. Like -- so if you asked me a few years ago, would Kinaxis play and be working with energy and utility companies, that wasn't in our top 5 list. Now those energy and utility companies have significant supply chain challenges as they're trying to service the data center build-outs as an example, right? And we'll always be evaluating incremental verticals as we go forward in the coming 3 to 5 years. But we're adding quota-carrying capacity in a thoughtful way.

Our North America go-to-market engine is really humming really well. We've got a lot of growth happening in Western Europe as well. We are pretty concentrated. We're doing a lot of things in Asia Pacific, particularly in Japan, Taiwan and India. India is really showing a lot of interest and activity and pipeline right now. We are working with some of the leaders in that market there as well. And I think in my assessment, in my early assessment, I think they'll be the faster early adopters of our agentic AI and agentic orchestration capabilities.

So look, I think we're humming on all cylinders, but a big part of what we are focusing on in the second half of this year is to thoughtfully add the right skills to expand our go-to-market reach and coverage model as we go into 2027, so we can continue to sustain the growth momentum.

And let's touch on your strategy around forward deployed engineers, FDEs. So when -- I mean, you're just starting to staff up there. When do we start seeing some of the benefits you think in terms of revenue acceleration? And just to clarify the revenue model, you're not charging billable hours, my understanding. Maybe just clarify how you monetize that?

Yes, definitely. And I'll explain that and would love for Herb to add as well on the sort of the unit economics around that, right? So firstly, why are we launching this FDE engagement model, right, and engagement motion with our customers. It's really to unlock the value potential with agentic AI, right? So our traditional planning engagement with our customers is fundamentally different from the agentic motion with the FDEs. And let me explain the difference, right?

In a traditional model, the customers come to us with a set of requirements. Here are the features and functions you need. We scope it out. We have a project plan with our partners, with ourselves. And we deliver. There's a start and there's a finish the project, there's a go-live and then we support the customer to make sure they're getting the value, right? So that's been our model for many years.

Now I'm simplifying here, but even in that model, the problems we are solving for our customers are pretty complex and very algorithmically driven in nature, right? However, customers that have done that, the phase that they are in, what we are finding is they still have some pain points, and they want to look for the next wave of productivity improvement. They want to look at the next wave of working capital efficiencies. And so they have outcomes that they want, but they don't necessarily know what exactly will be the capabilities and features and functions that will get them there, right? So we have to bring that engineering mindset, that product mindset to our customers in our customers' engagement model.

And we -- in working in a very agile iterative way with our customers, we are defining what feature sets are required to help them develop the next wave of value, right? And that's where the FDEs come in. And this engagement model has a start, of course, but there's no finish because it's an ongoing engagement model. It's like a product-oriented engagement model as opposed to a project-driven engagement model, right? And it's very driven by pain points and outcomes. And it requires a little bit of a different skill set in how you are able to -- it's like a simpler skill set to our product managers, for example, that develop our products.

So in terms of the packaging for this, the way we are doing it is this is not a services engagement. This is not a PS engagement. This is -- or the focus is around billable hours. This is really about packaging our base platform, the usage-based structure we have, which is the same activity unit-based structure we have and FDE resourcing bundled into one ongoing subscription. And again, we expect this to be multiyear subscription deals. That's the way we are packaging it.

And frankly, while we're in early days since we launched this about 1.5 months ago, we're seeing a lot of interest and traction, and we're now getting into proposal phase with the early set of customers. And we're making sure we have the right skill sets and the capacity, partly ourselves, but also partly with scaling with our partners that have similar skill sets as well. Do you want to add to that, Herb?

Yes. I think the only thing I would add, Thanos, to what Razat said, and it's a very, very important distinction because I think a lot of them -- there's a lot of confusion where people think, oh, this is like a traditional time and materials, billable hours type of model. And that's absolutely not what it is. This is really about working closely with the customer to make sure the right solution, meaning our platform, everything that we're building in the decisioning and orchestration is delivered as quickly as possible to the customer so that they realize value.

And for that reason, our expectation is that the way this will be viewed from a customer perspective is value-based, value-driven. We would expect to get those types of economics from the customers. And the way that will then get reflected in our own financial statements would be something that looks just like a traditional SaaS or subscription revenue ratable recognition.

And competitively, how differentiated is this? Is RFPs becoming table stakes? Or does this help your competitive position? Or is it more about just making the client better aware of the competitive advantages technically that you have in the platform?

Look, I think we do get a good number of RFPs, and we respond to them and we react to them. But frankly, this FDE-driven approach towards agentic orchestration, we don't expect to get a whole lot of RFPs. These are going to be us generating those opportunities in a very consultative way with our customers and really bringing them on that journey towards agentic transformation and value creation, right?

Maybe over time, there'll be more RFPs. But right now, the state of the industry is the customers don't really know exactly what are the feature sets that are needed, right? And we are helping our customers define those with this differentiated, very trust-driven, very deep expertise-driven model that generates a ton of value.

Just a couple of questions from the audience on competition that I want to address. So the questions relate to just with everything changing, orchestration now, AI, the set of competitors maybe is evolving. I mean Manhattan has talked about moving into planning. Other new players are talking about orchestration. So maybe, again, drilling into the point in terms of how the dynamic might evolve, whether -- when you go into an RFP, the set of competitors you start looking at is different than the traditional set that you focused on. And again, you're right to win when others are buying the same opportunity?

Yes. Look, I think it's a very fragmented competitive landscape is the short answer. Of course, we've got traditional competitors like SAP, Oracle, Blue Yonder, o9 and others. And we continue to see them in different evaluation cycles, and our win rates have really improved significantly in the last 12 months against those competitors. And in Q2, it was really performing really well, right? But we don't take them lightly because customers are always evaluating and there's always options they have. So we're not getting complacent with it, but definitely our track record is improving significantly there.

But you're right, I think there could be new competitors. You mentioned Manhattan. We don't see Manhattan much at all in competitive cycles. And I think partly because even though they may want to get into planning, most of their warehouse management sort of installed base is in the retail sector, and we don't play in retail. Retail is not one of the 7 verticals that we've entered yet, right? The closest thing we come to retail is quick service restaurants. So we have some customers that are doing the demand planning, inventory planning, the demand sensing on our platform. But we haven't gotten into retail full throttle yet. Again, that's something that could be a white space for us in the future.

So we don't see Manhattan much at all in our cycles. But there could be other players that -- especially as we are getting into more agentic use cases, especially as we're getting into more sort of broader orchestration use cases, I'm sure we'll see new competitors. In the past, we haven't competed against Palantir. I expect that we will in the future, right? And I welcome that because I think our approach is going to be very different in how we position ourselves versus Palantir, right?

Our starting point is not from scratch, right? Our starting point is having the physics of the supply chain represented in our digital model, having the brains of the decisioning engines that are driven by deep optimization, machine learning, heuristics capabilities for demand, supply, production inventory as part of the libraries that we have developed over the years. And now we are leveraging those starting points and the domain knowledge we have within the domain we know about, which is end-to-end operations and supply chain, to then compose these orchestration use cases using a platform and using all the state-of-the-art data architectures, semantic architectures and agentic infrastructures, right? So I expect that we'll see them more, but so far, that hasn't been the case.

So to clarify, so the vast majority of RFPs today is the usual suspect still hasn't really evolved yet at this point so much?

Yes, because the RFPs that we have are coming in more of the end-to-end planning space. The RFPs have not yet been defined and they don't even exist for the agentic orchestration use cases.

Yes. If I can -- Thanos, just to underscore that point that Razat's making. If you think about an RFP that comes out, an RFP isn't a one sentence that says, I want to improve my working capital. The typical RFP is a very, very detailed statement of we need this type of speeds, feeds, feature, functionality, et cetera., okay? And tell us why what you have already prebuilt, okay, in terms of the platform, the modules, how it fits this very detailed RFP, okay?

Everything that Razat has been talking about that the company is focused on as one of these big TAM expanders for us around the operational orchestration, this is something that is -- this is a new way of thinking about solving this set of problems. So the customers, in general, are not at a point yet where someone is writing RFPs for this. This is more of a, you show up at the customer and you have a whiteboard and you say, let's map out what your business looks like. Let's talk about what your most pressing pain points are, okay? And now we're going to show you a way to solve this that before was not possible to do. That doesn't lend itself to an RFP. I just want to reside if I'm...

Yes, that's 100% correct. That's exactly right.

It is kind of saying we're having the FDEs working with the customer to help surface some of those opportunities?

Yes.

That's why we need the FDEs. That's exactly why we need the FDEs.

Yes. So Thanos, the FDE, again, to tie it back to the -- for people that are used to thinking about the, oh, it's a services time and materials. No, this is as much about the tip of the spear in go-to-market, because it is engaging with the client to help the client articulate, surface their biggest problems that they may not have thought could be fixed, that they've struggled to fix. So they've never even bothered to think about RFP because it's so broad of a problem, right?

So traditionally, people tackle these things in silos. And in fact, the silos create even bigger problems. And this decisioning and orchestration with intelligence across the entire operations of the enterprise is now a new way of addressing this problem in a way that I would say brings together the silos together with the intelligence that we have in our competitive advantage and the intelligence of how these supply chains can actually work and what the constraints are.

And what we're finding, Thanos, is customers and prospects are very open to that dialogue. And it's partly because of all the challenges that they're facing. It's also partly because of the trust and reputation we have in this domain, right, that we've earned over a number of decades.

And lastly, it's sort of word spreads as well, right? So we're bringing deep experts that are part of this FDE team, not just generalists, right? And we have a platform that has a harness that can really leverage our existing capabilities, but also lean in and compose very rapidly to address what these orchestration needs are that our customers have in a very modern, rapid way, right? And so I'm excited about this. Hopefully, that comes across. I think we'll see some good sort of early traction at the back end of this year. And I think it's going to be a big part of our motion as we go into 2027.

And I certainly spoke to a bunch of your customers at your user conference and heard some of the excitement in terms of what more they hope to do with your agents and with the orchestration mission. So Herb, let's talk about you. So you recently joined. What's interesting is, obviously, your investment banker is a bit of a different background. And you're not only CFO, you're Chief Strategy Officer, we don't usually see that combination. What are some of the initial areas of focus and priorities on your plate?

Yes. I would say, look, it's still early, but my initial areas of focus are threefold. And it's execution, growth and strategy. And on the execution point, Kinaxis, as we've been talking about, we have a very strong business with a very compelling market opportunity. And my priority is helping ensure that we scale efficiently as we grow. So that includes looking across the entire company, looking at how we allocate resources and capital, making sure that we're consistently driving productivity and maintaining the balance between growth and profitability.

The second, as you hear the excitement that both Razat and I both have about the growth opportunity ahead of the company, we see strong demand. We've been investing, Thanos, as you pointed out, in our go-to-market, and we're bringing new capabilities to market. So a key focus for me will be working with the entire team to understand what else can we be doing to accelerate growth. So whether that's continuing to invest behind the successful go-to-market motion that we have, investing more behind partnerships, exploring new routes to market and things that we can continue to do to grow and extend the reach within the existing customers.

And then the third point, which we've been talking a lot about in strategy is one of the things that excited me about joining Kinaxis is, we have this already established leadership position in supply chain planning, but there's also this much bigger opportunity that we've been spending time on around decision-making and orchestration. So part of the role is helping make sure that we capitalize on that opportunity in a disciplined way. So to make sure we are putting enough capital behind it, but always very focused on making sure it's a thoughtful deployment of capital that it's ROI-driven, payback driven.

And it will largely focus on organic product investment and growth, organic investments behind go-to-market, including FDE because I very much think of FDE as much as go-to-market as solution, making sure that we're deepening the ecosystem of partnerships because, Thanos, something as you think about the way software companies have developed over time, people used to think the key partners were the systems integrators. And absolutely, those are important. But you follow the company, you know the company well, you know that tech partnerships are also very critical, right? So partnerships with companies like Databricks and others can be very critical to both how we innovate and the rate at which we can get our solutions into market. So those ecosystem partnerships is something that I will spend a lot of time focused on with Razat and our partnership alliances teams.

And then, of course, when it makes sense, potentially M&A. And the M&A that we could potentially see because that's a question we're getting a lot given my background is I think the best value creator for Kinaxis is very, very strong organic growth with strong sales efficiency, strong payback periods, continuing to drive operating leverage in the business, and that obviously reflects itself in the margins. So if and when there's M&A that makes sense that accelerates what's already on our organic product and technology road map to pull it forward, those are the types of things that we would be looking at.

If there are teams of highly talented engineers, data scientists, people that are expert in machine learning, can we enhance the already very strong engineering capabilities that we have at the company through those types of transactions. But I didn't join Kinaxis to do M&A that's driven by cost synergies, trying to achieve that type of multiple arbitrage. But the goal is to deliver sustainable, durable organic growth, and that's how M&A fits into the picture.

And just to add to that, Thanos, I mean, Herb and I are very aligned on this, right? And I don't think we would have been able to get Herb if it was anything different, right? Because we're not looking to become a financial engineering-driven roll-up company. That's not our business model. It's not our DNA. And frankly, it's not in the best interest of our ability to create shareholder value. We are really an innovation-driven organic growth engine. So of course, we'll be open to the build versus buy in terms of accelerating our road map and doing acquihires and tuck-ins. And thankfully, we have a balance sheet to support that. But that's not going to be the primary driver for growth and value creation. It's really going to be the organic innovation and growth that we'd be focused on.

There are a couple of questions on -- that came in on AI monetization. So to clarify, when you talk about 10% of the customers being on paid or free trials, how is that weighted towards the paid part of that? And then your comment yesterday was that most of your new contracts now or all of them, I think, have MAUs. So just talk about maybe just the ramp of usage and what you're actually getting paid for?

Yes. So on the agentic side, almost all the customers we have are paid in some way, shape or form. Even the ones where we've got the starter kits, we're doing it in a way where they have some skin in the game, so they take it more seriously on the customer side. Of course, we do some demos and boot camps and hackathons that we don't charge for. But beyond that, the starter kits are all paid. So most of those 10% are paid.

In terms of -- in terms of the MAU-based pricing structure, we -- again, we introduced that earlier this year. And we've had a very deliberate, thoughtful rollout plan that's very phased, right? So any new proposals that are going out to customers incorporate the MAU activity unit-based pricing structure. Of course, if we've already given a proposal to our customer back in October, November, December or January of this year, we're not changing those mid-cycle. We didn't want to disrupt any bookings for existing pursuit cycles. But any new proposals going out all incorporate MAUs now. And then also as it relates to our renewals starting in July, and we announced this as well, all our renewals are also with this MAU construct in place as well. So as the existing customers come up for renewal, we'll be transitioning them to the MAU pricing structure as well.

We've gone through a lot of good learning cycles in the last 5, 5.5 months since we introduced it. We've incorporated those. I think our field team is getting more and more comfortable in going through the new pricing structure. And also on the customer side, we're not the only enterprise software company that has moved in this direction. There are others as well. So I think the procurement teams of these organizations are also becoming more and more comfortable over time as well.

And there's a question in terms of just the strength in upsells we saw this quarter where 2/3 of your new ARR was from the existing base. Would you expect that kind of ratio through the balance of the year just as you're monetizing better with AI and so forth?

Yes. So it's a little misleading. Our bookings were more balanced between net new logos and existing customers. But some of our net new logos, especially the large deals, they have a phased ramp-up, right? So in year 1, they may pay us $1 million; year 2, they pay us $2 million. In year 3, they pay us $3 million, right? So when we report our ARR on a deal, we only report $1 million for that first year, right? So it's sort of -- we take the most conservative representation of that. So -- but when we look at -- when we calculate the ACV bookings and the way we incentivize our sales team, that 1 plus 2 plus 3, which is $6 million over a 3-year period, the ACV would be $2 million for that, right?

So just keep that in mind. I think bookings-wise, I think it's more in that 50-50 ratio, but the ARR representation can vary -- the split can vary from quarter-to-quarter based on how many of these ramped deals that we do. And these ramp deals typically are in large commitments that customers are making and typically multiyear, 3- to 5-year commitments that they're making with us.

Which is a key point, which is that as you look at your backlog, there is some built-in visibility to ramped growth in the coming years from the existing base that's already kind of baked into the backlog, right?

Yes, it is. And look, I mean, RPO, we've been exposing the remaining performance obligation metric as well, RPOs, and that's approaching $1 billion now, right? And that kind of gives you the size and scale of what we already have contracted and committed with our existing customer base. And so we'll make sure we continue to provide more transparency around some of these metrics, especially with Herb coming on board.

And -- but we feel really good about the long term -- our contract lengths are in that 3- to 5-year range. Even a lot of the renewals we are doing now are in that 3- to 5-year range as well, right, with built-in year-over-year price ramps. So we just become far more disciplined in our commercial structuring than in the past as well. And there's still more for us to do there. So it's not all one and done. But it's really good to see the hygiene and quality of these long-term contracts coming through.

Perfect. I think I would be remiss if I didn't ask you about the guidance because I've had some questions in the back of the quarter, where your guide for '26 implies second half acceleration. So just to be clear, is that just a function of conservatism on your part? Is there any reason to think there may be deceleration?

Yes, Thanos, I think you and the investors who follow us, you can look at the SaaS revenue in the first half of the year. You can look at the RPO number. You've heard Razat's comments about the quality of the pipeline, how we feel about that. You've seen the success that we've had on renewals. So I think the read into the guidance is that we're giving ourselves some prudent cushion and buffer given what's been happening on volatility in FX on the exchange rates, which obviously has an impact on top line as well as just the overall macro environment, so things that we don't control ourselves.

The second question, I don't know if part of it was also around guidance with respect to margins, which we've kept for the full year in the 25% to 26% range. That's also because we want to make sure that we continue to have the ability to invest behind all of this great product innovation and go-to-market opportunity given the feedback that we're getting from customers. Customers have been extremely receptive to the things that we've been developing in those dialogues. So we want to make sure that we're investing behind that appropriately given the very direct feedback that we're getting.

Great. We're about on the hour. So maybe, Razat last question I'll ask you is I think you've now been at Kinaxis for 8 months. It seems like you've accomplished a lot during that time, you've been busy. So as you think about the next 6 to 12 months at Kinaxis, what's at the top of your priority list?

Yes, it seems like a lot longer, Thanos. It's only been 7 months or so, but it seems like a lot longer. But look, it's been fantastic just to be back in the domain that I had grown up in over the years, and work with the Kinaxis team in a culture that's just so amazing. And we are so fortunate to work with world-class customers and partners at a time when there's so much innovation happening around us. So it's been really an awesome first 7 months.

As I think about the next 12 months, really 3 top priorities, I would say, right? One, I'm going to start with is continue to stay focused on delivering customer success and value, right? And this is really important. It may sound like a pedantic thing to investors. But I'll tell you, I never take that for granted, right? Because we're in the business of solving really complex problems, right? And a lot of those complex problems involve a lot of transformation for our customers. And part of the reason why you're seeing us continue to sustain the growth rates is because we have built the trust on the back of successfully delivering to those customers. And you hear it from those customers at events like Connection and you were there, Thanos, and I know several of our other investors were there as well.

And I'm saying that because also we've got examples of some of our competitors that have not focused on that and now they're hurting and they're in recovery mode, right? So that's the first -- and it's like the single most important thing that I rally the entire organization around. Every function of the company is focused around that.

The second important element is just executing on our innovation road map, right? So we are investing significantly in core Maestro in continuing to increase the scale, the volume. There's more and more scale and volume going through Maestro than it ever has with our growing customer base and the use cases our customers are using us for and in continuing to make sure that we are continuing to expand the feature set capabilities and the agentic capabilities within Maestro. But then the innovation road map also has this extension using the agentic architectures and data architectures into operational orchestration. So the innovation agenda is really important. And the way we are doing that is in a very rapid modernized way with that FDE-led model, right? So FDE for us traverses across our go-to-market sales motion all the way through our product development motion, right, and everything in between. So that's really important.

And the third thing is continuing ourselves to utilize AI tools to transform our own internal ways of working. There's opportunities for us to gain velocity and productivity in everything we do ourselves, right? We're seeing rapid adoption of coding tools in our own engineering team. So we're now in the mode of balancing between token budget versus headcount budget, right? And we're seeing significant speed enhancements and velocity improvements there.

Similarly, in every other function, like the way we are thinking about business development and go-to-market motions, we are finding amazing use cases. The way we support our customers, we've got new agentic capabilities being deployed there. So every function in the company has a road map, and that will allow us to scale better and to scale to Herb's point, in a more disciplined, but also in a more efficient way. And ultimately, all of that will lead us to be creating a better experience for our customers as well.

So those are the 3 biggest priorities for me in the next 12 months is, one, ensuring that customers are getting value and we are successfully delivering to them together with our partner ecosystem; second, executing on our innovation road maps; and third, in internally leveraging AI capabilities to increase our velocity and better efficiency with scaling up.

That's great. So we'll leave it there. Thanks, Razat. Thank you, Herb, for all that color. Thanks, everyone, for joining in.

Thank you, Thanos. Appreciate it.

Thank you.

Good morning, and welcome to the Kinaxis Inc. Fiscal Second Quarter 2026 Results Conference Call.

[Operator Instructions] I'd like to remind everyone that this call is being recorded today.

I will now turn the call over to Victoria Hyde-Dunn, Vice President of Investor Relations at Kinaxis Inc. Please go ahead.

Thank you. Good morning, and welcome to the conference call. Joining me today are Razat Gaurav, Chief Executive Officer; Herb Yeh, Chief Financial Officer and Chief Strategy Officer; and Peter Yaraskavitch, Vice President of Financial Planning and Analysis.

Before we begin, we have a couple of reminders. We will be discussing our second quarter 2026 results, which we issued after the close of markets yesterday. The earnings press release and slide presentation are available on the Investor Relations website at investors.kinaxis.com.

Some of the information discussed on this call is based on information as of today, August 6, 2026, and contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those set out in such statements. For a discussion of these risks and uncertainties, please review the forward-looking statements disclosure in the earnings press release and in our SEDAR+ filings.

Additionally, we will discuss IFRS results and non-IFRS financial measures, including adjusted EBITDA. A reconciliation between adjusted EBITDA and the corresponding IFRS results is available in our earnings press release and MD&A, both of which can be found on the Investor Relations website and on SEDAR+.

With that, it is my pleasure to turn the call over to Razat.

Thank you, Victoria, and thank you, everyone, for joining us today.

Before I begin, I'd like to welcome Herb to his first earnings call with Kinaxis. Welcome, Herb. We also recently welcomed Kristin Russel as our Chief Marketing Officer. We're excited to have Herb and Kristin onboard as we scale and build Kinaxis for the next phase of innovation and growth.

I will start today's call with my observations on the quarter, then turn it over to Peter to discuss financial results and then to Herb to review guidance, before the Q&A session -- as many of the world's largest enterprises turn to Kinaxis to manage growing demand, volatility and uncertainty.

Second, our vision for operational orchestration and our continued investments in core Maestro capabilities reinforce our commitment to innovation and to supporting the world's most complex supply chains. Third, our second quarter performance builds on the strongest first half in Kinaxis' history, and we are very pleased to raise our full year guidance for total revenue and SaaS revenue growth.

Our continued commitment to product innovation, investments in growth initiatives, and focus on customer and partner success remain our North Star. Let me discuss these topics in more detail.

Beginning with second quarter results, SaaS revenue increased by 20% year-over-year, ARR grew by 19% year-over-year, and adjusted EBITDA margin of 26% is in line with our full year guidance. Our strong performance reinforces our position as a trusted enterprise partner for the world's most complex supply chains, reflecting continued customer demand for AI-enabled planning and orchestration as organizations navigate an increasingly volatile and unpredictable operating environment.

Companies are facing multiple sources of disruption simultaneously. Trade and tariff uncertainty, geopolitical conflict, energy prices, sourcing challenges and shifting customer demand are all happening at the same time. Given this fluid operating environment, organizations need an enterprise platform that can rapidly scenario-plan and help them make better decisions across their concurrent supply chain. We saw global scenario planning activity on our platform increase every month from April through July this year, with July up 30% year-over-year. We are seeing this momentum with customers as we unlock value within a $66 billion addressable market.

It was another strong second quarter for new business in total, including business from new customers and expansions with existing customers. Our average deal size was almost double what we experienced in the second quarter last year. Once again, we continue to see strong momentum with contracts with $1 million plus in average ACV, winning 3x more than a year ago.

Our pipeline conversion rates grew very well. Our partners are sourcing new opportunities and co-selling with us, having contributed a record number of new deals in the second quarter and providing pipeline for the second half of the year. Sales to existing customers have also accelerated. We set a new company record in ACV bookings for quarterly expansion from existing customers with over 70% year-over-year growth. These customer expansions were driven by innovative new capabilities, including agentic AI, machine learning based demand forecasting, advanced inventory optimization, enterprise scheduling and other supply chain optimization use cases, all part of our Maestro platform.

We're also seeing early traction with our Maestro activity usage based pricing structure. All new proposals to customers and prospects now include MAUs. Beginning in July, select renewals started incorporating MAU pricing bundles. We've been thoughtful in our phased approach to align pricing with the value we create for our customers.

Now let me share some notable customer wins and use cases. In consumer manufacturing, Lacoste, one of the world's most iconic premium fashion and sportswear brands, selected Maestro to modernize production planning across its manufacturing operations, improving service levels, reducing lead times and increasing operational agility.

In life sciences, Gedeon Richter, one of the Central and Eastern Europe's largest pharmaceutical companies, selected Maestro to replace fragmented planning processes with a single concurrent planning platform, improving visibility, collaboration and decision-making across its global business.

Dechra, a global leader in veterinary pharmaceuticals and animal health, selected Maestro to modernize demand, supply and inventory planning as part of its SAP S/4HANA transformation, creating a unified planning platform across its global operations.

Tsumura, a leading Japanese pharmaceutical company, has become a new customer. And Ecolab is expanding their footprints with Nalco Water in Europe. In industrials, Rockwell Automation, a global leader in industrial automation and digital transformation, has become a new customer. And we have a new Fortune 500 company for the machinery sector.

We are seeing a significant uptick in needs driven by the surge in data center build-outs. Many customers across the high-tech value chain, including tooling, equipment, storage, semiconductor, power and energy companies use our Maestro solution already. Ansaldo Energia, one of Europe's leading power generation equipment manufacturers, selected Maestro to modernize end-to-end planning across its complex manufacturing operations, supporting the growing demand for energy infrastructure, in part driven by AI and data center expansion.

Turning to Kinexions North America. Our flagship conference was a great success. We had record attendance from global customers, prospects and strategic partners, and received very positive feedback on our new operational orchestration vision. This includes interoperable, composable and extensible building blocks that can supplement Maestro and enable broader operational orchestration solutions, leveraging the latest in semantic architectures and agentic AI.

Our partnership with Databricks for data fabric is live in Maestro, enabling outside-in signal ingestion and data cataloging. It ingests data from sources like social sentiment, weather and news feeds, combining it with structured enterprise data. Since our launch at the end of last year, Maestro agents have progressed from starter trials to early adopters to paid customers. Approximately 10% of our installed customer base is on a paid or trial subscription. We have a significant opportunity to bring the power of Maestro platform and AI agents to a much larger pool of customers.

While still in early days, we've seen a broad range of use cases. For example, our data integrity agent has helped identify and prioritize data quality issues. The Inventory Excess Analysis Agent compares 2 scenarios to identify the largest shifts. The Demand At Risk Analysis Agent can pinpoint late purchase orders that risk demand and revenue.

Our Forward Deployed Engineering capabilities and ongoing platform investments will unlock new opportunities for Kinaxis. Kinaxis is moving beyond just being a system of record for planning and decisioning to becoming a continuous system of intelligence, action and learning. FDEs will work directly with customers to solve complex, unique, high-value business problems on our platform.

We have a growing list of customers actively engaging with us on AI-driven supply chain transformation. We are beginning discovery with these customers to determine what the FDEs will build and the outcomes to be achieved. We expect these engagements to actively expand through the end of this year and into 2027.

Looking ahead, we are very pleased with the strong year-to-date results and momentum heading into the second half of the year. We are raising our guidance for full year total revenue and SaaS revenue growth. We are building depth, scale and performance into the foundation of planning and decision-making for Maestro, and building a composable agentic AI platform to realize our vision for operational orchestration. Importantly, we are managing the business for long-term, durable growth and profitability.

As we shared at Kinexions, we are focused on 5 key strategic initiatives to drive long-term growth. First, continue investing in core Maestro platform. Second, building an agentic framework for operational orchestration. Third, executing on our new FDE customer engagement motion. Fourth, doubling down on training and enablement of our growing partner ecosystem. Lastly, and most importantly, continuing to stay focused on customer success and delivering value.

We believe AI is making our core strengths more valuable, not less. As the market shifts from experimentation to adoption, customers need trusted intelligence, explainable decisions and measurable outcomes. That's exactly where Kinaxis is investing and where we are seeing growing demand from customers and continued business momentum.

As I wrap up, thank you to my Kinaxis colleagues, our customers, partners and shareholders for your support. Let me turn the call over to Peter.

Thank you, Razat. Let me start with our second quarter 2026 results compared to the prior year. Unless otherwise noted, all figures reported are in U.S. dollars under IFRS.

Starting with revenue, total revenue was $158.8 million, up 16%, driven by strong SaaS revenue and professional services revenue. Foreign exchange rates negatively impacted total revenue by approximately $900,000.

SaaS revenue was $106.5 million, up approximately 20%. This represents 67% of total revenue, up from 65% a year ago. Growth was driven by momentum from new customers, strong net expansion among existing customers and healthy retention rates. Foreign exchange rates negatively impacted SaaS revenue by approximately $600,000.

Subscription term license revenue was $5.7 million, up 13% and above expectations. This was driven by several expansion deals with existing on-premise customers. For the full year, we now expect subscription term license revenue to increase 85% year-over-year, with the bulk of the remaining revenue recognized in the fourth quarter. This represents an improvement over our previous year-over-year revenue growth estimate of 60%.

Professional services revenue was $42.1 million, up approximately 12% and ahead of expectations. This is due to higher-than-expected realized rates, reflecting our premium services.

Given our outperformance in the first half of the year, we now expect mid-single-digit annual growth for the full year, an increase from our prior low single-digit estimate. Additionally, as a direct result of our strategy to shift more implementation and support work to our systems integrator partners, we now expect lower professional services revenue in the second half of the year compared to the first half. This remains a positive development for Kinaxis as our services partners are an important go-to-market channel and services are an attractive business for those partners.

Maintenance and support revenue was $4.4 million, down 20%, as expected, due to on-premise to SaaS migrations. As we noted last quarter, we continue to see interest among on-premise customers looking to migrate to our SaaS offerings. These migrations provide us with the opportunity to modernize our customers and grow our SaaS business. Since migrations are driven by timing and customer schedules, we now expect maintenance and support revenue to trend slightly lower in the second half of the year.

Turning to remaining performance obligations. SaaS and total RPO balances and growth both remained robust. SaaS RPO was $940.3 million, up 19%, and total RPO grew to $983.4 million, up 18%, highlighting the strength and visibility of our recurring business. Over the last 3 years, SaaS RPO has a cumulative average growth rate of 20% and total RPO has a CAGR of 19%.

Next, annual recurring revenue increased to $465.6 million, up 19%. ARR grew 21% year-over-year on a constant currency basis, excluding a negative impact of approximately $1 million from FX in the quarter. As Razat mentioned, ongoing strength in our $1 million-plus ACV contracts and net expansion with existing customers drove net new ARR growth of $75 million year-over-year and $19 million sequentially. Most of the customer growth came from enterprise or large enterprise customers, reflecting our upmarket focus.

Now I'd like to move on to our second quarter profitability metrics. Gross profit grew 19% to $104.4 million. We delivered a gross margin of 66%, up 1.6 percentage points. This was driven by higher professional services margin and a more favorable revenue mix as professional services as a percentage of total revenue declined. Our subscription software margin was 78%, down from 80% a year ago. This change is partially due to increased hosting costs as we migrate from private data centers to the cloud.

A quick update on this. We're exiting our private European data center by the end of 2026. Meanwhile, our North American data center migrations are underway and expected to be completed by the end of 2027. Once completed, Kinaxis will be able to realize the full benefits of cloud infrastructure.

Professional services gross margin was 32%, up significantly compared to 23% a year ago, reflecting higher realized rates in the quarter. Operating expenses were consistent with expectations.

Adjusted EBITDA was up 23% to $41.4 million, reflecting strong revenue growth, healthy gross margins and efficient operations. Adjusted EBITDA margin was 26%, up 1.3 percentage points, positioning us well to deliver on our full year outlook. Profit was up 15% to $21.2 million, with an effective tax rate of 28.8% for the quarter.

During the last -- during the second quarter, we repurchased over 450,000 shares for approximately $47 million. Since the program started last November, through the end of the second quarter, we've repurchased 1.2 million shares for approximately $134 million. This reduced the total outstanding share count on a net basis by 2.9%. We will remain opportunistic in share repurchases for the remainder of the year.

We ended the second quarter in a strong cash position. Cash flow from operating activities was $30.7 million, up 36%. Cash, cash equivalents and short-term investments were $310.7 million, down from $324.7 million at the end of last year, even with $108 million from share repurchases.

Free cash flow margin for the second quarter was 18%, up 3.8 percentage points year-over-year. Trailing 12-month free cash flow margin was 25%. The combination of higher revenue and reduced share count led to diluted earnings per share of $0.76, up 19% year-over-year.

That sums up the Q2 review. For full year modeling purposes, I would like to provide some additional details. First, we expect foreign exchange rates to remain a headwind for the rest of the year given the strengthening of the U.S. dollar against the euro, the British pound and the yen. For the full year, we estimate increased FX-related headwinds to total revenue between $4 million and $4.5 million, and to SaaS revenue between $2.5 million and $3 million.

Second, we expect full year basic weighted average shares outstanding to be approximately 27.3 million shares and diluted weighted average shares outstanding to be approximately 27.7 million shares. These share forecasts do not include the impact of any share repurchases that we may pursue in the future.

Now let me turn the call over to Herb.

Thank you, Peter, and thank you, Razat. As a new member of the Kinaxis team, I'm delighted to be here today. Before I address our guidance, I'd like to share why I joined Kinaxis.

Supply chain planning and decision-making is one of the most complex and mission-critical challenges facing global enterprises. Kinaxis has already built a market-leading platform, deep domain expertise, a strong culture and an exceptional team with a proven ability to create value for both customers and shareholders.

But what excites me the most is the opportunity ahead. AI has the potential to expand the scope of what we do, moving beyond planning into a much broader set of decisioning and orchestration opportunities. That expands the value we can deliver to customers, increases our market opportunity and strengthens our ability to drive sustained long-term growth and shareholder returns.

Now turning to guidance. As you heard from Razat and Peter, we delivered better-than-expected top line results in the first and second quarter. With this in mind, guidance for the full year ending December 31, 2026 is as follows.

We now expect total revenue to be in the range of $625 million to $640 million. This represents approximately 14% to 17% year-over-year growth. We now expect SaaS revenue year-over-year growth to be in the range of 18% to 20%. This equates to a range of approximately $427 million to $434 million. We're reaffirming our previously issued adjusted EBITDA margin guidance of 25% to 26%.

With respect to our balance sheet, we will remain disciplined in capital allocation. We'll maintain a prudent cash and liquidity position to fund day-to-day operations and to navigate any macroeconomic or industry volatility. We will also make thoughtful, ROI-driven investments in product innovation and go-to-market initiatives that support strong organic growth while maintaining strong sales efficiency and attractive payback metrics.

Any inorganic activity will remain tightly aligned with our product, technology and go-to-market road maps, delivering clear and actionable revenue synergies. Finally, we will opportunistically return excess capital to shareholders through share repurchases.

I expect 2026 to be a pivotal year for Kinaxis, and I'm thrilled at the opportunity to be a part of the journey. Thank you to our global team for delivering another strong quarter. I look forward to meeting with analysts and shareholders in the weeks to come.

Operator, we're now ready to take questions.

[Operator Instructions] Your first question, from the line of Thanos Moschopoulos with BMO Capital Markets.

Congrats on the strong quarter, and Herb, congrats on your new role at Kinaxis. Razat, can you provide some color on the nature of the pipeline and how it's evolved over the past quarter? It sounds like you're seeing broad-based strength across a number of verticals, but just anything in particular you'd call out in terms of pipeline composition and how that's evolved?

And then secondly, just given the accelerating growth you're seeing, could implementation capacity become a potential bottleneck at some point? Or do you see sufficient capacity in the partner ecosystem to handle further acceleration?

Yes, Thanos. Yes, our pipeline continues to trend very positively as we look ahead in the future quarters. We look at the 4 rolling quarter pipeline very frequently. We're executing on several campaigns to continue to add to the pipeline. What we're finding is that customers are definitely seeing a sense of urgency in their prioritization for supply chain planning, decisioning investments. We are seeing a significant surge in demand across the high-tech value chain just given what's happening with -- particularly with the data center build-out.

We're also seeing increasing interest in the aerospace and defense industry that is seeing surging demand with fairly limited capacity and a very complex bill of materials. We're also seeing changing dynamics in the product portfolios of our consumer products and consumer manufacturing customers as well. So really, we're seeing increasing demand in a lot of different industry verticals, and we're executing on those campaigns.

In terms of your question around the implementation capacity, look, this is something that's really important for us. And coming into this year, just to remind everyone, we doubled down on our investments in training and enablement, right? And that was all geared towards further building out the trained and the skilled talent pool across our platform across our partner ecosystem.

That is a very strategic priority for us, and we're continuing to do that. Of course, in addition to that, we have our own professional services team that supplements what our partners do for us. And we're continuing to scale the overall partner ecosystem with talented and skilled resources across the Kinaxis platform.

Your next question, from the line of Kevin Krishnaratne with Scotiabank.

Congrats on a strong quarter. This is Richard on for Kevin. Just had a quick question on Maestro agents. So you noted that it's installed in 10% of the customer base. So how do you see that evolving over the next several quarters and year-end? And do you have any targets on that?

Yes. Look, Maestro agents are getting a lot of good traction within our customer base, both through trials and paid customers now. And we have a sort of a dual approach there. We've embedded Maestro agents within our platform, within the Maestro platform itself. And there, we have developed agent skills that are packaged agents that now are getting good usage.

In addition to that, we've got Maestro Agent Studio, which provides a composable approach to really being able to compose agents based on different use cases that our customers have, while it has access to all the data and resources across Maestro. So that's really leading to all kinds of permutations and combinations of use cases. And as our engagement model with our customers grows around agents, we are seeing all kinds of creative agents being designed and developed and composed within Maestro.

Now beyond Maestro, we've also been investing in our orchestration platform where we have an extensible data fabric, we have an extensible semantic and ontology layer. And we have the same composable agent infrastructure that can stitch together agents across different outcome threads or outcome flows. And that's also going to lead to further transformation in the ways of working for our customers and create even further value.

So while it's early days for us, we are definitely seeing a lot of interest and a lot of traction. Of course, this forms a very important part of our innovation road map as well.

Your next question, from the line of Paul Treiber with RBC Capital Markets.

Just a question for Herb. Just given your background, your strategic advisory background, how do you see yourself, your skill set contributing uniquely to what Kinaxis has had in the past?

Yes, Paul. It's a great question. The way I would think about it is this. I will partner certainly very closely and, obviously, with the entire management team, Razat, product, go-to-market to identify what are the areas of potential inorganic activity that could accelerate what is already a part of the plan, the strategy of the company, and then to tie it together with the financial outcomes and to shareholder value.

So I think of it all in the context of my comments around capital allocation. The company has already year-to-date returned more than the free cash flow that they generated in the first half of the year. We'll continue to evaluate what we do with the balance sheet cash, all with the lens towards value creation and sustainable growth. Does that help?

Yes, it does.

Your next question, from the line of Mike Stevens with National Bank Capital Markets.

This is Mike on for Doug Taylor. Congrats on a very strong quarter here. Just wondering on the EBITDA margin guide, the back half does imply a bit of a step down. Just wondering the drivers behind that. Is that kind of continuing investment in R&D? Is that a bit of a conservatism here? Or just any color around that?

Yes. I think there are 2 things. One is if you look at the first quarter, EBITDA margins were obviously higher than, I'll call "normal" because we did have a strong STL revenue recognition in that quarter, okay?

The second thing is given the very strong go-to-market momentum that we have as well as the receptivity from our customers on what we are doing with agents in Maestro, as well as the operational orchestration platform that Razat spoke about earlier, we want to continue to capture that momentum and that opportunity and make sure that we are investing behind that appropriately to capture the market opportunity and the sustainable growth opportunity. So for that reason, we're maintaining the EBITDA margin guidance for the full year.

Okay. No, that's pretty helpful. And then just another one around the enterprise. It seems like ARR is being lifted quite noticeably by the enterprise motion in the last couple of quarters. Just wondering any early learnings on that with regards to sales cycles and what the strength is reflecting and whether you think that this could be sustainable in the quarters ahead?

Yes. Look, our enterprise motion continues to gain a lot of momentum and ground. As you know, we've been significantly transforming our go-to-market motion, our sales organization, our demand gen plans and how we're executing on those, both in terms of sales cycles, but also in terms of delivering successfully to customers.

One of the things that was very noticeable in Q2 was the tremendous traction we had with existing customers. As we've added additional capabilities to our platform, our cross-selling motion and our expansion opportunity is becoming very prominent, and that's very encouraging. At the same time, in terms of net new logo wins, we are continuing to see opportunities both with customers that are looking to put foundational end-to-end planning and decisioning capabilities in place, but also future-proofing their transformation with a platform that can really bring them into the agentic era, right?

And that's where the capabilities we've developed, our strong, single, unified Maestro platform, combined with all the agentic capabilities and the operational orchestration footprint that we are leaning in with, is becoming a very strong differentiator. So our win rates were very high in Q2 and the first half. Our pipeline conversion rates are higher than ever before. And we're not stopping at that. We're just starting and I expect that we'll continue to improve and execute globally.

Your next question, from the line of Stephanie Price with CIBC.

It's Sam Schmidt on for Stephanie Price. Can you talk through puts and takes to the increased revenue guide as well as your confidence and visibility into the back half? More specifically, the SaaS growth in the first half was strong versus the guide. How should we think about SaaS growth in half 2?

Yes. So if you look at the SaaS growth that was delivered in the first half, you're obviously also aware of the RPO that is available for the back half of the year. What the guidance reflects is that, as well as our lens into renewals as well as the strong backlog and pipeline that we have expected to be realized in the second half of the year. So we feel very, very good about renewals and current pipeline and backlog.

What the guide reflects, however, is we think it's prudent to keep in mind FX volatility as well as the overall macro volatility that we're all experiencing through the full year. So that's the reason for the SaaS guide.

With respect to the full year, Peter mentioned our expectation around services. Services will be slightly down from the first half of the year. But we're not expecting anything major changes in terms of our subscription term license that's been realized in the first half. And we're not expecting any meaningful change in terms of the maintenance and support revenue either. So when you take all of that together, that's how we thought about the total revenue guide for the full year.

That's helpful. And then one more for me on the partnership strategy. How should we think about partnerships with companies like Databricks and NVIDIA contributing to growth as well as growth from traditional SI partners? And then I'll pass the line.

Yes. We've got some important technology partnerships, definitely with Databricks and NVIDIA, but also with Google. In all 3 of those cases, we -- a lot of our partnership is anchored around doing joint research, engineering and product development. Our engineering team is working with NVIDIA's, Google's and Databricks' engineering team very closely because we are embedding those capabilities into our Maestro and operational orchestration platform. So that's really exciting.

We do see an opportunity for us to improve on furthering these partnerships in terms of the joint go-to-market motion, and that's something we're going to be working on later this year going into 2027 as well.

Your next question, from the line of Lachlan Brown with Rothschild & Co Redburn.

Herb, congrats on the CFO position. On your Forward Deployed Engineers, what early success are these teams having with accelerating those trial to paid conversion rates for Maestro agents? And just looking ahead, how should we think about the FDE utilization rate and the net impact on gross margins as you continue to scale that team into 2027?

Yes, Lachlan. Look, we launched the FDE motion at our Kinexions event in early June this year. And as we had announced earlier, we hired Manik Sharma, who has a significant amount of experience in our domain and through his experience at Palantir and Celonis in really executing and mobilizing an FDE motion.

What we've been busy with is really organizing FDE pods in North America, Europe and in India. And we've been hiring the right skill sets to really populate the capacity we have for FDEs. And in parallel, we started engaging with a lot of customers. When we launched this at Kinexions in early June, we saw -- we received a lot of customer interest.

Because in many situations, our customers are looking for the next wave of productivity and efficiency. And in a lot of cases, they have pain points and they have outcome aspirations, but they don't necessarily know, a lot of our customers don't know exactly what features and functions and capabilities they need. And that's where the FDE motion is very critical for us, is engaging with these customers and co-building with them what the features and function capabilities are, leveraging our Maestro platform, leveraging our operational orchestration, extensible platform, and utilizing agents where appropriate.

And so we are now engaging with several customers globally. We have interest from customers across North America, Europe and in India, especially. And later this year, we'll also be taking it to other parts of Asia Pacific. So I'm very encouraged with the customer reception and engagement. And definitely, like we said, in the back half of this year and going into 2027, we see ourselves really executing very well towards this motion.

In terms of the impact on gross margin, I'll let Herb comment on that.

Great. Thank you, Razat. So just to clarify or reiterate, first, there is not baked into our 2026 guidance and expectation any impact from the new FDE motion, okay? As Razat mentioned, we expect these engagements to actively expand through the end of this year and into 2027.

We're working very closely with our customers. We're reviewing the accounting treatment. But we expect that revenue generated from the FDE motion will be mostly recognized ratably. And then the second point around margin is that we're aiming to have the gross margins typical of SaaS for this bundled solution offering.

Your next question, from the line of John Shao with TD Cowen.

I also have one related to FDE. At your conference, I believe, Razat, you said the current FDE team is relatively small across 3 pods. So could you maybe talk about the kind of trajectory of headcount addition? And how long does it take to fully ramp up those new hires?

Yes. So since the conference in early June, we've been ramping up the internal team. And very pleased to say that we've added resources across North America, Europe and India. In addition to that, we've started discussions, we also received a lot of interest from our partner ecosystem. So our strategy is to definitely have an in-house capacity for FDE execution, but we'll be scaling this up by leveraging well-defined and well-identified partners that have the right skills for co-building.

And just to remind you of the skills needed for the FDEs, it's a combination of process and solution architects with supply chain domain knowledge, data engineers and data scientists. Because a lot of our use cases underpin algorithmic capabilities from deep optimization, machine learning and generative AI. And so our strategy is to have our internal in-house team, but also scale aggressively with very targeted and focused partners as well.

Your next question, from the line of Mark Schappel with Loop Capital Markets.

Nice job on the quarter. A couple of questions around your AI agents. First, in terms of the agents, is the entire sales team selling your AI agents today or is it just a select part of the sales team?

And then secondly, nearly every major supply chain planning vendor is now offering AI agents around their platforms. So I was wondering if you could just talk a little bit more about how you differentiate your agents from those of, say, your competitors.

Yes, sure. So look, the first question, definitely, our entire sales team is incentivized to take these agent capabilities to market, both with existing customers and with net new logos, right? So there's no special, separate quota-carrying sales team. Of course, we've got experts who are business consultants and FDE engineers who play a very important role in these sales pursuit cycles to make sure that the customers are able to get a detailed understanding of our agentic capabilities as part of their evaluation processes.

And I'm really happy to say that even in Q2, some of the largest wins we had, had a bundle of agents as part of the deal structure, right? And they were very important parts of the criteria in them selecting Kinaxis. So that's on the first question.

On the second question, in terms of our differentiators, there's 3 things I would say, right? Firstly, for agents within Maestro, I mean, again, we have natively developed the agentic infrastructure by building agent skills, building the Maestro Agent Studio to have access to all the data and resources within Maestro with a semantic and ontology context.

So we are uniquely positioned to leverage all the power of Maestro in terms of access to data because we have a system of record for planning, as well as leveraging all the architectural differentiation we have within Maestro with versioning that leads to world-class scenario planning and concurrency representation, and our agents are able to leverage all of those capabilities. That's the first part.

The second part is these agents in many use cases are leveraging decisioning algorithms, right, which are also part of the planning engines and the models we have within Maestro, right? So think of decisions that are made across demand predictions, supply plans, production plans, inventory. All of those leverage algorithmic -- decisioning algorithms that we have to enable those decisions, again, that are part of Maestro that get instantiated through agentic capabilities.

And then the last thing I would say that's differentiated for us is just our deep understanding of the physics of the supply chain that we reflect in our underlying end-to-end supply chain network model. So understanding all the constraints, all the policies, all the interdependencies of the end-to-end supply chain that the agents then can really be able to traverse to make meaningful, intelligent decisions, but also sensible and executable decisions, and operationalizing those decisions as well in a way that can really function in the operational environment of our customers. Hopefully, that helps you with the understanding.

Your next question, from the line of Suthan Sukumar with Stifel.

This is Essey speaking on behalf of Suthan. Just a question on AI adoption. The 10% adoption rate is very encouraging. And so my question is on new deals, what has the AI attach rate been? And what changed with regards to [ the AI requirements in your development conversations ]?

Yes. It was a little difficult to hear you, but I think your question was related to AI adoption and the attach rates in new deals with AI capabilities. I think that's what your question was. So look, let me first start by saying everyone has a different definition of what AI means, right? And I've always held the belief that we've been AI-native from our very inception, right?

So we've been leveraging predictive and prescriptive AI from the very start here at Kinaxis in enabling all kinds of planning and decisioning use cases. Those AI capabilities were enabled by advanced machine learning models, deep optimization algorithms, heuristics algorithms. So those are 100% of everything we do. So all deals include those capabilities.

More recently, of course, we've been adding the generative and agentic capabilities to our AI roster. And I'll tell you, almost every major net new logo that we are signing is involving some bundle of agents because we are seeing growing interest in customers not just trying to deploy a legacy planning approach, but to really modernize their ways of working. And in doing so, they're leveraging agents.

And in many cases, some of the net new logos that we are winning, we're replacing old legacy solutions from many years ago. And so it's really encouraging from my perspective to see the adoption happening, and the attach rates are really growing in terms of our agentic capabilities as part of all net new deals.

Your next question, from the line of Martin Toner with ATB Cormark.

My only question is around the AI supply chain. Is it meaningful within your pipeline? You mentioned that in the prepared remarks.

Yes. Look, again it depends on what you mean by AI. It's sort of -- it's interesting because a lot of our agents are really responding to sort of audacious sort of elements of the supply chain that are complex, that are needle-in-the-haystack kind of problems. And in unraveling those decisions, we've been using AI from the very inception, right?

I think if your question is more around agentic capabilities, our pipeline for agents is growing, both within our existing customers as well as net new logos. Like I mentioned, the attach rate on the net new logos is really growing very rapidly, and almost every customer is evaluating those capabilities if they're a net new logo for us.

And then also, as we are getting the FDE motion mobilized and really helping our customers realize the outcomes, and helping our customers extend beyond planning and decisioning into broader orchestration use cases, we can only do those with a strong leverage of AI, right? So AI is very core to our capability and is, frankly, a big reason why you're seeing the continued momentum and acceleration in our growth path.

There are no further questions at this time. I will now turn the call back to CEO, Razat Gaurav, for closing remarks.

Thank you for the questions. We reported a strong second quarter and feel great about our trajectory for the second half of the year. Thank you to our employees, customers, partners and shareholders.

Have a great rest of the day. Thank you so much.

This concludes today's call. Thank you for attending. You may now disconnect.

Good morning, and welcome to the Kinaxis Inc. Fiscal 2026 First Quarter Results Conference Call. [Operator Instructions] I'd like to remind everyone that this call is being recorded today, Thursday, May 7, 2026.

I'll now turn the call over to Rick Wadsworth, Vice President of Investor Relations at Kinaxis Inc. Please go ahead, Mr. Wadsworth.

Thanks, operator. Good morning, and welcome to the Kinaxis earnings call. Today, we will be discussing our first quarter results, which we issued after close of markets yesterday. With me on the call are Razat Gaurav, our Chief Executive Officer; and Blaine Fitzgerald, our Chief Financial Officer.

Some of the information discussed on this call is based on information as of today, May 7, 2026, and contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those set out in such statements. For a discussion of these risks and uncertainties, you should review the forward-looking statements disclosure in the earnings press release as well in our SEDAR+ filings.

During this call, we will discuss IFRS results and non-IFRS financial measures, including adjusted EBITDA. A reconciliation between adjusted EBITDA and the corresponding IFRS result is available in our earnings press release and MD&A, both of which can be found on the Investor Relations section of our website, kinaxis.com and on SEDAR+.

The webcast is live and being recorded for playback purposes. An archive of the webcast will be made available on the Investor Relations section of our website. Neither this call nor the webcast may be rerecorded or otherwise reproduced or distributed without prior written permission from Kinaxis. We have a presentation to accompany today's call, which can be downloaded from the Investor Relations homepage of our website. We will let you know when to change slides.

Finally, I want to remind you that our user event, Kinexions, will take place from June 1 to June 3 in Las Vegas. All sessions on the second and third are open to investors. You can review event details at kinexions.com. And if you're interested in joining us, please reach out to me directly at [email protected] before registering as we have capacity limitations.

Over to you, Razat.

Thanks, Rick, and good morning all. Turning to Slide 4. I'm extremely pleased with how the team performed in the first quarter. Momentum from our last year has continued with a record Q1 performance. Our great start to the year is evidenced by performance in our 2 key growth metrics. Our SaaS revenue grew by 21%, a significant jump compared to 16% growth a year ago. This provides us with a tremendous start towards our SaaS growth guidance for the year. Our ARR balance grew by 20%, accelerating from 14% growth in Q1 2025.

All this growth translated to significantly improved profitability in the first quarter. We achieved record quarterly profit and adjusted EBITDA, and our adjusted EBITDA margin was 32%. Blaine will speak to details soon.

Our momentum as the leader in AI-driven supply chain planning and orchestration continues to accelerate in an environment that is characterized by the following: firstly, there's heightened levels of volatility in supply and demand with ongoing levels of geopolitical and structural shifts; secondly, significant push to create new levels of productivity and working capital efficiencies while improving customer fulfillment service levels; and thirdly, a growing phase of innovation and change in underlying data architectures and agentic AI in an effort to create new levels of intelligence, efficiencies and automation.

Customers are exploring new forms of intelligent decision-making, governance, operating models and process automation, leveraging a mix of predictive, prescriptive, generative and agentic AI. Their feedback gives us confidence that Kinaxis is on the right side of an exciting opportunity to transform the ways of working across the entire supply chain and deliver unprecedented levels of value to our customers. The opportunity ahead is significant, and the latest innovations in data architectures and AI are providing us a tremendous tailwind.

Turning to Slide 5. It was a record Q1 for new business in total, business from new customers and from expansions with existing customers. Almost double the amount of total new business we signed in Q1 2025 and won 60% more than in any previous Q1, measured by average annual contract value. Our average deal size was over double what we experienced in the first quarter last year. Once again, we saw a disproportionate strength from contracts with 1 million plus in average ACV, winning several more than we did a year ago, including our largest initial customer contract ever, both by annual and total contract value. We'll provide you with specifics on the number of $1-plus million deals annually but our early success. And pipeline suggests that 2026 could be another strong year in this regard.

On to Slide 6. Just under half of the new ARR we added in Q1 came from some exciting new customers, most of which were enterprise or large enterprise class. I'll highlight a few wins. In consumer products, we were thrilled to win Pernod Ricard, the world's leader in premium international champagnes and spirits. They have over 200 iconic brands, including ABSOLUT, Beefeater, Chivas Regal, G.H. Mumm, Glenlivet, Havana Club and Jameson. Pernod Ricard is going to be deploying our Maestro platform for end-to-end planning across their global supply chain network in an effort to improve service levels and gain cost efficiencies.

In our chemicals vertical, Tesa has become a customer. Tesa develops over 7,000 innovative adhesive solutions and is active in 100 countries. Tesa is looking to leverage Maestro to help shift from regional silos to a centrally governed global supply chain model to support rapid growth, new product launches and other strategic initiatives.

We have continued our amazing run in the energy sector. Last quarter, we won Marathon Petroleum, and now we've added the largest renewable energy company in North America. The company uses a diverse mix of energy sources, including natural gas, nuclear, renewable energy and battery storage. Their expansive asset base requires better end-to-end processes to ensure the right parts are in the right place at the right time.

They're also looking to improve demand forecasting using outside-in data and machine learning techniques so they can quickly respond to new opportunities. The energy sector is undergoing massive investments to support the demands of the new AI economy and the surge in the build-out of data centers. So we expect this to remain a strong sector for us ahead.

In life sciences, we won a large vital organ therapy company, which for 70 years has driven meaningful innovations in kidney care. They're going to be deploying Maestro for end-to-end intelligent planning capabilities. We also won a couple of mid-market life sciences companies, ALK, an allergy treatment specialist headquartered in Denmark; and Laboratoires Théa, which researches, develops, manufactures and commercializes a wide variety of eye care products.

In industrial manufacturing, we won a significant contract with a global Fortune 500 company. This well-known leader is known to -- is looking to replace siloed business unit decision-making with our unified platform covering S&OP, demand planning, distribution, inventory, shop floor scheduling and more. They're also going to be deploying Maestro Agents to gain intelligence, productivity and automation.

In the mid-market tier of high tech, there are electronics [ manufacturer ] of Weidmüller exist. There are still dozen prospects in our vertical market, and we have never positioned to win. Along with success made in Q1, I think a lot of our addition came from existing customers. So the new application with the largest single expansion business and distribution [Technical Difficulty] expansion with all-time optimization and forecasting, with most of the expansions in the first quarter. The success is demonstrated via mathematics, namely algorithmics and machine learning models remain at the very heart of customer needs for powering high-impact supply chain decisions.

Our exciting new generative and agentic AI capabilities make it easier and more effective to leverage these advanced capabilities, but will not [Technical Difficulty]. Working together, all these technologies provide us with an incredible opportunity to further expand our impact into broader supply chain orchestration use cases. We have over 400 customers, a growing set of capabilities to sell a highly focused go-to-market team. So there are -- there's a massive room for expansion within the existing installed base.

On to Slide 7. While winning business with the world's biggest and best supply chains is the best validation we can receive, it is a tremendous honor to be ranked as a leader in Gartner's Magic Quadrant for the 12th consecutive time. And in such a prestigious spot. Gartner published 2 Magic Quadrants this time around, one for discrete industries and another for process industries. It is a testament to the powerful flexibility of Maestro that we placed so well in both. The reports support our long-held view that differentiation in our business is not about stand-alone planning features. It's about how well platforms enable fast, connected and automated decisions across the supply chain.

With respect to AI, the report shows that most vendors in our space leverage it, but with varying impact. The real value is seen as coming when AI is embedded directly into decision flows and execution rather than fragmented or assistive approaches. We see ourselves positioned well here. Maestro is infused with AI end-to-end and is the world's most sophisticated context and digital representation of the physics of the real-world supply chain. It enables rapid scenario planning, synchronized decision-making and continuous and concurrence planning.

Moving to Slide 8. As you will recall, we've already launched Maestro Agents, including out-of-the-box capabilities and Maestro Agent Studio, which gives supply chain teams a no-code way to compose AI Agents tailored to their unique needs. Our agents, which embed large language models, including OpenAI's ChatGPT, Google Gemini and Anthropic's Claude in training and in testing, make it easier for users of any skill level to access the full power of Maestro. They also enable automation of processes that would otherwise be impossible, difficult or inefficient for human users to undertake and create a practical foundation for more autonomous supply chain operations that deliver faster, better decisions with even greater confidence.

In Q1, we more than doubled the number of paying customers for our Maestro Agents, and we are in discussions with many more. The application of AI and agentic AI in supply chain planning, decision-making and orchestration is moving very rapidly, and there's no shortage of ideas for how to use it. One way we've been able to support customers in helping them prioritize specific high-impact use cases, we know will deliver value quickly. For example, we recently offered customers packages for up to 6 agents where deployment and knowledge transfer are supported by our forward-deployed engineers with full implementation done in as few as 4 to 8 weeks. The package includes predefined agents that target some critical decisions, ensuring data integrity, anticipating demand and supply risk, improving forecast accuracy, evaluating demand shifts and optimizing inventory and supply outcomes.

We also have launched our Maestro Agent Studio to enable composability of agents tailored to our customers' unique needs. Our start-up package, combined with forward-deployed engineers, aims to kick-start that process and quickly demonstrate value by absorbing real plan of work, standardizing analysis, creating automations and accelerating decisions. Our world-class customers move carefully and thoughtfully and they undeniably move forward. I'm certainly biased, but it's difficult to imagine any customer not using our AI agents in the coming years.

As I've described before, the next steps in our AI journey are to add the following: orchestrator agents that coordinate and sequence multiple agents across concurrent supply chain workflows; secure connections and interoperability between Maestro Agents and external agents and systems; and expanded data context and semantics through an extensible ontology layer that enables composable agents to reason consistently across larger data sets and analytical environments beyond Maestro for true supply chain orchestration. Initial versions of these initiatives will be available within 2026 and will open a much larger opportunity for Kinaxis. Stay tuned for additional announcements on this front at our Kinexions event in early June in Las Vegas.

Lastly, with respect to internal use of AI, we continue to prioritize this usage for improved efficiency, better results and increased velocity. I'll provide some examples. In R&D, we found that AI-assisted work is 25% faster on average. And over 90% of requests to move code into production now include some AI-assisted elements. Our business development team has dramatically improved efficiency and conversion by using AI for deep research on prospect accounts that could benefit most from Maestro. AI identifies the use cases, finds the right contacts, writes e-mails and follows up, all referencing the specific prospect context.

Our professional services team is using AI to increase our assurance that partner deployments are following all the rigorous standards that get quicker answers to the field to unique deployment challenges. We will continue to emphasize the use of AI for innovative ways to improve operations company-wide and transform our internal ways of working.

The search for a new CFO is going very well, and we have been working with the top-tier executive search firm to engage with over 200 potential candidates. At this time, we're in our final stretch of decision-making with a very short list of candidates. As it was when I joined Kinaxis, most of these candidates will need some transition time from their current roles. We will provide formal feedback when the process is complete. Meanwhile, Blaine is leaving us with a high functioning finance team to allow for a seamless transition. As I said on the last call, I can't thank Blaine enough for successfully steering Kinaxis through great growth opportunity and change and to leave us in such a tremendous shape today.

Over to you, Blaine.

Thank you, Razat. I couldn't be more excited than to complete my time here with such a stellar quarter. Like recent periods, Q1 was beyond expectations in several key areas and establishes even greater confidence in meeting or beating our 2026 targets.

If you look at Slide 9, turning to the numbers and compare to Q1 2025 results, total revenue was $165.6 million, up 25%, largely driven by very strong SaaS revenue growth and higher-than-expected subscription term license and professional services revenue. SaaS revenue was $102.9 million, up 21%, thanks to recent strong momentum winning new business, including record levels in Q4 2025 and our strongest Q1 ever. Subscription term license revenue was $19.1 million, up 111%. The result was a couple of million dollars higher than expected as a new customer joined us under the hybrid model. Under that model, we deliver Maestro from a hosted environment, but the customer has an option to move the deployment on-premise, which triggers term license accounting. You should adjust your annual term license estimates accordingly.

Professional services revenue was $38.7 million, up 16% and stronger than expected due to higher realized rates as we work to ensure that pricing fully reflects our premium services. We continue to successfully shift services work to systems integrator partners, and we'll continue to focus on that in 2026. The strong first quarter result doesn't currently change our view that professional services revenue will grow in low single digits for the full year.

Maintenance and support revenue was $4.9 million, down 11% due to some contract changes, including success moving a couple of large customers from a hybrid hosted model to SaaS. We mentioned in last call that there is ongoing interest in such transitions. As a result, we now expect maintenance and support revenue to decrease slightly and consecutively in the remaining quarters this year.

Our gross profit was up by 32% to $114 million for a 69% gross margin, up from 65% due to a higher software margin, higher professional services margin and a more favorable revenue mix as professional services declined as a percentage of total revenue. Our software margin was 81%, up from 80%, largely due to higher subscription term license revenue. Professional services gross margin was 27% compared to 21%, reflecting the higher realized rates in the quarter as mentioned.

Adjusted EBITDA was up 62% to $53.6 million, beating our record from last quarter and reflecting strong revenue growth, higher gross margin and efficient operations. Adjusted EBITDA margin was 32%, up from 25%, which sets us up well for our full year target. It's important to note that the positive impact from high-margin subscription term license revenue decreases substantially in future quarters this year.

Our profit in the quarter was a record $29.4 million, higher than any previous quarter and compared to $15.9 million in the first quarter last year. We are very proud of that result.

Cash flow from operating activities was $59.1 million, up 87%. Cash, cash equivalents and short-term investments were $327.6 million, up from $324.7 million at the end of last year despite $62 million deployed under our share buyback program this quarter.

Moving to Slide 10. Our trailing 12-month free cash flow margin was extremely strong at 24%. Given timing variations in individual quarters, we believe focusing on the trailing 12-month figure is most suitable. If you look at Slide 10, it illustrates our significant progress over the past 3 years. That said, it's worth highlighting that free cash flow margin in Q1 was an incredible 35%. Our organic cash generation muscle is now very well developed.

Turning to Slide 11. Annual recurring revenue grew 20% compared to the first quarter of 2025 and now sits at $447 million. We added $14 million to our ARR balance during the first quarter. This is a record for our Q1, even as our conservative approach to measuring ARR left significant committed future amounts out of the calculation. And despite foreign exchange movements in the period, reducing the balance by $2.6 million. As Razat mentioned, ongoing strength in million dollar-plus ACV contracts helped drive this great result. We also continue to convert very well on opening pipeline in the quarter, and our gross dollar retention remains very strong.

On Slide 12, SaaS and total RPO balances and growth remain very robust, with SaaS RPO at $905 million and total RPO at $949 million, highlighting the strength and visibility in our business. The balance remains slightly below $1 billion as Q1 is typically a low renewal quarter, which limits RPO growth. Over the last 3 years, SaaS RPO has a cumulative average growth rate of 20% and total RPO has a CAGR of 19%. We look at 3-year growth rates to help normalize for the impact of normal customer renewal cycles.

On Slide 13, despite total revenue, SaaS revenue and adjusted EBITDA results coming in ahead of our expectations, we are maintaining all aspects of annual guidance, which we provided only 60 days ago. The political, economic and foreign exchange environments remain extremely volatile. So we feel that the approach is prudent. It is still early in the year, and we will gather more information and review our guidance assumptions next quarter. In any case, we exit the first quarter even more confident that we will achieve or beat our goals for 2026.

Slide 14, we maximized our normal course issuer bid shortly after our last quarterly call, doubling the repurchase limit to approximately 2.8 million shares or 10% of our float at October 31, 2025. During the first quarter, we repurchased 570,204 shares for an investment of approximately $62 million. We see tremendous value in being aggressive on our share buyback program, while public markets continue to misvalue complex AI-enabled enterprise SaaS companies like ours.

As I said last call, Kinaxis' business has never been in better shape over my 6 years here. It's hard to imagine that our quarterly revenue is now approaching Kinaxis' full year revenue in the year before I joined. It's been a privilege to be part of that growth.

ARR and SaaS growth are accelerating. RPO is closing in on $1 billion, and profitability is up and has a higher ceiling in the years ahead. Kinaxis is only at the beginning of its AI journey, which I'm confident will add even more opportunities for growth.

I want to thank again the whole Kinaxis team, which is truly PFA, and all of you, our investors and analysts. I hope to see you again down the road. I will now turn the line over to the operator to start the Q&A session.

[Operator Instructions] Your first line comes from Kevin Krishnaratne.

A couple of questions on Maestro. I think, Razat, you said something about how the release is allowing your customers to do things that were really complex, sometimes impossible. So can you talk about maybe the pricing here? And how are customers thinking about the ROI on their side? Are they maybe hiring fewer demand planners? Or are they just going faster on plans?

Yes. I think it's part of an adoption journey, Kevin. And so really, right now, what we're finding is a lot of the focus with our customer base is in gaining efficiencies, productivity, but also on driving working capital efficiencies and cost efficiencies and service level improvements in their supply chain. That's the bigger value proposition in the near term. Clearly, in the midterm, there's going to be opportunities to further consolidate and scale to a much larger extent with fewer headcount and planners, but that doesn't seem to be the initial focus for our customer base.

Got you. And it certainly seems like a big opportunity, some education and handholding on your side. You talked about the FTEs. I'm just curious to how do you work with your partners and SIs to make sure that you're getting this technology properly deployed and scaled over time?

Yes. Look, we've done a few things there. Firstly, we have almost doubled our investments in training enablement for our partner ecosystem. That's a really important initiative for us this year and that's really well on track, and we're going to continue to see us make a lot of investments. That's the first part.

Second, we're working with fewer set of partner organizations, but we are going deeper in the skill development, the talent development with them. And then thirdly, when partners do lead implementations, which we are perfectly fine with, we are insisting that we have a level of engagement to ensure that we are reviewing the solution design, we are reviewing the integration architecture, we're reviewing some of the testing and things like that before they go live. And we have a package now we call that the Guardian package that we are insisting that every customer uses when they are selecting partners. And that's something that is becoming -- getting a lot of ground. And all the mature partners we have, they like our level of engagement in the implementations, even though they take the bulk of the implementation work, they like to have Kinaxis experts involved in it to make sure we are doing it properly and we're mitigating any risks going forward and ensuring the right outcomes for our customers.

Your next question comes from the line of Richard Tse at National Bank Capital Markets.

Blaine, I just wanted to say it's been a pleasure working with you and all the best with your new opportunity here. If I kind of look at the growth here, it's obviously accelerated quite a bit this year versus last year. How would you attribute that growth to sort of just an improving sort of macro for supply chain? Or is it specific more to Kinaxis and what you've done on the execution side? I'm just trying to kind of gauge where that incremental is coming from.

Yes, it's a good question. I think it's a combination of factors. Clearly, there are some structural shifts that are happening geopolitically, from a tariff perspective, just overarching demand-supply volatility that provide us some good tailwind. It builds the need and the case for the Maestro platform. So that's definitely a factor. But I think beyond that, there are, I think, 3 other factors as well.

Firstly, we're seeing a significant push for replacement cycle of old legacy supply chain planning deployments where customers are fed up of those old legacy deployments, and they're looking for a more modern solution that is usable and is on a single platform and there's really purpose-built for taking them to the agentic era, right? So there's a significant push for a replacement cycle that is underway. And at the end of last year and in Q1 this year and as well as in our pipeline, we are seeing continued increase of those replacement opportunities. So that's an important factor.

The second one I'll tell you is I think beyond just the macro tailwinds, we're seeing that the Chief Supply Chain Officers are under more and more pressure from their CFOs and their CEOs and their Boards to create the next big wave of efficiencies in terms of working capital efficiencies because supply chains account for a very large percentage of the balance sheet and inventories that they carry account for a very large part of the working capital. And also in certain industries where logistics costs are a big part of the percentage of cost of goods sold and with the increase in the fuel prices, there's a lot of pressure for reducing the cost basis as well. So all of these factors are also creating a bigger need for our platform.

And then the third thing I would say is I think we -- our execution has improved dramatically. And we've really rehauled our overall go-to-market engine. We've added capacity and we're going to continue adding capacity through the course of this year in terms of quota coverage. And we're just winning more business, including competitive business, and we're expanding within existing accounts as well.

Okay. And I just have one other quick one in terms of the expanding business. Of the wins today, like how many would you say are being kind of influenced by the fact that you've got a pretty progressive road map for AI, particularly with sort of Maestro Agents? Like is that kind of part of the decision-making you think in terms of what you're doing there? Or is it still a bit early for that?

Yes, it's a good question. I'll tell you, in all -- I mean, obviously, with our existing customers, we are very actively engaged with them and they're coming on the adoption journey with us. But in net new accounts where there are evaluations happening, the underlying platform capabilities for agentic AI, the underlying capabilities for being able to have composability for agents and the out-of-the-box agents we have is playing a bigger and bigger role in the evaluation process. And every pursuit cycle that we're engaging involves demos of these newer capabilities. And there's a growing trend where they become part of the solution set that our customers are buying even in net new logos. So it's becoming a bigger and bigger factor, I would say, in net new accounts.

Your next question comes from the line of Stephen Machielsen at BMO Capital Markets.

Blaine, it's been great working with you over these years. I want to dig into the spending environment. So on one hand, you've got global volatility in oil prices, supply chains, underscoring the need for your software. But on the other hand, enterprises will often delay decisions during these kinds of periods of uncertainty. What's the dynamic you're seeing with your prospects today? And how might that vary across the different verticals and geographies?

Yes, there's definitely some differences by industry verticals and geographies there. There are some verticals like the high-tech value chain or the energy sector that is feeding into the surge in the build-out of the AI data centers where those needs are very, very urgent and they're not waiting for the macroeconomic uncertainty to sort of settle itself. They're really moving ahead with those investments. There are other industries like aerospace and defense, where we're seeing similar trends.

And then in industries where there are more chronic disruptions and sort of inflationary cost pressures, our solution and what we at Kinaxis and what Maestro [Technical Difficulty] builds a bigger business case for our sponsors and our champions in these organizations to get additional funding to move ahead with these initiatives, right? So we're frankly not seeing any delays or inertia in decision-making.

Now I would call out that to be the case, especially in North America. Our North America business had a fantastic Q4. They've had a fantastic Q1, and the pipeline has tremendous momentum for us in North America. Slightly different dynamic in Europe. Europe, we are seeing -- we had a very strong Q4 in Europe. And we are seeing good pipeline momentum there, but the pace of decision-making doesn't seem to have the same sense of urgency as in North America. And then in Asia Pacific, it's a different dynamic based on which country you're talking about between Japan, Taiwan and India, which is where we operate. In India, we're seeing a lot of deal flow and a lot of momentum in organizations that are looking to scale up and looking to become more competitive, continue to invest in our solutions. And so it varies by industry and vertical. In general, we have not seen the slowdown with any of the macro issues. In fact, if anything, it's been a little bit of a tailwind.

Okay. That's some really helpful color. So I know you've been calling out some of your larger deals, especially this quarter. Did you say that you signed your largest initial deal ever?

That's correct, both in terms of ACV, average annual contract value and in terms of total contract value, that's right.

All right. I'm going to go in a different direction. I just was wondering if you could comment on how you're ramping up your reseller channel? Like how has the progress been there? I guess, going to the smaller deal size?

Yes. That's an important area for us because, of course, we are adding direct quota-carrying capacity in our go-to-market engine. But resellers play a really important role, particularly in segments of the market where we don't have our own direct coverage. So that includes many countries and regions around the world as well as certain segments of the market that are more down market. So we have a pretty good, robust global reseller program. We are actively evaluating and recruiting and developing partner relationships where appropriate with them. We do want to make -- continue making investments in training and enabling them and making them more proficient.

And then we also have an offering, a sort of a rapid quick start offering where it's still our Maestro platform, but we've really simplified the template and usage for it because a lot of these resellers are selling to customers that are at a different phase of maturity as organizations, and they want something that can be implemented very quickly, have lower total cost of ownership and can lead to more rapid time to value. And so a combination of the product packaging as well as the training enablement and then our global reseller program is important. We had a pretty good year last year with this program. This year, we're looking to continue that growth momentum with the reseller program as well.

Your next question comes from the line of Lachlan Brown at Rothschild & Co Redburn.

Blaine, wishing you all the best on your next opportunity. You added $5.7 million of SaaS revenue in the first quarter, which I believe was your last quarter of SaaS revenue dollars added sequentially. And I believe this did come ahead of your initial expectations. So could you just run us through the core drivers behind this? Was it on pricing, cross-selling, commencement of large new contracts or anything else to call out within that number?

Yes, great question. So we had a pretty healthy balance of new name accounts as well as expansion that obviously contribute to that. It was almost like 50-50 for where we ended up. At the end of the day, it comes down to like execution of that go-to-market team that is doing extremely well. They're converting at a very, very high clip to a point where when Razat joined, he said I've never seen conversion at this. These are levels that are extremely high, which we're obviously very, very proud on.

Obviously, the strength of Q4 really helped us out and put us in a great position. So it was just compounding at this stage. A great Q4 and then a great Q1 is helping us hit those high numbers. It's a situation where CFO is pretty exhilarating to be in a position where you get to go out and have these amazing numbers that you get to brag about. And we gave our guidance in a, I think, fairly prudent way. I'd say we are very, very, very confident, more confident probably than we've ever been before that we're going to at least hit those numbers. And I hope that my successor is going to be very happy with me giving them a reward to be in a position to potentially give you some, I guess, increases in those guidance in the future. But we've been in a very fortunate position to have some great execution on the go-to-market side.

The other piece I would just kind of end with is like you asked a question about expansion and AI, and an earlier question came from that. And we called out ADF and agentic AI, both of those products are our fastest-growing products right now, and there's a lot of high demand. So we're in a fortunate position that what we've been innovating for has led to where we're at right now. And maybe one of the unsung kind of metrics that usually a CFO wouldn't want to brag about right now is just the R&D increase. We are investing for the future right now. The innovation that we're doing is what's getting us the wins against all of our competitors and the future competitors because they're seeing that we're investing in our product and making this product top right of any Gartner MQ that's out there. So we're in a great, great position.

And the comment on agents ties nicely into my next question. So with the new paying customers on Maestro Agents, how has their usage been? Has that come in above, below expectations? And has this changed your thinking around how you're bundling MAU usage within subscription?

Yes. No, we're really happy with the traction we're getting with the early adopters of our Maestro Agents. It's been a lot of fun. And actually, they'll be presenting and discussing some of those early wins at our Kinexions event. And it's always exhilarating to hear our planners who our users talk really about how they can do things in minutes or seconds, what would take them hours or days. So I think that's really on a really good, strong trajectory. Of course, as we are landing new customers with our agentic capabilities, we want to make sure we're also working with our partners and our forward-deployed engineers to make sure we can think through the outcomes and the use cases and get them the value. So that continues to be a really, really important focus area for us.

In terms of the MAU pricing, as you know, we launched that last quarter in Q1. And all new proposals going out to customers and to prospects involve that Maestro activity unit structure, which is a consumption and value and outcome-based pricing structure. We've continued to get good feedback from customers and prospects. And we're continuing to refine the details and the minutia details of the metrics. But all the telemetry is in our platform as well, both for ourselves as well as for our customers to track it.

And then just to remind you later this year, in July this year, all renewals we're going to be doing with our customers is also going to involve the MAU pricing structure. So it's just -- it's a great sort of trajectory for us to tie the movement and the emphasis we have around our AI-oriented use cases and road map and the agentic capabilities with this MAU-based pricing structure.

Your next question comes from the line of Paul Treiber at RBC Capital Markets.

Just in terms of -- you mentioned pricing, you also mentioned that you're seeing larger deal sizes. The -- could you dig into further on the deal sizes, that reflect more so momentum of larger customers? Or are you also seeing an increase in the economics per customer? And then with the changes in your pricing structure with AI and other aspects of your road map, how do you think about the average economics per customer going forward?

Yes. Look, I think -- well, firstly, it's a very good question. And what I'll say is between sort of winning business with large organizations,and sort of the deal sizes, what I'll say is that both are important factors, right? I mean, I think we are selling to large enterprise organizations that was a big contributor of our bookings in Q1. Some of the large wins were with some of the largest companies in the world. But also, I think the scope of the capabilities we are taking to market has broadened, right, as we've innovated and brought new capabilities to market.

Blaine talked about ADF, which is our machine learning-based forecasting capabilities that is using outside-in data and using sophisticated machine learning techniques that we feature engineer for improving our customers' approaches to how they think about demand of the organization or another capability that we introduced, which is our enterprise scheduling capabilities, right, which is using sophisticated scheduling, genetic algorithms and optimization capabilities to bring efficiencies to the shop floor of these manufacturing organizations and bring an integrated approach to supply planning with production scheduling.

All these expansion capabilities, and of course, now we have these agentic capabilities that we are also adding on to our footprint. So all of these capabilities are adding -- are creating fantastic opportunities for us to both cross-sell to existing customers, but also when we land net new logos, they're becoming a broader footprint. And a lot of times, customers are working with us because we were able to bring that end-to-end solution with a platform that understands the complexity and the physics of the supply chain, and then we are adding these intelligent algorithms, these intelligent agents on top of them to really be able to create the next wave of value. So it's, I think, a combination of larger organizations, but also a broader set of capabilities.

That's helpful, and great to hear. The second question, just on -- there's obviously a lot of interest for customers to use AI to develop more software internally. Based on the feedback that you've seen or heard from customers, where are they delineating between software for supply chain or within the enterprise that they're looking to build themselves versus what they would use a partner like Kinaxis to provide?

Yes. Look, this is a good question. And I think most of our customers are still calibrating where they work with Kinaxis versus where they do in-house development. What I can tell you is, as we are making investments in our underlying platform, we are providing capabilities more and more where customers can both use out-of-the-box capabilities that we embed in our products and our capabilities, but also we are able to provide extensibility and composability in the underlying platform we have. So when there are unique capabilities that our customers need or use cases where we need to extend what we are able to do, we are being able to facilitate that in a very supportable, maintainable and sustainable way, right?

And going forward, I think the ability of our platform to provide for that composability and provide for all the extensibility will allow both our customers and our partners to develop capabilities on our platform. And -- but when they develop capabilities on the platform, it's not to write custom applications or custom solutions like in the traditional or legacy approach to it. It's really going to be allowing them to compose solutions, compose agents, compose micro apps while taking into account all the different pieces of the LEGO blocks that are part of our platform.

And so that's an important trend that we're seeing. Supply chains, the extended supply chains deal with the minutiae of operational details. There's a lot of variance in the needs by industry, by vertical, by geography, by country, by operational function. And so being able to have a platform that is flexible, extensible and composable gives them that ability to leverage all the knowledge we've been able to accumulate over the years and all the reflections we have of -- the digital representation of that physical supply chain and the intelligent library of algorithms we have together with our semantic and ontology layer to really be able to compose applications when needed as well. So our vision is to not only play in out-of-the-box packaged applications, but to also play a growing role in organizations that do want to innovate and in the DIY space as well.

Your next question comes from the line of Stephanie Price at CIBC.

Hoping you could talk a little bit about where you are in the partnership strategy. How should we think about partnerships with companies like Databricks and NVIDIA contributing to growth? And also, how do you think about growth with the traditional SI partners here?

Yes. It's a good question. So look, I mean, obviously, we've been working with our SI partners for several years, and we're going to continue working with them. They are playing a bigger and bigger role as we scale up the business. And like as I mentioned earlier in the call, we're really doubling down and investing in the training and enablement and ensuring that we still have an active involvement in those implementations through the Guardian package that we now have with these SI partners.

In terms of the rest of the ecosystem, beyond the SIs, there's some important ecosystems that we are becoming a part of in a more and more active and strategic way. Of course, we work with 2 hyperscalers, Google and Azure. And we're actively working with them. You'll be hearing some announcements coming up at Kinexions along these lines and some of the more innovative work we're doing with some of these hyperscalers.

In addition to the hyperscalers, Google and Azure, we're also working actively with NVIDIA. We had made that announcement in our partnership to innovate our optimization engines and our MIP solvers using NVIDIA's cuOpt, which is an innovative capability that they've just launched recently and it runs on their GPUs. And we're getting deeper and deeper into that NVIDIA ecosystem.

And then with Databricks, that's an important relationship because we're building out our extensible data fabric. That's a relationship we entered last year. We are continuing to leverage their machine learning pipelines as we enable capabilities for forecasting and machine learning-based forecasting for our customers. So that component that we are OEM-ing from Databricks is also very important. But I envision that the ecosystems like NVIDIA and Google and Azure will become more and more important for us.

And then there's another element, which is we have -- we OEM and we leverage the LLMs as well, right? So OpenAI, Google Gemini as well as Anthropic Claude. So there's different ecosystems emerging. We want to, of course, play appropriately in those ecosystems. With the hyperscalers, with the SIs and in some situations with some of these other folks, we are engaging and partnering in certain accounts as we engage with customers, as we engage with prospects as well. And you're going to see us continue to double down and focus on developing these ecosystem relationships even further going forward.

Maybe for my next question. Obviously, Kinaxis has been doing well in multiple areas and definitely results this quarter were very good. Is there anything worrying you, Razat, as you now have kind of been in the seat for the few months here? And how are you thinking about the business and the evolving landscape here?

Well, I worry about everything. But look, it's -- the business clearly has a lot of momentum right now. And -- but we're not being complacent about it, right? If I look at it with all the new wins and the growth we have, we have to stay anchored and focused on ensuring our customers are getting value. We are doing that with a lot of investments we've made in our delivery organization, in our customer success organization,and with our partner ecosystem, right? So I mean, we only retain the right to continue growing as long as we can keep making our customers successful and ensuring that they're getting value from our solutions. That's a really important focus for us.

Of course, beyond that, we are accelerating our innovation cycles. We've increased our investments significantly in R&D, as Blaine mentioned earlier. And the investments in R&D are not from the point of -- or a vantage point that there's a great white shark that is coming to eat us. It's really to really focus on the fundamentals of what are the needs of our customers, what are they trying to achieve and then map that to all the new and exciting technologies, whether they are new data architectures or new generative and agentic AI capabilities, how can we marry those together to create the next wave of value for them.

And so that's a very big focus area is our innovation road map, and you're seeing us continue to innovate so we can leverage our fantastic core we have, which is Maestro and the end-to-end planning capabilities and that representation of the concurrent supply chain, but also extend beyond that with an extended platform to get into agentic orchestration across the end-to-end supply chain, right? And that's where we are investing in the data fabric and the semantic and ontology layer and the knowledge graph and the agentic studio.

So a lot of things to get done, but all exciting. And all of that only happens as long as we can retain and attract the best talent and our people, right? The company has a fantastic culture. We are not taking that for granted. We're making sure that we continue to retain the innovation culture, the collaboration culture, the product-centric and customer-centric culture, but we also need to make sure we attract the right talent as we aspire to bigger dreams and bigger goals. So those are the things that I'm working on is making sure we continue delivering on customers, making sure we continue to execute on our innovation road map and continue to make sure we retain and attract the best talent possible.

[Operator Instructions] Your next question comes from the line of John Shao at TD Cowen.

I just want to ask about token costs, which seems a concern for some software investors. I know your pricing model is hybrid and consumption based. But could you still remind us the guardrails you have there to make sure it's not going to be a gross margin headwind?

Yes, that's a great question. And we've heard in a lot of different companies having to worry that tokenized costs and the change in tokenized costs will elevate the amount of cost of goods sold as you go forward. We're in -- I think just like everyone else, we're still in early days. We're not seeing that impact at this stage. It will be something we'll have to figure out. And at the same time, we're having some almost tokenized pricing that we are bringing to our customers. So we're trying to offset that cost with our own pricing strategy as we go forward. But it's still too early to determine how that's going to play out.

Just like any other new change, we expect that there's going to be a price elevation in the short term, and then it will start to work its way out and be a little bit more efficient as we go forward. But today, it doesn't have any impact on any of our numbers, including in our short-term forecast.

Yes. And just to add a little bit to that, right? So I mean, tokens come into play on 2 fronts. One on the internal usage of AI and code assist and other LLM capabilities. And there, now we are allocating a token budget to all our engineering teams and we have seen situations where some of the most productive engineers are blowing through that. And actually, frankly, we're celebrating that to some extent because the numbers are not something we can't manage within our budgetary guidelines and our forecasts. But what we're seeing in terms of outcomes, in terms of velocity and productivity improvements and speed is just fantastic. So that's on the internal side.

With our customers, we have put in place a telemetry like I mentioned. So the MAU construct factors in tokens, like Blaine said, and we monitor that telemetry. Our customers can monitor that telemetry. And when customers reach at the top end of that, we do engage our commercial teams to engage with the customers to see if they need to top up on that, right? So we are well protected from that regard. Of course, we're also watching closely what are the pricing trends for unit costs from LLM providers. Obviously, we've been beneficiaries of those unit costs coming down in the last 2 years pretty dramatically, but we are watching that pretty closely as we go forward.

Your next question comes from the line of Mark Schappel at Loop Capital.

Razat, there's been considerable recent discussion about kind of the software power center kind of shifting from traditional applications to these orchestration layers. That seems to be a trend that you guys are embracing. I was wondering if you could just elaborate maybe on how real that shift is you're seeing? And then also maybe just elaborate on your orchestration capabilities.

Yes. Look, I think the underlying data architectures are shifting. And I'll talk about ourselves a little bit. The key sort of capability we have, orchestration is -- it means different things to different people. For us, really, what it means is to leverage our underlying platform and our sort of understanding of the physics of the supply chain and to really help our customers plan, make decisions, take actions and to really be able to achieve the outcomes and then to go through the learning cycles as they go through that. That's the orchestration loop as we think of it, right? So planning, decision-making, actioning, execution, achieving the outcomes and the results and then going through the learning cycles.

And I think what's most important and, frankly, the big effort to achieve this vision is not so much on the underlying technical architectures or the product capabilities or the agentic capabilities. It's more importantly in working with organizations on how they need to rethink their ways of working. And these organizations are Fortune 1000 companies that we're working in, in the 7 verticals we work in, right? And it requires -- I mean, there are some use cases that can have a quick hit with creating productivity and automation and repetitive tasks and things. Those are the low-hanging fruit and easy things to facilitate through agentic workflows.

But to really truly get into orchestration across functions, across planning horizons of strategic decision-making versus tactical decision-making versus execution, it requires organizations to rethink their fundamental operating models, their underlying processes, how they're organized, how they think about their metrics. And that takes time, right? And that's why as we -- I think in my humble opinion, I think most people are over-expecting what impact these orchestration capabilities will have in the enterprise in the near term. But I think they're also underestimating the impact in the mid- to long term. But it's not just a technology-driven approach you've got to also make fundamental changes to your organization structure, operating models, processes, metrics and things like that to really transform your ways of working, right? And that's why the work we do together with our partners is very critical in achieving the true outcomes from this vision.

Your next question comes from the line of Suthan Sukumar at Stifel.

Congrats on a very impressive quarter. With respect to my question, I just had a -- I wanted to chat on the competitive landscape with AI. How are you guys positioning Maestro Agents versus the agentic frameworks that are offered by some of the incumbent underlying platforms like SAP that your customers already use? I'm just wondering, is this more of a share of wallet discussion at the orchestration layer? Or is there a coexistence and interoperability here that can be leveraged?

Yes, I think you were cutting out a bit, but I think I got the gist of the question. Look, I think what I'll say is most organizations are early in the journey to really leverage these agentic orchestration capabilities, right? Customers have done pilots with agents, they have put many agents in production, including with ourselves, and they're seeing good results when it comes to getting productivity and automation improvements. But to really truly do orchestration, I fully expect that companies will have to have orchestrator agents work across a very heterogenous systems landscape, right? And in that regard, our philosophy and our approach is to be interoperable, right? We're not trying to be everything to everyone. But as we have sort of architected our platform and as we are making investments in the go-forward road maps in our platform, we're really architecting in a way that we can be interoperable, right?

In the end-to-end world of supply chain, any supply -- any Fortune 1000 company may have anywhere from 10 to 100 applications that power that end-to-end supply chain, right? And so we had to really have the ability to really be able to integrate to those systems and work across those systems. And the orchestration use cases that agents can facilitate will also need to traverse a pretty diverse systems landscape. That's where this semantic and ontology layer is very important because it provides the context for what these orchestrators do. It provides a common taxonomy. And then these agents have a chance of traversing that heterogenous landscape.

And of course, as companies are doing that, they're always looking for opportunities to consolidate that heterogeneous landscape and to simplify them, but they continue to be fairly heterogenous in that end-to-end supply chain world. So our design principle is really around interoperability and coexistence. And at the same time, we expect that we'll have our own agents that will play the orchestration role. And at the same time, I expect that there'll be orchestrator agents from third parties where they leverage the Maestro platform for making decisions and for doing computations that we are very good at doing for supply planning, for demand planning, for inventory optimization, for production scheduling and things like that. So I think it will work in both ways, and that's how we're architecting our platform.

We've reached the end of the Q&A session. I'll now pass the call back to Rick for closing remarks.

Thank you, everyone, for participating on today's call. We appreciate your questions and your ongoing interest in Kinaxis. We look forward to speaking with you again next time when we report second quarter results. Bye for now.

This concludes today's call. Thank you for attending. You may now disconnect.

Good morning, and welcome to the Kinaxis Inc. Fiscal 2025 Fourth Quarter and Year-end Results Conference Call. [Operator Instructions] I'd like to remind everyone that this call is being recorded today, Thursday, March 5, 2026.

I will now turn the call over to Rick Wadsworth, Vice President, Investor Relations at Kinaxis Inc. Please go ahead, Mr. Wadsworth.

Thanks, operator. Good morning, and welcome to the Kinaxis earnings call. Today, we will be discussing our fourth quarter and year-end results, which we issued after close of markets yesterday. With me on the call are Razat Gaurav, our Chief Executive Officer; and Blaine Fitzgerald, Chief Financial Officer.

Some of the information discussed on this call is based on information as of today, March 5, 2026, and contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those set out in such statements. For a discussion of these risks and uncertainties, you should review the forward-looking statements disclosure in the earnings press release as well as in our SEDAR filings.

During this call, we will discuss IFRS results and non-IFRS financial measures including adjusted EBITDA. A reconciliation between adjusted EBITDA and the corresponding IFRS result is available in our earnings press release and MD&A, both of which can be found on the IR section of our website, kinaxis.com and on SEDAR+.

The webcast is live and being recorded for playback purposes. An archive of the webcast will be made available on the Investor Relations section of our website. Neither this call nor the webcast may be rerecorded or otherwise reproduced or distributed without prior written permission from Kinaxis. We have a presentation to accompany today's call, which can be downloaded from the IR homepage of our website. We'll let you know when it change slides.

Over to you, Razat.

Thanks, Rick. Turning to Slide 4. I'd like to start by saying how thrilled I am to be a part of the Kinaxis team. It's a company I've admired and competed against for several years. Here are my top 3 reasons for joining Kinaxis. One, getting back to my roots in supply chain software, where I've spent over 20 years in my career, particularly at this time when organizations are experiencing unprecedented levels of demand and supply volatility; two, to build and scale a company that is already a market leader in AI-powered supply chain planning and orchestration; and three, the tremendous talent and culture in the organization that is rooted in innovation and customer success. I am truly excited to build and scale the business while delivering unprecedented value to our customers.

Turning to Slide 5. I couldn't have joined Kinaxis at a better time. The team performed really well, and we had a record-setting fourth quarter and year with ongoing momentum in 2 key growth metrics. Our SaaS revenue grew by a healthy 19% in Q4 and 17% for the year, significantly higher than our initial guidance range of 11% to 13%. Perhaps more importantly, our ARR balance grew by 20%, accelerating from 12% growth at the end of 2024. Incremental bookings hit record levels in the quarter and year. This momentum sets us up really well to target higher SaaS revenue growth in 2026, as Blaine will explain and speak soon.

This growth momentum combined with operating efficiency also translated to significantly improved profitability. Full year adjusted EBITDA was at a record level and grew by 30%. The margin in Q4 was 26% and was 25% for the year, at the high end of our initial guidance range and a year early at our midterm target. We see room for ongoing improvements in coming years.

Moving on to Slide 6. The new business we won in the quarter and year demonstrates excellent execution on important go-to-market strategies. Let me give you some color. In Q4 and in fiscal 2025, we won roughly 1/3 more new business than in any previous quarter and year in our history, measured by the total average annual contract value in the period or ACV. The number of contracts with $1-plus million in average ACV was at record levels in Q4 and the year. We won 21 deals over $1 million in the year versus 6 in 2024 and over 30% higher than the closest result.

When looking at total contract value or TCV over the committed term, we won over 100 deals above $1 million. Our pipeline suggests that 2026 could be another strong year in this regard. Together, these metrics reflect the growing market need for companies to develop agility and adaptability as they navigate unprecedented levels of supply and demand volatility. We continue to be the market providers, the go-to-market providers for AI supply -- for AI-powered supply chain planning, decision-making and orchestration for the world's largest and most complex supply chains.

Going to Slide 7. We won some world-class companies in Q4, which are distinguished not just by their size, but also by the role they play in the global AI transformation. As investments increase in the build-out of data centers and related AI infrastructure, Kinaxis Maestro is becoming the default choice for supply chain planning and orchestration across the value chain.

During Q4, we won a top 5 global semiconductor foundry, which manufactures highly advanced GPUs for the world's AI infrastructure leaders, mobile device leaders, massive players in the digital economy and others. You'll recall that in the first quarter of 2025, we also won another global leader in the semiconductor ecosystem. In Q4, we also won a major player in the global storage business, serving the world's largest cloud providers, consumer electronics companies and other device makers. Last quarter, we talked about winning a material science company that is also a key part of the global data center infrastructure.

We have continued our amazing run in the oil and gas sector by earning the business of Marathon Petroleum Corporation, a leading integrated downstream and midstream energy company headquartered in the U.S. and operating the nation's largest refining system. The AI economy is energy hungry, so our success in oil and gas continues to position us really well. We're also seeing increasing demand from energy utility companies that are expanding their operations to service the surge in data center needs.

We're performing very well in other growing markets like aerospace and defense. Companies in the sector are seeing significant growth in demand while leading with complex bill of materials, engineer-to-order operating models and capacity constraints. In the fourth quarter, we won one of the world's largest aerospace engine makers, which powers defense, civil and business aircraft worldwide. We already support Honeywell, Lockheed Martin, Raytheon, L3Harris and several other leaders in the aerospace and defense space.

In consumer goods, we won the Magnum Ice Cream Company with revenues of roughly EUR 8 billion in 2025, the Magnum Ice Cream Company is present in 80 markets around the world and is home to icons like Magnum, Ben & Jerry's, Cornetto and the Heartbrand. If that wasn't enough, we also won a top 5 global chocolate company in Q4.

At the end of 2025, roughly 85% of our ARR is split between our top 4 vertical markets: life sciences, high-tech, consumer products and industrial manufacturing, including aerospace and defense. Maestro's ability to offer comprehensive AI-powered supply chain planning and orchestration for such a diverse set of major manufacturing markets, all without custom coding is unparalleled. There are still 14,000 prospects remaining in our markets, and we have never been in a better position to win them.

Moving on to Slide 8. Despite outsized success winning major new accounts in Q4, 55% of gross additions to ARR came from expansion business with existing customers. For the year, that number was 53% compared to 45% in 2024. It was our biggest year ever for expansion business. We revamped the structure and goals of our installed account teams at the end of 2024. The impact has been meaningful, immediate and lasting. The contribution of expansion business from applications hit an all-time high with newer products like enterprise scheduling, machine learning-based forecasting and supply optimization making notable progress. We have over 400 customers and a growing set of capabilities to take to market to them. There is still massive room for growth within the installed base.

Going on to Slide 9. I'm excited to tell you more about our ongoing journey with AI, the commercial launch of Maestro Agent Studio. This is a next-generation capability that gives supply chain teams a no-code way to compose AI agents grounded in their real operating context to reimagine the ways of working and delivering the next level of value outcomes. The agents are proprietary -- use proprietary data, workflows, resources and tools in our Maestro platform and can leverage the context of the most comprehensive digital representation of the complex and interconnected physical supply chain.

Working within Maestro's trusted supply chain planning environment, the agents help teams concurrently evaluate trade-offs and coordinate decisions and actions as business conditions change, and the business conditions are changing at unprecedented levels as we speak. Maestro Agent Studio embeds leading large language models, including OpenAI, ChatGPT and Google Gemini with others like Anthropic's Claude in testing and keeps agent behavior anchored in Maestro's trusted data intelligence and governance.

The agents call on and complement our existing decision automation capabilities that are anchored in decades of deep domain expertise and sophisticated mathematical models that LLMs aren't designed to replace. This includes advanced machine learning capabilities, deep optimization algorithms and heuristics algorithms. Together, these capabilities create a practical foundation for more autonomous supply chain operations that deliver faster, better decisions with confidence and trust.

To date, early innovator customers are using Maestro Agent Studio for exciting use cases. For example, a major global electronics manufacturing services company is autonomously analyzing forecast quality and outside-in demand signals across business units to recommend improved forecast quality. A prominent consumer fashion company is analyzing demand changes to help planners understand the impacts on production and distribution and determine mitigation strategies. A global life sciences company is eliminating steps in inventory risk assessment to surface insights in seconds instead of hours. And several early adopter customers are streamlining reporting processes to reduce manual effort and tons of hours per month.

Our progress is exciting, but the best is yet to come. So far, Maestro Agents are focused on working with data within our own platform. As we continue our AI journey going forward, we are expanding Maestro's reach to the broader ecosystem with an expanded data fabric and an abstracted semantic layer to enable composable agentic orchestration right across the supply chain.

In 2026, our plans are the following: orchestrator agents that coordinate and sequence multiple agents across concurrent supply chain workflows, securing connections between Maestro Agents and external agents and systems through emerging protocols like MCP and A2A, expanded data context and semantics with an extensible ontology layer, enabling agents to reason consistently across larger data sets and analytical environments beyond Maestro. Through agentic connections to other systems that can provide relevant data and insights, we can leverage our context-sensitive real-time concurrent planning engine to help customers make better, more informed decisions and achieve unprecedented positive outcomes.

Moving on to Slide 10. Maestro Agent Studio and our prebuilt Maestro Agents are fully available today. Monetization will happen through our next-generation pricing structure, an evolution that we've launched with customers and which introduces the Maestro activity units. Our new pricing structure remains subscription-based and still reflects a platform fee based on customer size and fees for individual functional modules like supply and demand planning, inventory optimization, production planning, enterprise scheduling and so on.

However, now a subscription also includes bundles for Maestro activity units or MAUs, which expand the basis for usage-based pricing in our structure. Customers will commit for the full term of the contract to a quantity of MAUs bundles that reflect anticipated usage. The size of MAU commitment grows with a number of scenarios, AI tasks and automations and plan calculations and data exports a customer expects to engage through our MCP server. This more fulsome notion of usage achieves some very important goals.

First, over time, we anticipate a bigger share of Maestro work to be conducted by AI agents. So our pricing needs to reflect that important value. If efficiencies result in fewer users, we are compensated by the growth in AI tasks and automations. Second, since we expect Maestro to interact more with a broader network of interoperable agents, we need to capture the value of the intelligence and analysis we share at. The data export aspects of MAU compensates us for that. Finally, embedding plan calculations in the MAU better reflects the value that customers receive and the costs we incur through normal plan iterations. Maestro now has the instrumentation to track MAU usage and persistent overages require additional MAU subscriptions.

We will learn a lot more about MAU usage and our next-generation pricing model over the next few quarters and fully expect some tweaking along the way. I am confident that it better aligns pricing with the value we create for customers in an even more AI-forward world.

The new pricing model is getting thoughtfully rolled out in a phased approach. I see AI as meaningfully expanding our TAM in the long run. As with all meaningful innovation, we encourage you to both avoid overestimating its impact in the short term and underestimating it in the long term. Our customers run the world's most important, complex and innovative supply chains. By necessity, they move carefully and thoughtfully, but they undeniably move forward.

I'll pass the call to Blaine to discuss Q4 and 2025 results and our 2026 outlook.

Thank you, Razat, and good morning. Q4 was a great record-breaking quarter for Kinaxis, and 2025 was also beyond expectations in key areas. We are positioned well for even more progress in 2026. I'll start with Slide 11.

As we look at the numbers for the fourth quarter and compared to Q4 2024 results, total revenue was $144.2 million, up 16% or 14% in constant currency, driven largely by very strong SaaS revenue growth. SaaS revenue was $97.2 million, up 19% or 16% in constant currency, thanks to strong momentum winning new business throughout 2025, including record levels in Q4. Subscription term license revenue was $1.7 million, up 8% and consistent with expected renewal cycles for on-premise customers. Professional services revenue was $40 million, up 14% and stronger than expected due to higher realized rates as we work to ensure that pricing fully reflects our premium services. We continue to successfully ship work to system integrator partners, and we'll continue to focus on that in 2026.

In 2025, partners participate in almost 70% of new customer implementations won by our direct sales team. Maintenance and support revenue was $5.4 million level with comparative period. Our gross profit was up by 26% to $94.3 million or a 65% gross margin, greatly improved from 61%. Our software margin was 78%, up substantially from 73%, largely due to more efficient delivery of our software. We see room for ongoing improvement as we complete our migration to the public cloud. Professional services gross margin was 32% compared to 29%, reflecting the higher realized rates in the quarter, as mentioned.

Adjusted EBITDA was up 19% to $37.6 million, a record level. This reflects strong revenue growth, a higher gross margin and strong control over operating expenses. Adjusted EBITDA margin was 26%, up from 25%. Our profit in the quarter was a record $19.5 million compared to a loss of $16.3 million in the fourth quarter last year, which, as you remember, reflected some onetime items. Cash flow from operating activities was $29.9 million, up 24%. Cash, cash equivalents and short-term investments were $324.7 million, up $26.2 million from last year despite a very active share buyback program.

Moving to Slide 12. Key aspects of full year results were beyond our expectations. SaaS revenue, our most critical GAAP measure, grew 17% compared to the initial guidance of 11% to 13% and came in at the top end of our most recent guidance range. Constant currency SaaS revenue grew 16% versus initial guidance of 12% to 14% and at the top end of our most recent guidance range. Total revenue was $548 million, up 13% and at the top end of our guidance range despite shifts from subscription term licenses to future SaaS revenue as well as lower professional services than expected as we shifted more work to partners and faced a challenging pricing environment earlier in the year.

In constant currency, total revenue was $540 million, in line with recent guidance. Adjusted EBITDA grew an impressive 30% from 2024 to a record $138.4 million. The 25% margin is the highest since 2019 and a big step from 22% in 2024. Our adjusted EBITDA margin was at the top end of guidance and hit our midterm profitability goal of full year ahead of target. We're pleased with the progress.

On Slide 13, our trailing 12-month free cash flow margin remains strong -- onetime payments we made in the first quarter relating to tax planning and litigation settlement reduced the results by 5.1 percentage points. So the normalized result is 25.6%, similar to our adjusted EBITDA margin for the year and trending positively.

If you flip to Slide 14, annual recurring revenue growth in 2025 was impressive, growing by 20% year-over-year compared to 12% in 2024. In constant currency, ARR growth was 18% compared to 14% in 2024. We added $73 million to our ARR balance in 2025 with $26 million of that coming in the fourth quarter, both records. This dramatic progress reflects improvements in go-to-market strategies and personnel over the last year as well as the benefits of an increasingly differentiated and AI-centric product. As Razat already mentioned, some drivers of growth included many more deals above $1 million ACV, more large enterprise accounts wins and more focus and execution on expansion business.

On Slide 15, SaaS and total RPO balances and growth remain very robust. Both measures show a healthy 3-year CAGR of 18%, and our total RPO is rapidly approaching $1 billion. This metric continues to highlight robust growth in our subscription business. Loyal customers driving gross revenue retention over 95% and is also influenced by normal renewal cycles.

Looking at Slide 16, I am very pleased to introduce 2026 guidance. Given our strong momentum, we expect SaaS revenue growth of 17% to 19% in 2025, which at the midpoint is consistent with our constant currency ARR growth rate exiting 2025. We expect total revenue of $620 million to $635 million. Underlying this guidance, we assume that professional services revenue will grow in low single digits as we expect success enabling partners to handle more work, which is a key strategy to achieve scale in the business overall. Maintenance and support revenue should be flat to slightly down from 2024, given the recent conversions on-premise contracts to SaaS. The remainder of total revenue will be made up by subscription term license revenue, which should see growth in the 60% range versus 2025 and then decreasing to 2027 by roughly 25%.

For 2026, approximately 60% of subscription term license revenue will be recognized in Q1, roughly 1/4 in Q4 and the remainder in Q2. Ongoing demand from on-premise customers who are moving to our hosting infrastructure could change the assumptions, and we will advise if that happens. We view 25% adjusted EBITDA margin as a new floor for the foreseeable future and are guiding to an adjusted EBITDA margin of 25% to 26% for 2026 as we make strategic investments in the year, primarily to drive exciting growth initiatives in AI and go-to-market activities that Razat will speak to shortly. Our business model and strategy allows for even higher margins in the coming years. I'll add some other color to help you with your models.

We expect our total gross margin rate to continue its steady growth in 2026, driven by a more favorable revenue mix and a slightly improved professional services margin. We expect our subscription revenue margin in 2026 to be similar to 2025 as the benefits of moving North American customers to public cloud will be offset by onetime costs related to those transitions in the year.

With respect to operating expenses, we expect sales and marketing to grow by high single digits relative to 2025. We expect research and development to grow in the high 20 percentage range versus 2025. And excluding stock-based compensation, we expect roughly 10% growth in general and administrative expenses compared to 2025. Including stock-based comp, we expect growth to be above 25%, reflecting some senior hires. Finally, we expect CapEx will be in the $8 million to $10 million range as we make office improvements to support growth in Japan and undergo internal IT refresh.

I'll leave you with Slide 17. As we exit our quiet period, we will be maximizing the size of our normal course issuer bid by roughly doubling the repurchase limit to approximately 2.8 million shares or 10% of our float by October 31, 2025. We've already invested $54 million under the buyback and repurchased roughly 440,000 shares. At the average price paid for those shares, our new commitment put in an additional investment of up to approximately $284 million throughout the term of the buyback. We see tremendous value in maximizing our share buyback while public markets continue to misvalue complex AI-enabled software companies like ours.

Kinaxis business has never been in better shape over my 6 years here. ARR growth has reaccelerated, and we are winning more industry leaders than ever, including in markets that have huge AI and other tailwinds. We have room to improve SaaS revenue growth and adjusted EBITDA margin in the coming years. We have a revitalized go-to-market team and the market's best product that continues to lead the AI transition in our space.

All this made my personal decision to take a new opportunity extremely difficult. I'll be joining an exciting private company with a path to go public ahead, which is a really exciting place to be for a CFO. I'm sure my departure raises questions as senior management changes always do. Let me address them right now.

First, I believe Kinaxis will be a huge AI winner, and we have a great new pricing model to monetize the inevitable evolution of how Maestro will be used. Second, Razat will be a fantastic leader for Kinaxis, and I truly wish I could have partnered with him a lot longer. There is no better time to have an industry veteran CEO with such impressive qualifications on the product side of the business as well as such strong go-to-market and overall leadership job. Finally, 2026 is set up to be a great year, and overall, the future looks exceptionally bright. So I'll be cheering from the sidelines.

I want to thank the entire senior team for their support over my time here, including past leaders like John Sicard, Richard Monkman and Bob Courteau. They taught me a lot and created a truly special culture. And thanks to you, our shareholders and analysts for years of partnership as well. I've learned a great deal from you and enjoyed getting to know you all. We may meet again.

For now, I'll let Razat make some concluding remarks.

Thanks, Blaine, for your countless contributions to Kinaxis. We've strengthened our business foundation, built a great finance team and successfully steered the company through great growth, opportunity and change to leave us in tremendous shape today. I wish we could work together longer, and I hope our paths cross again soon. I'm very pleased that Blaine will be with us through our Q1 earnings call in early May. In the meantime, we're actively searching for a new CFO to fill his big shoes.

Going on to Slide 18. Kinaxis has a long history balancing rapid growth with strong profitability, and that will not change. A 25% adjusted EBITDA margin represents a solid floor and will also allow us to invest in exciting growth opportunities. We are focused on accelerating the transformation of Kinaxis from a supply chain planning solution provider to an AI-driven supply chain decision-making and orchestration platform. I'll highlight 4 key areas of investment in 2026.

First, we're going to accelerate our road map for building out our core planning capabilities and turbocharging the leverage of agentic AI, including an extensible data fabric and semantic layer to enable our fulsome supply chain orchestration vision. Second, we're going to keep our foot on the gas for even greater go-to-market success. We will add quota-carrying capacity to expand account coverage and develop the go-to-market operating model for our new and exciting agentic capabilities. Third, we'll increase the leverage of key partners to both give us bigger edge in winning new business and to scale and help deliver the customers successfully with an increasing share of the implementation services. We are expanding our investments in training and enablement of our partner ecosystem and ensuring strong collaboration with solution assurance during implementation cycles.

Finally, we are mobilizing a team of forward deployed engineers to accelerate the go-to-market usage, adoption and value realization from our agentic capabilities. This team will work across the life cycle of our relationship with customers with a mix of deep supply chain domain knowledge, data science and data engineering skill sets to compose agentic solutions architected to deliver valuable outcomes while still leveraging the core foundation of Maestro.

We've already hired a leader for this group, a highly respected executive who rejoins Kinaxis after roles leading go-to-market and customer engagement teams for supply chain at Palantir and Celonis as well as senior roles at Cooper and Llamasoft. I couldn't have asked for a better person to spearhead our agentic solutions initiative.

Internally, we have a company-wide program to identify use cases for AI to transform our ways of working in an effort to gain velocity and productivity as we scale up the business. In our product teams alone, roughly 90% of all requests, which is the way that new code goes into testing -- goes from testing into live environments, includes AI-assisted code, helping us gain speed and freeing up more time for innovation. Roughly 80% of engineers and growing are using AI in their work and half of those are power users.

I hope these priorities give you a sense of how strongly Kinaxis continues to lean into the AI transformation opportunity. Evolving from a market-leading supply chain software solution to a composable agentic supply chain orchestration platform is a unique opportunity for Kinaxis and is why I am here. As you know too well, there is a lot of confusion in the public markets about who the winners will be in a more AI-forward world. We are working hard to prove that all the innovations in AI, data and agentic architectures are a significant tailwind for Kinaxis as we build the future of supply chain decision-making and orchestration. In the meantime, we are focused on delivering quarter after quarter as we did in Q4 and throughout 2025.

Thank you for your ongoing support. I will now turn the line over to the operator to start the Q&A session.

[Operator Instructions] Your first question comes from the line of Richard Tse with National Bank Capital Markets.

Great results, guys. Just before, Blaine, congratulations and all the best in your new job. It's a pleasure working with you over the years. Razat, like really great color on AI. And against that, I've got a really sort of basic question I'll ask here because we're getting a lot of inbounds on this. And so when you think about Kinaxis, why is it that a sort of high-powered sort of small team could not come in and build an AI native platform to compete directly with Kinaxis here. I know it's a basic question, but it's certainly one that we're getting a ton of inbounds on.

Yes, Richard, thanks for asking that question. And we think about this very deeply. And I think the underlying facts are what are the types of problems we are solving for our customers. The types of problems we're solving for our customers requires a very deep understanding of the supply chain domain. And the supply chains that our customers operate are highly complex, highly interconnected. And you need to understand the physics of the supply chain before you can use AI or agents to do anything with it, right? And that's what we've built in Maestro over decades long. And that platform is the single richest representation of that complex interconnected supply chain that our customers operate.

And then on top of that, we, like everyone else in the enterprise software space, are leaning in, in leveraging generative AI to transform the user interface to a more conversational interface, which is democratizing the usage of our solution. But also we are leaning in on all the new data architectures and the semantic architectures to create a composable agentic platform, right?

So when you think about the kinds of customers we have, these are customers like Ford Motor Company and Unilever and Schneider Electric and Merck, they rely on the trust and the robustness and the industrial strength and the understanding of the physics of the supply chain on our underlying platform. And then we are layering the intelligence and the automation and the prediction layer with agents and with AI. So we feel very confident in our ability. We're clearly seeing the demand for it in our customers, and we have every intention to continue performing to prove that out.

Okay. Great. I have just one follow-up question, and I'll pass the line after that. So with respect to the new pricing model, is sort of, I think, the bias here that it will be sort of incremental to the existing growth profile here of the company because obviously, it sounds like that's kind of what is happening here. And when it comes to profitability, can you maybe just provide us a bit of color because, obviously, it's sort of transaction based and there's a lot of sort of things with tokens, like I imagine the costs won't be fixed. There'll be obviously sort of variable. So how are you thinking about sort of those two things? And then I'll pass the line.

Yes, Richard, I'll start. As we're going through this, it's somewhat exciting in terms of -- we think this is a potential to accelerate growth in revenue while keeping our costs actually at the same levels. As you know, there are some like AI modules that we have that are a little bit more costly than others. But overall, what we've done is we covered that with this actual almost variable cost that is actually committed. And that's the one thing that I think people need to realize for what we're doing here is that although it's consumption and usage based, we are obviously going forward with a committed revenue scheme.

So at the end of the day, it won't look too much different from what we have today. However, there are areas of revenue opportunities and value that we're giving to our customers that we think that we should be monetizing on. And so we think this is going to be both beneficial to overall EBITDA, but also very much the revenue side. I will say that in any of our guidance that we've given today because it's early days, we have not put any of that upside in our guidance at this stage just because it's too early to tell how that's going to play out.

Yes. Let me just add a little bit to that as well. So the biggest driver for us to really evolve to a usage-based pricing structure is to better align our offering going forward and the substance of the value we're bringing to our customers going forward to the way we price our offering, right? And so a lot of the metrics that form the basis of the MAUs, the Maestro activity units are anchored on those usage patterns.

I fully expect that the initial phase of adoption, and we're seeing this with early adopter customers right now is really around making the key personas that interface with our applications, whether it's a planner or it's an extended part of the supply chain organization or even senior executives within supply chain organizations. It makes them more productive. It makes them leverage our platform and gain insights from our platform and take actions on our platform in a far, far more efficient way in a far easier and simpler way as well. So that's the first phase of adoption.

As we keep building out our platform and we get into a more expanded agentic orchestration layer, I fully expect we'll be getting into more and more use cases that are developing digital personas, right? And so we don't want to tie our pricing to just users because I think we're going to scale across our customers' organizations in a very nonlinear way from a user perspective. And so that's the whole emphasis and the thrust behind our MAU structure.

Your next question comes from the line of Thanos Moschopoulos with BMO Capital Markets.

I'll echo the congrats to Blaine on the opportunity. Maybe starting off with a question for Blaine. When I look at your SaaS backlog at year-end relative to your SaaS revenue guidance, it's a higher coverage ratio with respect to the backlog than we've seen in prior years. Is that conservatism? Or is there some other dynamic?

Yes, it's a good observation. So we're -- our CRPO is about 80% of what our midpoint on our guidance is, which is a good thing to point out. I think we are having a healthy amount of confidence in what we're landing at 17% to 19%. I think there is always opportunities. I just mentioned one of them with NGP where we could start next on pricing, which could show that we could maybe potentially beat that. Obviously, if you look at our past and look at 2025, in particular, we did much better than that 88 percentage points. And I think that's something that we are continuing to evaluate. And I'm hoping we'll be putting some smiles on people's faces throughout the rest of the year and beating that 17% to 19%.

But right now, I'd say 10 months, I guess, 9 months to go in the year, it's a long way to go. We'll see how things play out. Hopefully, you'll be hearing some increases in that guidance over the year.

Great. And then for Razat, how would you characterize the near-term spending environment? Clearly, you had strong bookings in the quarter, but is that a function of better execution, better competitive performance on your part against the stable markets? Or has there been some improvement in the demand environment with supply chain being more topical with tariffs and the like?

Yes, I think it's a good question. Look, I think it's a few reasons. I'll put it in sort of three buckets there. First, I do think there is growing levels of supply and demand volatility, which creates a better need -- even a bigger need for our platform, right, for our customers because customers are trying to gain agility, gain adaptability and through sort of high degrees of uncertainties and volatility, they need a platform like Maestro that enables scenario planning, enables intelligent decision-making while incorporating all the physics of the supply chain. So I think the overall macro environment has been a tailwind for us.

The second is definitely our execution has improved significantly. Our go-to-market execution in the last 12 to 18 months has significantly improved. We have revamped the makeup of our go-to-market engine. The way we are engaging with customers has been significantly improved. And then we're going to continue to add capacity and coverage in the field to make sure we can continue to scale up. So that's the second big reason.

And then I think the third big reason is I think there's a deeper interest in organizations that have had legacy systems and processes and supply chain planning and decision-making to really look for the next wave of productivity improvements, right? And that's causing a significant replacement cycle of old legacy systems, right? And we are one of the preeminent providers that is replacing older legacy systems right now in an effort to really architect processes and operating models and applications that help companies get the next wave of improvement in working capital efficiencies, next wave of improvement in supply chain operating cost efficiency.

So these are the three big reasons, I would say, that is driving the growth momentum we're seeing in the company. And by the way, as we come into this year, we continue to see our pipeline growing along the same dimensions.

Your next question comes from the line of Kevin Krishnaratne with Scotiabank.

Congrats, Blaine, great working with you and good luck on the future. Question on your R&D. Did I hear that you plan to grow that line 20%? And if so, can you just comment on the moving pieces there? I noticed in your slide deck, you talked about the addition of forward deployed engineers. I'm just wondering sort of what you're seeing? Is that driven by customers? Are some of the decisions taking a bit longer on their side requiring you to kind of step up your -- the FTEs and to help drive that adoption. Just wondering if you can unpack the growth in R&D.

Yes. Great question. And so what I said is that we'll be in the high 20 percentage range for that growth year-over-year. And there's a great reason. I mean we're seeing unprecedented momentum in the business at this stage. We had -- in 2025, we had the biggest deal ever. We had the biggest day ever. Every quarter had the biggest amount that we've ever seen for the demand coming in and the wins that we had for every single region. We had adjusted EBITDA, net income, basic EPS, like everything was off the charts records for us. That demand makes us believe there's a bigger opportunity that we could actually go after at this stage. In R&D, with the innovations that we see in front of us with agentic AI, with what's happening on trying to get access to the machine learning that we have in place and the tool that we have that our product has built, we just see that there's so much more than this.

What -- a lot of the discussions we're having right now between Razat and myself and the other leaders of this team is that we're not okay with just being a supply chain planning company. What you're probably going to see is a company that may not even have supply chain in it at some point in the future and be more focused on enterprise AI. I think that is the eventual vision of where Kinaxis will do extremely well. And I think we have now this leadership team that -- which is part of the reason why this decision is so tough is that we have a leadership team that's all coming together and creating a huge opportunity.

So the R&D spend, yes, it's going up. It's going up because there's a huge, huge opportunity, and we're seeing that today from every single customer that's asking for more and more and more.

Yes. Maybe just add a little bit more color to that. So look, our R&D investments are growing in 2026, and that's a very deliberate approach to this, right? And I would say that it's in two big buckets. One, investing in our core Maestro platform. Given the new architectures, given the new performance and scale expectations of our customers, we need to continue to expand and build on the core platform that we have and build out further the broader planning footprint that we have with our customers. So that's an important area. There's a lot of investments happening there.

In addition to that, as I talked about earlier, there's a new architecture evolving with agentic AI. And we want to be leaning in and shaping what that means to the world of supply chain decision-making and orchestration, right? And so we are leaning in and building out this data fabric, abstracting the semantic layer, building out the agentic infrastructure around it and working with early adopter customers in faster cycles. So these things are important investments to really future-proof a sustained growth path for us in the coming years.

On your question about the forward deployed engineers, look, this is a really important operating model that we're putting in place because unlike taking our traditional planning footprint, where the customers had a strong understanding of the feature functions requirements, and then we would be evaluated by those customers based on the fit of our platform against those feature function requirements. In this new world of agentic AI, it takes a different shape and form where the customers are more anchored on their pain points and outcomes. And then we together formulate what is the solution set required and how to architect the feature set required with the combination of our Maestro platform and agentic architectures to create a tailored and composable solution.

That requires a very different engagement model, and that's where the forward deployed engineering skill set becomes really, really important. We're going to be investing in that. We've hired the leadership for that. We've got some internal skill sets. We're going to be hiring additional resources in this mix to really scale this business in a discovery-led consultative model so that we can really harness the power of the platform we're building out and deliver the outcomes throughout the life cycle of our customers.

Your next question comes from the line of Paul Treiber with RBC Dominion Securities.

A question for Razat. You talked about one of the reasons that you joined Kinaxis is building and scaling the company that you see as a market leader. What do you -- as you look forward in the next couple of years, what do you see as the largest challenge to scaling that you're looking to address as you grow?

Yes, it's a good question. And what I'll say is it's a unique moment in time for Kinaxis and frankly, for me to come in and to really build and scale. And I'm very bullish on the market need on the market opportunity, the market size. I'm very bullish on the domain problems that we're solving and the hard complexity and the value generation potential of those problems. I think the biggest barrier for a company like us would be to continue to scale in terms of retaining and attracting the talent that is required for us to realize the potential we have and to realize the expectations our customers have. That continues to be the biggest sort of thing to focus on is the talent.

What doesn't keep me up at night is the market potential. I'm not too worried about the competition because we really have some amazing customers, and we have a lot of momentum. It's really allows -- really about scaling the business in every dimension with the best talent because we solve hard problems. We're not solving easy problems for our customers. And so we need the top caliber talent. And so you're going to see us continue to expand the talent. We've got -- we're anchored with some amazing talent in Ottawa, Toronto, Dallas. We've got a rapidly growing team in India, in Chennai and Bangalore. You can fully expect us to create new hubs of talent as we continue to scale up the business.

And an interesting point you made that you're not worried about competition. You mentioned earlier the new hire from Palantir. The -- and I think this is one of the first times I've heard Kinaxis mentioned Palantir. Can you speak to like the competitive environment, if you're seeing these new entrants get traction in the market? Or is it still -- do you just see the traditional competitors?

It's -- the net story there is it's a very fragmented market. You've got a mix of a lot of old legacy players, including some of the ERP players, where we're actually driving replacement cycles. You've got some players that have emerged more so in the last 10, 15 years that we see in different cycles in different industries or different verticals or different geographies. And then you've got some new entrants that are coming in, right? But through all of that, our win rates have been very high throughout 2025. And maybe Blaine can talk a little bit more about the win rates there.

Yes, that's a great point. Obviously, the -- it's a common question is the competitive landscape changing? The short answer is yes, but only slightly. SAP, o9 and Blue Yonder are still the main competitors we see. We have extremely high win rates. I think we've talked about in the past over 60% against those 3, which we can say is the same. I would say one of those, they almost landed the goose egg in terms of trying to win dollars from us, which is a pretty incredible, I guess, achievement to be almost 100% against one of those big 3 competitors. But those are the big 3 that we continue to see over time. I think there's going to be more new entrants that are going to come in. But at this stage, it's a very, very small percentage of the competitors that we do see.

[Operator Instructions] Your next question comes from the line of Lachlan Brown with Rothschild & Co. Redburn.

Congrats on the strong results. And Blaine, congrats on an excellent tenure as CFO. I would like to dive into the regions. Asia was pretty successful throughout 2025. Europe was a good driver of growth, while North America was a laggard. Could you run us through why we're seeing different outcomes in the different regions? The recent bookings over the last couple of quarters tell a different story? And just any initiatives you're doing to push growth into the North American market?

Yes, sure. Well, number one, I'll just reiterate, we had records every quarter, every -- for the full year for every region. I would say though, the one that outperformed by a significant, significant amount was EMEA. It was well beyond our expectations. I won't say the percentage, but they were extremely much higher than their target they had. The APAC team also did extremely well. They had a Q1 and Q2 that was much higher than our expectations. And then North America, they set the all-time record right now. They are the ones that are the champion for us in terms of those records for the full year. So it's one of those situations where I don't -- people look for the bad news. We don't have the bad news in any region at this stage. We're very proud of those regional leaders and how they performed. If there's one that kind of stuck out as way over the targets that we had, that was EMEA. They did extremely, extremely well.

Yes. And look, North America is our largest region in terms of bookings and ARR and revenue, and we have tremendous momentum in North America right now. I think we're going to be off to a great start this year, and we ended obviously Q4 at a very, very strong level as well. So actually, I'm super excited about the momentum in our North America business.

Your next question comes from the line of Stephanie Price with CIBC World Markets.

Congratulations, Blaine and Razat, looking forward to working with you. My question is on the Maestro Agents. They've been available more broadly to your customer base. Just curious about early feedback on the consumption bundles for the agents and what customers are saying about the pricing strategy that you discussed? And maybe more generally, how customers are kind of thinking about the pace of AI uptake here?

Yes. Look, it's a good question. First, on the early adoption with customers, right? So we were very deliberate in curating a mix of customers from various industry verticals that we play in to make sure we could work with those early adopter customers in a very iterative agile way and continue to improve the underlying Agent Studio that we've developed now. And the results are exciting. Clearly, there's a lot of learning cycles on the customer side and our side as we go through that. And what we're finding is the use cases fall in sort of or 2 or 3 different buckets, right? There are use cases that are very straightforward and are easy to compose and deploy, and they add additional intelligence and insights and create a much simpler experience for the users that are already interfacing with Maestro today. That's sort of the low-hanging fruit, if you would, and provides a lot of quick hits.

The second category are use cases that are really oriented around creating a different way of working in creating automation capabilities in being able to rethink how planning gets done in the enterprise, right? And those, while our platform is an important enabler to that, they also require changes in operating models, in governance structures, in underlying processes for our customers. And that's where we're working with our customers and our partners very closely in not just enabling it through a system, but also surrounding it with the operating model shifts and the process changes that are required to truly transform how business gets done, right? So that's the second category.

And the third category, we are just about to sort of embark on, which is the broader orchestration scope, which goes well beyond just the Maestro platform and the data sets that reside in Maestro and go into the extended supply chain, the extended enterprise, right? So I'm very encouraged by the early results. We are working very closely on this. This is a big priority for us as a leadership team and for our customers. And what I'm finding is I've talked now in the last 8 weeks to roughly 25 customers, there's a big appetite for customers to really co-innovate. They're looking for the next wave of efficiencies. They're looking for use cases where AI can authentically create value as opposed to just following the hype. And we're very fortunate to work with many organizations that want to be leaning in and be on the front foot on that. So really encouraging on that.

On the pricing side, it was a very thoughtfully curated pricing structure where we leverage third-party experts. We benchmarked ourselves on what other companies are doing. We got some feedback and input from various existing customers. And that's what has resulted in the MAU structure. As we roll this out, by the way, the rollout of this just started last month, right, in February, we're getting additional feedback and input from our field teams, from our customers. And I fully expect that we'll go through those iterative learning cycles in evolving that pricing structure and refining it -- so it's something that works for our customers and for ourselves going forward.

Your next question comes from the line of John Shao with TD Cowen.

Razat, you mentioned semiconductor is a new win. So just curious if this industry is any different from a supply chain planning perspective. Any specific pain points you're helping them to address that's just unique to them? And how should we think about your expansion with this new vertical, as you mentioned, top 5 global foundry?

Yes. Look, the semiconductor industry has a very interesting supply chain. I've had the fortune of working with semiconductor companies for many years now. If you think about the high-tech value chain, the semiconductor companies are at sort of the top tail end of that in some ways, right? And so as shifts happen in demand in downstream demand for various products, right, whether it's chips required in powering data centers, which are on an upswing or in consumer electronics products like mobile phones and iPads and servers, et cetera, the shifts in demand downstream impact the semiconductor industry in very massive ways. That's the bull effect that how demand propagates upstream through that value chain.

So -- and then semiconductor companies are always trying to grapple with big swings in demand by the time it gets to them with the capacity that they have. And capacity is not easy to mobilize. They require heavy capital investment. So it's a unique supply chain problem. We're very familiar with it. We're very excited and very fortunate to work with several semiconductor companies, and we're seeing a significant need and demand for really allowing semiconductor companies to develop a more agile paradigm because as demand is shifting downstream, they're having to figure out how to service that demand with supply and capacity in a profitable and sensible way. And that's what Maestro is helping them do.

This will end the Q&A session. The Kinaxis team will reach out to those who did not have a chance to ask questions. I will now turn the call back to Rick Wadsworth, Vice President of Investor Relations at Kinaxis, Inc. for closing remarks. Please go ahead.

Thanks, operator. Thank you, everyone, for participating on today's call. We appreciate your questions and your ongoing interest and support of Kinaxis. As the operator mentioned, we've run out of time here, but I will reach out to folks who didn't get a chance to ask their question here, and we look forward to speaking with you all again when we report first quarter results. Bye for now.

This concludes today's call. Thank you for attending. You may now disconnect.

Good morning, and welcome to the Kinaxis Inc. Fiscal 2025 Third Quarter Results Conference Call. [Operator Instructions] I'd like to remind everyone that this call is being recorded today, Thursday, November 6, 2025.

I will now turn the call over to Rick Wadsworth, Vice President of Investor Relations at Kinaxis Inc. Please go ahead, Mr. Wadsworth.

Thanks, operator. Good morning, and welcome to the Kinaxis earnings call. Today, we will be discussing our third quarter results, which we issued after close of markets yesterday. With me on the call are Bob Courteau, Interim CEO and Chair; and Blaine Fitzgerald, our Chief Financial Officer. Some of the information discussed on this call is based on information as of today, November 6, 2025, and contains forward-looking statements that involve risks and uncertainties.

Actual results may differ materially from those set forth in such statements. For a discussion of these risks and uncertainties, you should review the forward-looking statements disclosure in the earnings press release, as well as in our SEDAR+ filings.

During this call, we will discuss IFRS results and non-IFRS financial measures, including adjusted EBITDA. A reconciliation between adjusted EBITDA and the corresponding IFRS result is available in our earnings press release and MD&A, both of which can be found on the Investor Relations section of our website, kinaxis.com and on SEDAR+. The webcast is live and being recorded for playback purposes. An archive of the webcast will be made available on the Investor Relations section of our website. Neither this call nor the webcast may be rerecorded or otherwise reproduced or distributed without written prior permission from Kinaxis.

To begin our call, Bob will discuss the highlights of our quarter and recent business developments, followed by Blaine, who will review our financial results and outlook and open the line for questions. We have a presentation to accompany today's call, which can be downloaded from the Investor Relations homepage of our website. We will let you know when to changes slides. Over to you, Bob.

Good morning. Thank you, Rick, and thanks to all of you for joining us today. We had a great third quarter. Our momentum and financial performance has once again allowed us to increase key targets for 2025. We're winning important large enterprise accounts. We're striking partnerships with leading software vendors that add value to supply chain orchestration, and we're leading the supply chain AI race, having launched fully embedded Maestro agents to our customer base. These agents enable a new revenue stream for Kinaxis and allow for faster and better outcomes for our customers.

I'll start by highlighting a few key items in our financial performance. We booked the most new business for Q3, doubling the amount from a year ago. It was the second highest total ever next to the fourth quarter of 2024 when our renewed momentum began. Quite simply, we're winning the big deals in our space. As a result, our ARR growth accelerated to 17%, and we'll exit the year with a higher ARR growth rate than we did in 2024.

Second, we grew SaaS revenue 17%, a strong result and testimony to our market-leading product, better scalability in our go-to-market team and approach and enhanced focus on our very best opportunities. Third, thanks to strong growth and efficient management of the business, adjusted EBITDA hit record levels again, and the margin was 25%, which helped us achieve our fifth consecutive quarter of Rule of 40 performance. We highly value consistency around this metric.

Slide 5, we added many exciting new customers in the quarter. Enterprise class companies continue to be the biggest cohort, and we're particularly pleased to have won multiple large enterprise accounts, a sample of which demonstrates our broad reach across vertical markets and geographies.

Renault is a French multinational automotive manufacturer founded in 1899. It designs, manufactures and sells a wide range of private and commercial vehicles under brands such as Renault, Alpine and Mobilize. This was a highly competitive win and it adds to our enviable list of household name European, North American and Asian automakers.

We continue to have success in our emerging oil and gas vertical with the addition of Repsol, headquartered in Spain. Repsol is a multi-energy company employing 25,000 people in over 20 countries and serving 24 million customers. We have also had successful deployments at ExxonMobil, Castrol and others. So, we can't help but be optimistic about this market.

In our industrial manufacturing market, we won one of the world's leading innovators in material science based in the United States. Enterprise class accounts also include the well-known high-tech brand, Seiko Epson, a Japanese multinational electronics company specializing in printers, projectors, robotics and much more. FasterPak, a U.S. based manufacturer of sustainable packaging solutions.

Even with all of the success to date, there's still lots of room for growth. There are over 14,000 prospects remaining in the vertical and geographic markets we target, and we've never been in a better position to win them. I'm also pleased that half of our gross additions to ARR came from expansion business with existing customers, an area where we have made much progress.

This success reflects both the value of our recent investments in innovative new product capabilities and validation of the tremendous value and differentiation of our core capabilities that keep supply chains transparent, agile and in sync through ongoing volatility and disruption.

Our 400-plus customers are a huge asset to Kinaxis and include some of the largest companies in the world in our vertical markets. For example, in Q3, we also secured a very significant expansion with yet another global top 5 oil and gas company. Not able to name them right now, but we're very excited about this expansion.

Another way we add value for our customers is through key partnerships that enhance supply chain orchestration. Previous this year, we announced exciting relationships with Databricks, a key part of Maestro's data fabric that helps enable AI capabilities platform-wide and with Infor, where we are now tightly integrated to their Infor Cloud suite for discrete manufacturing. And in Q3, we announced an exciting new partnership that will combine Maestro and Workday Adaptive Planning to give customers a unified view of their operational finance and people data to drive faster, more informed and confident decisions.

Finance data has always been important to Kinaxis, but this is a big opportunity to also comprehensively embed workforce data in our planning processes, too, in real time. When demand spikes, leaders can weigh margin impact, workforce needs and production options to make profitable growth decisions in minutes, not weeks.

This cross-functional scenario planning will help ensure faster pivots and stronger resilience. Partnerships are an important part of our supply chain orchestration story, and we will continue to build out relationships where it can help Kinaxis and our customers the most. Now I'm thrilled that we made our initial Maestro agents generally available to our customer base, creating the opportunity for a new revenue stream for Kinaxis, enabling faster and better outcomes for our customers.

Maestro agents enhance our capabilities, supercharge our existing product differentiation and represent a major step forwards towards a more autonomous supply chains that boost productivity, democratize access to data and generate better customer outcomes faster. We've launched the initial agents with a 30-day trial, after which customers can subscribe to consumption bundles for the full term of their contract.

Our AI strategy is simple and compelling with 3 key goals: to enhance Maestro's core capabilities, to extend our core capabilities within the enterprise and then to share supply chain data with external functions and integrate external data to achieve fully orchestrated organizational decision-making without silos. Let me talk about each of these in turn.

We've been using AI to enhance our core capabilities for some time, embedding machine learning and modules like self-healing supply chain and our AI-powered enterprise demand forecasting and advanced demand forecasting solutions to dramatically improve plan and forecast accuracy. The initial launch of our Maestro agents add to that track record and will dramatically increase user efficiency.

One example, a top 10 global pharmaceutical company used Maestro agents to boost planner productivity tenfold in its work to identify inventory risk, surfacing insights in seconds instead of minutes or hours and driving significant efficiency gains across planning processes. Additionally, one of the world's largest electronics manufacturers cut 30 hours from monthly reporting processes, and we focus that time on improved on-time delivery and higher customer satisfaction.

In short, the benefits of Maestro agents are real and are being experienced in mission-critical supply chains today with some of the biggest brands in the world. Next, we'll be using AI to extend our core capabilities with Maestro Agent Studio, which will allow customers to design and configure agents tailored to their own unique processes and business rules and help them make decisions that are critical to the enterprise.

This capability is already in limited availability to early innovators. After more experience here and working with partners, in 2026, we'll introduce a catalog of prebuilt agents from across our ecosystem that addresses common supply chain use cases and delivers even more out-of-the-box intelligence for our customers.

Finally, we'll share our supply chain data externally and also integrate more with external data by working with a network of third-party agents to enable true orchestrated organizational decision-making that operates without silos. In this phase, our orchestrator agents will resolve issues by coordinating multiple agents, both within and outside Maestro to come up with optimal solutions.

Our partnership with Workday is an excellent early example of this, where agents will exchange labor, financial and supply chain data in real time for vastly improved coordinated decision-making. Each step in our AI journey will add tremendous incremental value for supply chain practitioners and creates a significant Kinaxis opportunity.

Look, AI is the next evolution of software and a massive opportunity in the supply chain space and particularly for Kinaxis. In world-class supply chain software, complex logic modeled via tools such as heuristics, optimization and machine learning is critical for optimizing the design and execution of the supply chain to meet business objectives.

The richness and breadth of Maestro's core orchestration algorithms developed through decades of industry experience and the unique and unified proprietary data they generate will remain a massive differentiator for us even as AI becomes ubiquitous in Maestro. Amongst existing players and any potential new AI platform entrants who are offering custom one-off solutions and lack supply chain experience, we are well positioned.

We're starting our AI journey with a tremendous competitive moat. We offer proven, hardened AI-enhanced software, not a risky custom one-off project. We're already a mission-critical trusted partner to globally referenceable big brands, and we're already embedded in the daily workflow of global supply chain teams. And we're already securely integrated with other key enterprise systems to help in the orchestration of supply chains.

So overall, I'm so pleased with our momentum so far in 2025 and super excited about the future. The talent we added and the refined focus we've implemented is helping to deliver quarters consistently and to scale the company. Our product is a leader in the market, and our AI enhancements are only building on that and growing our opportunity.

We have created a tremendous environment to welcome our new CEO. The search is narrow and focused considerably, and we're confident in a great result for Kinaxis. We'll update you as we move along, and you can count on ongoing strong execution from the high-performance senior team we have in place today.

Blaine, over to you.

Thank you, Bob, and good morning. As a reminder, unless noted otherwise, all figures reported on today's call are in U.S. dollars under IFRS. If you move to Slide 8, I'm very pleased that our strong momentum continued through Q3. As Bob mentioned, this was a record-breaking third quarter for a new organic business based on average annual contract value.

It also marks our second highest quarter on record behind only Q4 2024 when the impact of our go-to-market restructuring started to take hold. Our ARR growth rate in Q3 led to 17%, both as reported and in constant currency, which is a testimony to our growing product leadership, demand in our space and our company-wide efforts to achieve scalability and focus on our very best opportunities.

Stronger-than-expected performance year-to-date enables us to increase fiscal 2025 SaaS revenue guidance for the second consecutive quarter, along with our full year adjusted EBITDA margin outlook. I'll provide details momentarily.

Our trailing 12-month free cash flow margin also remains on a strong trajectory. Briefly for the third quarter and compared to Q3 2024 results, total revenue was $134.6 million, up 11% or 9% in constant currency. As I'll speak about in a moment, our success moving subscription term license business to SaaS lowered total revenue growth by roughly 2 percentage points.

SaaS revenue was $92 million, up 17% or 15% in constant currency, thanks to ongoing strong bookings. Now with respect to subscription term license revenue, certain on-premise customers that want access to exciting new cloud-based product modules, including AI modules, opted to move forward with the renewal and expansion on our hosting offering. This shift meant that starting in Q3, associated revenue is now reported as SaaS.

Consequently, subscription term license revenue was only $79,000 in Q3. If you ignore the expansion amount, this is roughly $3 million less than had the renewal been won on-premise. Given the level of interest in some of our new cloud-only offerings, we are having more transition discussions like these. We will alert you to these types of changes, if any, after they happen.

For professional services, revenue was $37 million, up 4% and similar to last quarter. As we've discussed, there is a competitive pricing environment for professional services, but work is underway to ensure that our pricing fully reflects the premium services our team offers.

We continue to have success working with our systems integrator partners. Over the last 4 quarters, partners have led or jointly delivered more than 75% of new customer implementations won through our direct sales team. Given that ongoing success, our own professional services should be a smaller portion of total revenue in the future, while remaining a key enabler of SaaS business.

Maintenance and support revenue was $5.5 million, up 7%. Naturally, amounts recognized as maintenance and support revenue from the customers who transitioned to the cloud will be recognized as SaaS revenue ahead, though the impact is small.

Our gross profit was up 13% to $85.9 million or a 64% gross margin compared to 63% in the same quarter last year. The term license to SaaS conversion reduced current period gross margin by roughly 1 percentage point, ignoring the expansion component. Our software margin was 79%, up from 76% in Q3 last year.

Professional services gross margin was 24% compared to 32%, consistent with my comments around recent market conditions for these services. Adjusted EBITDA was up 13% to $33.9 million, a record level, reflecting our revenue growth, improving gross margin and despite the $3 million shift from subscription term license revenue to SaaS, adjusted EBITDA margin was 25%, equal to Q3 last year.

We continue to focus on profitability and gaining operating leverage as we scale. Our growth and profitability resulted in Rule of 40 performance for the fifth consecutive quarter, calculated by adding SaaS revenue growth and adjusted EBITDA margin, our usual approach. We are proud to be consistently performing at this elite level again.

Our profit in the quarter was up 150% to $16.9 million or $0.58 per diluted share and versus a profit of $6.8 million or $0.23 per diluted share a year ago. Profit benefited largely from the same factors that supported our adjusted EBITDA performance.

Cash flow from operating activities was $33.6 million, up 12% over the $29.9 million in Q3 2024. Cash, cash equivalents and short-term investments were $334.4 million, up $36 million from the $298.5 million at the end of 2024 despite being active with our NCIB program.

On Slide 9, our trailing 12-month free cash flow margin remained strong at 19.8%. The one-time payments we made in Q1 2025 relating to tax planning and a litigation settlement reduced the result by 5.4 percentage points. So the normalized result is 25.2%, and we're trending in a positive direction.

On Slide 10, I'm very pleased that our annual recurring revenue, or ARR, grew by 17% year-over-year, both as reported and in constant currency. The balance crossed a new threshold to $407 million and grew by $16 million from last quarter despite a slight foreign exchange headwind. This growth was driven by an outstanding quarter winning new business.

Notably, we matched our best quarter ever for contracts exceeding $1 million, including both new customers and expansion deals.

As Bob mentioned, we will exit 2025 with a higher ARR growth rate than we did in 2024 in constant currency terms and otherwise. The split of gross additions to ARR was 49 to 51 between new name accounts and expansion business. We remain very pleased with the healthy mix and the recent improvement in our expansion business under our new go-to-market structure. I'm particularly encouraged that applications made up the largest single component of expansion business as it demonstrates the value of our ongoing innovation.

If you move to Slide 11, our SaaS and total RPO balances remain very strong, growing to $810 million and $846 million, respectively, with 3-year CAGRs of 18% and 16%. This metric continues to highlight growth in our subscription business and our strong gross customer retention. More details on our RPO can be found in the revenue note to our financials.

On Slide 12, I'm very pleased to update our 2025 guidance. We're pleased to maintain total revenue guidance of $535 million to $550 million in both as reported and constant currency terms. Our SaaS business is extremely strong, compensating for the effects on total revenue of the professional services market dynamics and the encouraging shifts from subscription term license revenue to SaaS.

We expect to end 2025 toward the midpoint of the range for the reported results and toward the bottom end in constant currency. For the second consecutive quarter, we're excited to increase our SaaS growth guidance in both as reported and constant currency terms. We now expect full year SaaS revenue growth of 15% to 17% and 14% to 16% in constant currency.

Now thanks to the success converting on-premise business to SaaS and despite increasing customer ARR among those transitioning, we're adjusting our subscription term license revenue guidance to $15 million to $16 million. More conversions could occur this year, but there's also the possibility that new customers join us hybrid or on-premise.

Our current subscription term license revenue and total revenue guidance is based on the status quo. Ultimately, these are accounting details only. All contracts are subscription-based, and we are focused on winning and expanding with customers in a way that best suits them. After multiple quarters of better-than-expected performance and profitability, I'm pleased to increase our adjusted EBITDA margin guidance to between 24% and 26%. While our midterm aspiration has been to hit a normalized adjusted EBITDA margin of 25% by 2026, it is likely we can achieve that goal a year early.

Finally, on Slide 13, we have continued to be active on our normal course issuer bid. In the first 9 months of 2025, we repurchased approximately 467,000 common shares at an average U.S. dollar price of $130.77 for an investment of roughly $61 million. Our NCIB ended November 5, 2025. Over the full life of the plan, we purchased roughly 707,000 shares and invested approximately $92 million. We've entered into a new plan that allows us to purchase 1.4 million shares with a daily maximum of roughly 14,000 shares over a 12-month period ending November 11, 2026.

Overall, I'm very pleased with the momentum in our business. We've been successful and simultaneously improving both ARR growth and profitability in recent quarters. We remain confident with our pipeline for the rest of the year and are encouraged by our success winning key deals and our higher pipeline conversion rates under our new go-to-market structure. Our recently launched Maestro Agents unlock a new revenue stream, and we're only at the very beginning of that journey. I'm excited to see where the business can go from here.

With that, I'll turn the call back to Bob quickly before opening the lines for Q&A.

Thanks, Blaine. Just quickly, a couple of thoughts before we open the Q&A. I'm really, really pleased with the performance of the guidance and excited to raise guidance yet again. We're winning the biggest and most important deals in our markets, both against existing competitors and new entrants. Our product is already the best in our space and Maestro Agents create even more differentiation. And we've launched live solutions ahead of our competition, and we have a growing number of the world's best supply chains invested in our AI road map.

We have 14,000 more at bats with products and organizations and the AI opportunity can create even more. We have 400 of the largest companies in the world that are world-class customers, representing a massive expansion opportunity. Our GTM organization has never been in better shape to take advantage of our product superiority. And the CEO search will conclude soon. Our goal is to announce a new CEO in January. Our new CEO will be welcomed into a tremendous ready for scale organization. Thanks for your support and your ongoing interest in Kinaxis. To date, I'll turn the line over to the operator to start the Q&A session, but thanks for joining us.

[Operator Instructions] Your first question comes from the line of Thanos with BMO Capital Markets.

Regarding the Maestro agents, I realize that it's early days, but should we think about maybe the sales cycles for that upsell opportunity being a lot shorter than for a typical upsell just given the trial dynamic? What are you seeing in that regard?

Well, the way we're -- we've gone into the market is to partner with early innovators for each of the products, and that's going to continue. We're already doing some pretty interesting research and development, I call it applied research and development for future products with customers. And the interest is extremely high. Probably as we go into next year, we'll be in a place where we give some guidance on how that gets monetized, what the traction around that is. But I can tell you that the enthusiasm is high, but the way this alert is they'll have an opportunity to bring the product into their company, do a trial period and then start consuming AI solutions or performance units as they go forward.

So more to come on that as we roll out into 2026. But what I'm super excited about is the enthusiasm from some of the largest customers in the world.

Great. And then looking at the acceleration in ARR growth, to what extent has the demand backdrop is a tailwind? Are you seeing some uplift from tariff uncertainty? Or is the acceleration just far more weighted towards your own internal execution and sales investments?

The biggest change in the last year is a year ago, we were winning with the best product in the industry and a good vision for artificial intelligence. Now when we're engaged in opportunities, we're showing product and around AI. And we've used AI to really enhance the potential in core Maestro. And so, you're seeing that transition where customers want to see the product now. And probably the third part of this, because it's all integrated or unified, the ability to implement these solutions is much less complex than, for example, using third-party agents and setting up the data integration around this. This is a unified offering that customers are using today. They have products in their hands, and they can see yet again a road map that's even going to make this more exciting.

So, I think we put ourselves in a place where we have a product advantage. And then obviously, we're -- from a go-to-market perspective, we've made dramatic changes and improvements in our team. So, we're also executing on the go-to-market on these go-to-market campaigns as well in a much better way.

Next question comes from the line of Doug Taylor with Canaccord Genuity.

Congratulations on another quarter of strong bookings. I'm going to follow up on that question about the market overall right now and the purchasing behavior of your customers that push pull from being distracted by all the tariff shifts and trade challenges versus driving the need for dynamic supply chain management tools. I mean, where would you say we stand right now on that spectrum? I'm just trying to understand if you feel like this strong performance is in the face of headwinds? Or has that shifted to a tailwind now?

I think supply that chain planning with the advent of AI is becoming a core practice inside companies. It's a must-have functionality. And what we're observing is that these are tough competitions, which we're winning. Procurement is tougher than it has been before. We find ourselves in a place where people have high expectations about deployments and returns. And all those things allow us to win. I don't think that's going to change. I think what we'll see is a situation where customers are absolutely looking more and more for these type of solutions because we're in a place now where I don't think the world is going to get less complex. It doesn't mean that people are racing to buy these applications. But when they come to a conclusion that they need it inside their business, we're winning against traditional competitors and new entrants.

So, we feel good about our pipeline. We feel good about our product road map, and we love the quality of execution from the team in a world where these are heavily competed. And there's a lot of oversight right now because of the economy and the challenges on spending. So we feel like we're in a good place.

One more question for me, perhaps for Blaine. Obviously, the margin expansion momentum, particularly impressive considering the on-prem to SaaS dynamic. You've hit that 25% bogey a year early. Can you talk about the next horizon for you? And more broadly, is there a thought to optimizing for growth a bit more versus margin expansion at this stage? Any thoughts there? Or is that a question best suited for the incoming CEO?

You know what, I think the -- and I'll let Blaine jump into this one as well. This is the way I'm thinking about it is that when you're executing the way we are with a great go-to-market team, you find yourself in a place where you create optionality. We have a -- we're obviously building a pretty important investment plan for 2026. And we feel like we have room to really go after both investments that are going to improve the productivity of the organization, a lot of that using AI-based products.

We'll expand our go-to-market team. We'll start new programs, and we can do it in a way where we can continue to be a profitable company. Beyond that, we're looking at multiyear investments that are super exciting that create incremental TAM. So the way I'd say it is that we feel like we're in control of alternatives. We're not going to be just trying to optimize EBITDA margins or margins. We're not going to overweight that. We absolutely believe that there's a growth agenda in front of us, particularly now that we have our AI products in the market.

Blaine, why don't you jump in on that a little bit as well?

Yes. I mean we're in a privileged position to hit our targets a lot earlier than we were expecting. It gives us room to play in the upcoming years to figure out what type of margin do we want to balance with our growth going forward. But we still see some benefits from some opportunities in front of us, like we are going through an ongoing transition of customers from private to public cloud. That will start to eliminate, again, more and more duplicative costs going forward.

We are -- as you've seen, we've been pushing more and more to our PS organization pushing more and more of their deployments into the SI partners rather than taking it on ourselves. And that's a low-margin business. But it's something that we think we can actually increase our SaaS growth even more by working very strong with these SI partners.

I think there's some ongoing traction in higher-margin expansion business that we have involved. The fact that we're now talking about 50-50 versus, I think, even a year ago to 1.5 years ago, we were talking about 65-35 in terms of the new name logos and expansion business balance. And that balance is actually really important for us to get higher-margin business from the expansion business.

The other thing I'll point out is that we're continuing to run the business with like operating efficiency. And as much as we are loving the direction we're going with AI externally, we're also focusing on with AI internally and trying to get a lot of efficiencies by using AI within our everyday processes that we have. We're in the middle of what we call investment planning and our investment planning process looks at 2026. We're in a fortunate position again to have a little bit of room to play with our margins if we want to push that more in a direction of growth. I think 25% is now a floor that we have. And so now we just have to figure out what the next level is, which is the next milestone, which I won't say on this call yet, but I think it's going to be higher than what we're at right now.

Your next question comes from the line of Paul Treiber with RBC Capital Markets.

Just want to follow up on your comment on the shift from private cloud to public cloud. Where are you in the transition? It sounds like that transition is accelerating because of customer interest in AI. So how long do you see that being in a transition period? And remind us again of the financial impact, both to gross margins, but then also on the revenue side.

Yes. Maybe -- yes, I'll start the, it's almost 2 different questions where I'm going to answer here because our private cloud to public cloud migration, there isn't a big impact in terms of the product suite that they have available to -- on beam one or the other. We think we're much more efficient and flexible and it's easier to scale with public cloud. We are in the midst of that. As I've mentioned before, Asia Pacific is done. We are right in the belly of EMEA right now. So Europe should be done, we think, at the middle of 2026, and then it's North America to get to the end of the whole migration process.

We do believe that there's some percentage points that we will be gaining as a result of eliminating those duplicative costs. Maybe just to jump on the second part of, I think, what the question really was is, we have been seeing on-prem customers having a little bit more of a demand to move to our cloud platform. And the reason for that is we have a lot of modules that may not be available on-prem. The most recent quarter, obviously, in Q3, we had some significant movement there that we weren't expecting at the start of the year, but they reached out to us and obviously mentioned that there are some modules that they want available to them and want to move as quickly as possible.

They did that while increasing ARR. So, our total contract value increased when they moved over. But we still have a lot of upsell and cross-sell opportunities with those customers as they come on board and want to get access to those modules that maybe previously weren't available for the on-prem customers. Right now, we do have a number of customers we're talking to that are all asking for access to the AI modules. And so we're getting ready for maybe some switch ups with what we see and foresee with our subscription term license revenue line items.

And just a clarification question on the on-premise or term license to SaaS transition. On a like-for-like basis, I guess if there's no upsell, does that shift have an impact on ARR and RPO growth?

Yes. For us, I'll say in the current quarter and probably every quarter going forward, when this happens, there is an increase in ARR and RPO. In this particular quarter, we had a fairly nice sizable bump up for ARR, which we will recognize over the term of the contract versus upfront. Same thing with RPO. So we were -- we took advantage of a nice renewal that was a little bit of an upsell at the transition. And that's before the opportunity to sell those new modules that we have to those companies.

And just lastly, what do you think the time frame is typically between a customer moving from on-premise to SaaS to you realizing the upsell opportunity?

That's the -- hopefully, the million-dollar question. We are in obviously discussions with them. As we mentioned, the AI modules as an example, right now, they're on version 25 10. That's a flick of the switch right now for some of the modules that the agents, especially the work sheet agents to get access to it. But there are some on the configurable agents that we have available. Those will take a little bit longer, not much longer than what we have with flipping a switch, but there is some extra work that takes place. I think in 2026, we'll start to see some revenue coming in from those upsells and cross-sells.

Next question comes from the line of Lachlan Brown with Rothschild.

Third quarter bookings were quite strong despite being usually a seasonally low quarter. And now we're up to the fourth quarter, which is usually your highest period for bookings. I just want to check if there was any pull forward of bookings that supported the third quarter? And if you can maybe just talk to the deal pipeline that you're seeing and confidence in 4Q bookings being strong relative to prior periods.

Sure. Blaine, do you want that one?

Yes. Yes, I'll jump in. Q3, there weren't any pull-ins for Q3. It was a phenomenal quarter, and there was -- we don't talk about win rates every single quarter, but we won all the major deals. I would say when we looked at any deal that was over $1 million and the opportunity there, we won the vast majority of those. We won the most important deals that were out there. The execution of the sales organization, I applaud them with an amazing quarter. It was beyond expectations, beyond historical norms of what we've seen. And that just is a testament to the product differentiation we have and how important we are to these customers.

We're proud to be able to obviously talk about some of the logos. One of the interesting facts is that we didn't say some of the logos, and there's one particular logo, a very, very large one that we didn't say. And they said, using Kinaxis is a competitive advantage. We don't want our competitors to know that we're using it, you cannot use our logo as part of the earnings call. That's a great excuse for us to be able to say, well, yes, that's great for this company to think of us as such a strong competitive advantage. But we want to make sure that we continue to sell and get those references for Q4 and beyond.

Now Q4 bookings, we're very confident in there. There's some major large enterprises, and that's where we're starting to see a lot of traction that we didn't see in maybe '23 and '24. The large enterprise are back. They're having a lot of discussions. They like our AI road map and where we're going. And I'm confident that we're going in the right direction right now. So there's a very nice pipeline in Q4, I'll say.

Yes. The only thing I would add to that is probably the, one of the biggest changes year-over-year is, as Blaine described, the execution of our sales force and how -- when we're in an opportunity, the type of -- our ability to make sure that they understand our product advantage is really, really important. And we've really done a pretty good job of that in terms of the quality and quantity of people that can execute in a complex environment. But even beside the opportunity for AI, we have products in the market now that allow us to win with new customers but are a big part of our expansion, self-healing supply chain, AI-powered enterprise demand forecasting and advanced demand forecasting.

We're going to continue to come out with products in core Maestro that customers are going to want. And what I loved about the quarter was the ability or the stories that our customers were talking about. We had proof points about how these products and even the new AI products have realized better customer outcomes. And that's going to only reinforce our ability to be the go-to company for both traditional SaaS solutions, AI-enhanced SaaS solutions and now AI stand-alone solutions. So, we've got a really, really big expansion opportunity in front of us.

Appreciated. And more of a modeling question, but margins in professional services, we've seen a step down this year as you make more use of partner integrators and with pricing pressure in the market. But they've been ticking up in recent quarters despite the continued outsourcing. Is this AI and product enhancements beginning to reduce the cost and complexity of Maestro deployments? And how should we think about the right steady state for professional services margins going forward?

Yes. We're going to -- I'm going to definitely -- go ahead, Blaine. Go for it.

I was going to say that, obviously, we don't give guidance on professional services margins. However, we think we're on the low side of where we should be right now for those margins. It should start to tick up over the next little while and get back to what we expect is a good margin for us. We believe right now, we have premium services for professional services team, and that should give us a little more pricing power than what we're seeing right now.

The only other thing I would add is, look, as part of our SI strategy, we're definitely working hard to prioritize industries, markets and the alignment with key partners around Kinaxis because when you have the kind of win rates we're doing, these things kick off fairly important, in many cases, business transformation projects. So, core Maestro, we're going to make it easier to implement, less costly, certainty of outcomes on projects, higher value. But then what you're observing, not unlike Exxon, which has always been a great example, is that people are building a business transformation program around that. And that's why it's so exciting to some of the large SI companies.

And then part of the reason that we're going to defer a little bit on professional services is that we're starting up and have had some early success on subscription-based services. And that's a normal a more normal type of revenue stream that now gets reported by some of the AI native companies as ARR. And so, through 2026 and certainly, we should be in flight in 2027 with more subscription-based services. And we'll talk a lot more about that when we give our guidance going into in the March time frame.

Your next question comes from the line of Richard Tse with National Bank Capital Markets.

It's Mike Stevens on for Rich. Congrats on another strong quarter here. I wanted to follow up on that SI strategy you touched on and the move away from professional services a bit. I'm just wondering if that's brought on any additional challenges at a time when you're bringing a lot of new innovation and products to market. I don't know if you could discuss the dynamics there.

Well, the dynamics of core Maestro have not changed. The economics haven't changed. The opportunity is still there. We'll be working with customers and partners to serve that demand. And when you have the kind of success we've had with ARR growth, new projects, biggest customers in the world and the expansion into other parts of the company, that creates a revenue stream that we hope to encourage our SI partners to start taking one of the ideas of being an enterprise class software is to have the SIs start to take the resources where the pipeline is, and we're seeing that.

People are investing in the SI network in a way where they're going to try and get involved in some of these world-class customers, not unlike Renault, which we just closed and there's a few others. The follow-on to that is, as you go into AI, what's been pretty cool is, there's less complexity in the implementation. And the real opportunity around professional services with AI solutions is the idea that as they become more expert in using Kinaxis AI solutions, they'll be able to roll this out themselves.

But because we're integrated, like, for example, in one of the products that we now have in the market with innovation customers, we're doing something called configurable agents. And what that means is that you can actually build solutions that are unique as we described to your business processes. And there is a level of configuration complexity that's associated with that, but it's so much lower than actually implementing Kinaxis for the first time. So, what we'll see is an opportunity to work with them with this construct of subscription services where we can get them to use our solutions more broadly throughout their company. And then obviously, when you start thinking about using supply chain data more broadly throughout your organization, that also creates some opportunity for mass deployment of artificial intelligence with Maestro at the core.

So, it really is all incremental. The ability to take advantage of AI, the way we've developed them is much less complex than implementing Maestro. But by having these products, our large customers, these massive brands that are our customer base can get it more out of Maestro and they can extend that capability with our AI road map. So, it's pretty cool. It's pretty exciting. It's not dependent on a whole new professional services organization. It's extending the teams we have now in partnering with companies like Workday and the SIs to really, really dramatically extend the functionality of Maestro throughout the company. It's a pretty good business model. We're pretty excited about it.

Okay. No, that's great color. I really appreciate that. And then just on the sales and marketing spend, you're obviously seeing phenomenal returns on that spend. You've also alluded to in the call, probably continuing to invest in these opportunities. The MD&A mentioned a lot of the growth has been driven by additional spending with your partners on that go-to-market. Is that where you're seeing the best ROI on that incremental spend? And going -- looking further out, I don't know if you can give any color on how we should view that growth going forward in sales and marketing.

Look, we have 0 restraints on our spending on sales capacity. What we have is a focus on quality. We wanted to have more productive territories. And a lot of our spend last year was just around transitioning into talent and people and management that is going to make a difference. In the last, I guess, half of the year going into Q4, real focus on business development like and marketing, really, really changing the paradigm of making people aware of Kinaxis, and that's going to be critical. We are a new very experienced, highly connected BD or business development manager, which is about inside sales and really putting a privilege on visibility, marketing messaging, events in a way that now that we think we're in a place where we've created even more differentiation against the competition with our products, we got a great sales execution team.

Now we're going after the 14,000 customers out there that should be on the Kinaxis platform. But this is not straining the company from a margin perspective. This is like rigorous, high-quality ads focused on programs and people that can make difference. And a good example of that is that we did a really nice job at our Connections event in Europe. First time we did it, great turnout, great executive event, world-class. And these things are absolutely going to turn into pipeline for us.

Your next question comes from the line of Stephanie Price with CIBC.

It's Sam Schmidt on for Stephanie Price. I wanted to ask a question around RapidStart. How should we think about the mix of implementations between RapidStart and more fulsome enterprise rollouts? And what trends are you seeing in enterprise rollouts in the current supply chain environment?

Yes, why don't [indiscernible] just to give you a quick answer like, every discussion usually starts with RapidStart. People want to have their solution deployed as soon as possible. It's not even something we track anymore because everyone has taken it in some format. It gets rolled out to additional things that aren't covered under RapidStart. So, if they decide they want enterprise scheduling, that is not covered under RapidStart. If they decide that they want to use advanced demand forecasting, that's not covered under it. But generally, every conversation starts with how fast can you deploy this. Obviously, people want to get access to our solution as quickly as possible.

It is not something we track anymore because it is embedded within every single conversation that we have.

That's helpful. And then just one more for me. Can you share some commentary on net retention and how that's been trending? And maybe any relative differences between the retention for your larger clients versus the more mid-market clients? And then I'll pass the line.

Sure. Yes. So, NRR is a question we get asked quite a bit. It's one of those ones that we're getting warmer and warmer as to should we disclose it more. The truth is our expansion business continues to drive NRR upwards. After getting a quarter where we just doubled our incremental bookings over what we had in Q3 of last year, the second highest quarter ever for incremental bookings only Q4 of 2024, obviously, having a much larger portion of that coming from expansion business. It's going to drive that NRR up. And we have like one of the best-in-class gross dollar retentions, which is as strong as it's ever been. So, we're in a fortunate position, and that's why our constant currency ARR growth has reached 17%. It's actually the -- it was a 4-point increase from Q2, which is the largest quarter-over-quarter gain since ARR tracking began for us.

So, we're excited about the impact that expansion is having on our business. It's helping out with our adjusted EBITDA margins being at a very, I would say, conservative 25% at this stage, which we think is giving us even more opportunity to grow that.

That completes our Q&A session. I will now turn the call back over to Mr. Wosworz for closing remarks.

Yes. Thanks, operator. I will get back to anyone who we missed. We have a tight 9:30 stop here. So, thank you all for participating on today's call. We appreciate your questions, as always, and your ongoing interest and support of Kinaxis. We look forward to speaking with you again when we report fourth quarter results. Thank you very much, and goodbye.

Ladies and gentlemen, that concludes today's call. Thank you all for joining. You may now disconnect.