Innoviz Technologies Ltd Stock

Ladies and gentlemen, thank you for standing by, and welcome to Innoviz's Second Quarter 2026 Earnings Call. Our presentation today will be followed by a question-and-answer session. [Operator Instructions] I would now like to hand over the call to our first speaker, Ada Menaker, Head of Investor Relations. Ada, please go ahead.

Good morning. I would like to welcome you to the Innovus Technologies Second Quarter 2026 Earnings Conference Call. Joining us today are Omer Keilaf, Chief Executive Officer; and Eldar Cegla, Chief Financial Officer. I would like to remind everyone that this call is being recorded and will be available on the Investor Relations section of our website at ir.innoviz.tec. Before we begin, I would like to remind you that our discussion today will include forward-looking statements that are subject to risks and uncertainties relating to future events and the future financial performance of Innoviz. Actual results could differ materially from those anticipated in the forward-looking statements. Forward-looking statements made today speak only to our expectations as of today and we undertake no obligation to publicly update or revise them. For a discussion of some important risk factors that could cause actual results to differ materially from any forward-looking statements, please see the Risk Factors section of our Form 20-F filed with the SEC on March 26. Omer, please go ahead.

Thank you, Ada, and good morning to everyone joining us for our second quarter earnings call. The recent months have been transformative for Innoviz as we enter the defense and homeland security markets. For the past decade, we built our lighters to the toughest barrel in the industry, automotive functional safety and automotive qualification. That work established a strong technological moat and a leading position in liters for the auto market, a high-volume, long-term business.

And those same capabilities now let us take our proven LiDAR platform into defense and homeland security, which is a market with faster growth and a much higher margins. Governments are allocating tens of billions of dollars in Israel, the U.S., Europe and elsewhere to counter emerging threats, establishing what could be a multibillion dollar TAM. We are serving this market under a dedicated new brand, Persis, with our existing sensors expected to be going into culture U.S. perimeter security and unmanned ground vehicle UGV applications. We've also appointed retired Major General rava even, the former President and CEO of Rafael to our Board of Directors to advance our efforts in this market.

So far, 6 companies have publicly announced that they are engaging with us to adopt liters in defense and security applications. and we are in active conversations with dozens more. We've received our first multimillion-dollar defense order for counter UAS and perimeter security and our lighter solutions have been installed and are fully operational in several locations. We believe the defense and security business will be complementary to our automotive business driving revenue growth and gross margin improvement with ASPs that are in order of magnitude higher than in the auto space.

In automotive, growth continues. We announced the development of a LIDAR-based perception stack with a top 10 global OEM for highway driving. Mobile announced its own Robotaxi on the dry platform with 9 Innoviz lighters in every vehicle. The same platform powers the ID buzz soon to be operating in 6 cities. More SOPs are on track to follow, including BW's Level 3 and Diners Trucks Level 4 platform. Combined, our automotive programs and our new security and defense wins drove all all-time record revenues of $18.1 million in the quarter. We also strengthened our balance sheet through our recent registered direct offering with a participation from well-known institutional investors, including Neuberger which grew its existing position.

Other investors included some of the largest funds in the world. We believe that the transaction will enhance long-term value and allow us to unlock large defense agreements while supporting our automotive ramp ahead of upcoming SOPs. Looking ahead, we expect nonautomotive sales to grow from 1% of revenues in 2025 to 10% in 2016 and to 20% to 30% in 2027, expanding further after that. Including the counter UAS orders we just received, our Defense and Security backlog for 2026 is approximately halfway to our 2026 target.

For 2027 and beyond, we believe that the automotive end market will drive substantial revenue growth through unit scale and multiple programs are likely to ramp quickly starting late next year. We expect NREs to remain at their current levels. The defense and security end market will drive gross margin uplift aided by shorter cycle times with ASPs that are in order of magnitude higher than in the auto space. Together, we believe they can create a flywheel effect, which strengthening the other and adding the potential for additional end market expansion for now -- and now let's jump into the details.

The security threat landscape around the world is changing profoundly. Traditional sensing and security architectures can't keep up with autonomous systems and asymmetric tactics. Our LiDAR-based solutions change the equation in 3 specific areas: counter UAS, perimeter security and unmanned ground vehicle and robotics. Drone warfare has become 1 of the most pressing security challenges facing the world today from Ukraine to Israel and beyond.

The FBI, Deputy Director, Chris Rye, recently said that it's only a matter of time before battlefield-style drone attacks reach the U.S. Small drones fly below radar and fiber optic or autonomous control, defeat jamming and RF-based detection. Swarms and erratic flight path other well tracking systems, while birds and vegetation drive core positives. And these inexpensive drones often require expensive and comparatively slow interceptors to neutralize them. On the perimeter security side, current detection systems based on cameras and radar have inherent technological limitations, whether difficult to rain and slow or irregular movement make it hard for them to locate and identify threats. Bad actors know these weaknesses and know how to exploit them. This is the soft underbelly of perimeter defense. LiDAR-based solutions are expected to close these gaps.

They can precisely localize small drones and therefore, have the ability to support better protection of borders and critical infrastructure like airports and energy facilities.

Finally, in new JVs or robots, we can combine all of our capabilities in 1 deployment, enabling a functional safe drawn over autonomous vehicle. As governments around the world address these threats and build new capabilities, the robust 3D perception layer, we enable is gaining attention quickly here in Israel and abroad. Our new brand per brings the sensing, perception and AI expertise we built for autonomous driving to the defense and security market.

A dedicated brand under the Innoviz name lets us offer our proven LiDAR solutions with centimeter level 3D localization to government agencies, defense contractors, system integrators and security technology partners.

From our customers' experience, the traditional camera and radar-based solutions for counter UAS applications will only tell you that there is a drone present. This is not sufficient to protect an area or a critical installation. And many systems are either too large or too expensive to be relevant, especially in a moving platform. Systems supported by our LIDARs can reliably locate the threat in real time, even at low altitude and in clutter urban environments at close range. allowing those systems to accurately react while minimizing collateral damage. In perimeter security applications, we have the ability to support intrusion detection for critical infrastructure and book security. -- at distances of up to 1 kilometer.

By integrating LiDAR camera and AI, such systems will be able to detect and classify humans and vehicles in very complex environments. This includes behind trees and fences under power lines and in many other conditions where redercamera fusion solutions fall short. When it comes to solutions in the defense and security space, our customers are looking for 4 major KPIs, outdoor performance with range and resolution, resilience to occlusions such as dirt, water, bugs, et cetera, production readiness and geopolitically secure. Our LiDARs are all of the above. In particular, our resilience is a true unique proposition.

As in automotive, a LiDAR in defense applications cannot be derailed by environmental factors or obstructions. The video you've been watching showcases our lighter ability to withstand occlusions and demonstrate our readiness to serve this market today. We believe these are significant differentiators. Our work in defense and security is already starting to pay off. Last week, we announced our first large orders for a prominent defense customer, $3.5 million for several hundred LIDARs units that will be deployed in counter UAS and perimeter security. This program is in its early days, and there is potential for more significant volumes following the successful completion of the first deployment.

We are in active conversations with dozens of potential customers, many of whom have already purchased later units for testing, development and integration. We believe that some of these programs could drive partnerships and large-scale orders. Just in the past 3 months, 6 customers have announced engagement with us.

Drive Group said that they intend to integrate on LiDAR into applications such as drone localization, border security and critical infrastructure protection. This collaboration is a foundation for potential building meaningful revenue with Drive Group targeting $20 million sales opportunity by the end of 2027. We are also working with Regulus and Givon Defense to improve counter UAS performance in complex operational awareness environment. We expanded our engagement with Cognitive and are powering their new counter UAS model for advanced security platforms. Arona, part of Israel Shipyard, industry group announced a collaboration to integrate our technology into their open architecture command and control platform for counter UAS operations. Finally, prior our make had announced that they will be filling Innoviz lies across their unified platform.

As defense contractors and system integrators build out real counter UAS perimeter security and UGV capability, -- we believe Innoviz is well positioned to serve these applications. Our lenders are already operational in several locations, supporting potentially life-saving solutions Customers in the defense space need a sensor they can trust. And through synergies with our automotive business, we deliver a production-ready product that can support their mission.

Persis is off to a strong start as our teams focus on additional engagements in Israel and beyond. We believe that we are in the early stages of this business and the programs and traction we see already are very encouraging as we address what we think is a multibillion dollar TAM. Let me now update you on our automotive business. Our programs with our existing customers are on track.

The Volkswagen ID buzz is progressing on multiple fronts. It's being tested in LA, Orlando, Austin, Hamburg, Munich and Oslo with partners such as Moya, Uber and BP Moya has started the next phases of its autonomous mobility program with the ID buzz in Hamburg as part of their like project. Passengers can already book rights. During the quarter, Mobile announced its vertically integrated robotaxi business, which adds a potential of opportunity of 150,000 units to our pre-existing programs with Mobileye, Volkswagen, Diamond trucks and others.

For our Level 4 Dinara program in collaboration with Talk, we are delivering units to support milestones through SOP. We are continuing our development work with Loxo on the Level 4 autonomous delivery platform and on Level 3, we're advancing our -- on our SOPs with mobilize fail and programs such as Audi.

Globally, automakers are targeting deployment of life-saving autonomous capability in Level 3 for passenger vehicles and Level 4 for commercial vehicles. Importantly, given the increased level of regularity, scrutiny Excludent OEMs have been carefully assessing the risk of selecting or continue to use Chinese liters. There is robust interest in our technology from both platform providers and OEMs. And -- just yesterday, we announced the development of a letter-based perception stack with a top 10 global OEM. The project includes our InnovizTwo LIDARand perception capabilities powered by NVIDIA hardware. We are actively participating in multiple processes with OEMs with decisions expected to be made in the coming quarters. For programs prior to 2028 SOP, we are offering our suite of Innovest products. For programs of later SOPs, we are also offering the InnovizTwo, which was designed with a smaller form factor and reduced power consumption, making it ideally suited for deployment behind the windshield. The customer reception of the InnovizThree has been very encouraging.

Now let's talk about our outlook for 2026. We are reiterating the 26 targets. -- we said earlier this year. We expect revenues of $67 million to $73 million, driven by the ramp of later shipments and repayments. Given the timing of customer milestones and we expect the bulk of our second half revenues to come in the fourth quarter. In 2026, we expect up to 10% of our revenues to come from nonautomotive physical AI applications, largely in defense and security, and we expect Defense & Security to make up a growing portion of revenue thereafter. We target new NRE payment plans of $20 million to $30 million in addition to our existing plants. We expect to add 2 to 3 new programs this year. And now I'll turn it over to Eldar to discuss our financials.

Thank you, Omar. In the second quarter, revenues were an all-time record of $18.1 million. They reflect a significant uplift in customers NRE recognition as we meet key milestones for programs approaching SOP. Consequence, the gross margins in the quarter returned to positive levels, and we believe gross margins will be positive for the full year. supported by an increase -- increasing numbers of units being shipped to defense and security customers, continued NRE payments and the ramp of volume production for automotive.

For the quarter, cash used in operations and capital expenditure was approximately $15.2 million. For the full details of our operating expenses and stock-based compensation, please see the tables in our press release. We continue to have no long-term debt and we ended the quarter with approximately $48.5 million in cash, cash equivalents, short-term deposits and marketable securities on the balance sheet.

This does not include the additional of $30 million gross proceeds of the transaction we closed on July 29, significantly strengthening our balance sheet. The use of the proceeds will include supporting the commercialization of proceeds, our defense and security brand. We expect that the Defense and Security business will become a meaningful segment for us, driving revenues, growth with a quicker cycle as well as improving profitability. In 2027, we expect to see significant growth from LIDAR unit sales into both our focus segments, which will further accelerate into 2028. We believe the transaction we just closed will provide us with operational runway into 2028, allowing us to realize this expansion in 2027 and beyond.

Our recent performance reflects our ongoing commitment to our automotive customers. I'm also very proud of what we have been able to achieve in the Defence & Security sector in just the past few months. Our efforts are already bearing fruit, and I'm excited about the opportunity ahead. And with that, I'll turn the call back to Omer for his closing remarks.

Thank you, Eldar. Before I wrap up the call and open for Q&A, I want to recap our recent accomplishments. We are seeing strong traction in defense and security with our new Persis brand as government face new and urgent challenges and are allocating significant funds to address these threats. Our customers in this end market appreciate our automotive expertise.

They understand how our commitment to functional safety directly translates to their need for a reliable product that can withstand harsh conditions. Just last week, we announced our first multimillion dollar defense orders for counter UAS and perimeter security applications. And this engagement has the potential to grow substantially. There have been 6 partner announcements in just the past 3 months across a variety of applications and we are in conversations with dozens of additional potential customers in Israel and beyond.

Our automotive business is progressing well, and we have products launching this year to support programs set for SOP with our existing customers. We have several development projects underway and are actively competing on Level 3 and Level 4 RFIs and RFQs -- the outlook for the full year remains unchanged, and we are pleased with the operational and business momentum we've seen so far this year. Longer term, we view the automotive business and the Press business as highly synergetic, driving key elements of our long-term growth and profitability. And with that, operator, let's begin the Q&A.

[Operator Instructions] First question will be from Mark Delaney with Goldman Sachs..

Yes. Morning, afternoon. Thank you very much for the question I was hoping you could start with more context on what the defense and security bookings mean for sales from here, including how much annual revenue has now been booked when these awards fully ramp if you can speak more on your visibility and confidence as securing the rest of the awards needed for NVIS to meet its goal for non-auto revenue to be about 10% of the total in 2026.

Yes. I think that the more we are working in this field, we're getting higher and higher confidence about this market to be a very promising opportunity for us, not only for this year, but also for the coming years. Specifically on your question about the bookings. So as we said, we've already booked halfway our targets for the year. And in terms of the opportunities that we are currently in discussion with several customers, we have high confidence that we'll be able to meet our 10% target. We also said that we are expecting next year that -- the contribution of the defense and is a platform would be roughly between 20% and 30%. This is coming from the second rows of some of the activities that we are working on, which are expected to grow.

Helpful. And then on the award environment in the auto area, including personal vehicles as well as you mentioned that's ongoing. I don't know if you could share a little bit more context on how those engagements are progressing? I think you said you're most active at the moment on L4 awards, but any incremental color you can share both on the consumer vehicle front as well as commercial robotaxi type applications.

Sure. Yes. There are several activities in terms of collaboration with different OEMs, both on Level 3 and Level 4. When it comes to Level 3, primarily, this is with Innoviz behind the windshield. There are a few OEMs that are evaluating InnovizThree. I believe that 1 of them would probably also turn into a development project quite soon. And there are a few programs that I expect that at least some of them would turn into sales world. In terms of Level 4, I think InnovizTwo has already been proven as a product that has a very high fit for the automotive market, especially when it comes to durability. As I try to express every time because I think this is, I think, a hidden gem or I would say it's a topic that is not discussed enough.

When it comes to autonomous driving, the LIDAR acts as redundancy to the camera. And as you saw from the video we showed earlier, the LiDAR and the camera should never fail simultaneously -- if that's the case, then the LiDAR is not really providing redundancy. A very obvious use case for failure mode for a camera is dirt. And when a car drives over a puddle of mud, both the LiDAR and the camera fails. They cannot fail together. If they are both covered with mud, you will not have redundancy. And it means that the system becomes completely blind.

As far as we know, Innoviz is currently the only later company that is capable of offering a solution for this use case. Many companies talk about functional safety for autonomous driving. And if the safe LiDAR is unable to fulfill redundancy for the camera, it's not the case. You cannot be functional safe without the capability to operate in these environments. For this reason, any OEM that is interested and desires to have real functional safety, it needs to use a LiDAR that does not fall under those conditions. For that reason, I believe that Innovus ability to succeed in the Level 4 with this very distinctive and very important capability our ability to sustain and get more award is high.

Our product is mature. It is ready to production and several OEMs that have been using LiDARs that are coming from China in the U.S. are aware about the risk that they are taking and are looking for alternatives. Inova's set of LiDARs, which are combining of short midrange, long range and our ultra-long range is a one-stop shop that we are able to offer including our ability to close some of the gaps related to perception software or MRM systems as we are showing more and more activity with OEMs that are looking for partners that can offer everything -- for that reason, I believe that we will be able to extend our market share and have additional awards.

Very helpful. Just lastly for me was on OpEx. R&D fell meaningfully sequentially in the second quarter. Can you hear a bit more on what the driver of the reduced R&D expense was in 2Q? And any guidance on how to think about R&D going forward?

It's strongly related to reallocation of costs towards COGS once we recognize NRE. So the NREs are served by the R&D team and then -- there is some reallocation. So it's more technical than substantive. The R&D team is practically the same R&D team as it was.

Our next question is from Josh Patwa from JPMorgan. Please go ahead.

Maybe just on the automotive side. Could you give us more color on what developing a LiDAR perception stack with the top 10 automaker actually means -- what are you solving for them? And is there any way to size the revenue tied to that contract? And just as a quick follow-up on that, does does a development of a LiDAR perception stack typically sit right at the start of an automaker's program. Just wondering if you could give us more color on that. I have a quick follow-up.

So first, I want to make sure it -- clearly, we're talking about a new OEM relationship. It's not an OEM that we've been working with so far. It's -- well, it's a top 10 OEM and therefore, opens a new opportunity with the engagement of working together towards possible opportunity for serious production. -- the development work that we are doing with the OEM is -- maybe I would add here, this OEM is developing platforms that are targeting both Level 3 and Level 4. The work that we are doing right now with the OEM is dedicated on Level 3, where while on Level 4 right now, the engagement is related to -- when it comes to the Level 3 activity, there is similar to what we've done in the past with BMW.

As a reminder, BMW vehicles that are operating level are using not only our lidar. We are -- the vehicles are operating by using the LiDAR and the perception software, which means that our perception software has met the automotive requirements and are used for functional safety. As you can imagine, reaching SOP for Level 3 for the lidar alone is a very unique, I would say, capability that Innoviz has demonstrated.

As far as I know, -- we are the only -- we are also the only 1 we're able to reach SOP with automotive perception along with the lion -- the same capabilities that we offer for BMW are now being served to this new OEM. They have several KPIs that they want to assess with the LiDAR while they are preparing towards the next step where they want to start working on the series production program. This is a development stage where they are going to use the LiDAR alongside with our perception system in order to learn how to prepare the platform for the next stage of their development stage. In terms of the volume, I would say, the revenue, this is related primarily to NRE and sales of LiDARs. We did not give color on the amount. It's a development program, which we believe would tie the relationship between the teams that we later can translate to the series production.

Understood. That's very helpful. And congrats on that contract. Just as a follow-up, any feedback on how the LIDAR units are performing on the test ID buzz units? Maybe just what has surprised you to the upside or downside -- and relatedly, is there an updated timing on the SOP for the Mobileye Drive platform? And how are you and your suppliers ramping the supply chain ahead of that?

Sure. So I will start with the first question. The feedbacks are very good. We are getting very good feedback from the customer who is very pleased with the light on -- this is obviously very -- we're very happy to hear that. And this is part of -- also in discussions about the next platform. well as far as we see right now, get the feedback from the team that they are planning to use the same 9 LiDARs platform for the next rollout or I'd say, the next platform or hardware refresh, you might call it. I know that in the past, there were some discussions about possibly LIDARs would be displaced with imaging radars or so, but it's definitely not the case. They are very satisfied with the LIDAR performance and happy with the relationship as well. We have a very good relationship with Volkswagen. And I think the collaboration is very successful. We are fortunate to work with a good team as well, both from Volkswagen and Mobilite.

In terms of the time line, so there is -- there are 6 cities where the ID buzz is planned to serve by the end of this year. We are ramping up our production capacity where we expect to have a meaningful uplift already next year and then an even more significant 1 and et cetera. So eventually, there are already vehicles on the road in several cities, and we expect to have at least 6 cities by the end of this year. which will unlock the increase that is expected next year.

That's very helpful. Good luck. Thank you.

Our next question is from Colin Rusch from Oppenheimer.

I'm just curious, as you moved into a little bit more diversity of applications with the LiDAR, I'm curious about the pipeline and how many different form factors we should be thinking about the integration of the technology really being able to address. It seems like the near term or the short term or short range, LiDAR has a lot of applications. and that there are a limited number of suppliers that can actually do what you guys do for a number of these merchant boom factors.

Sure. Let me add something here. You are right that there are very few western supply lidosuppliers that can support short-range layers I think here, it's even more, I would say, differentiated. A lot of companies that have developed a short-range ladder, which basically means being able to capture a very wide field of view, -- in the automotive space, it is only needed for a very short range, 20 to 30 meters. The InnovizTwo short range is called short range because that was the gap that was needed by the OEM.

But actually, the LIDAR optical performance is identical to the ultra long range. So basically trying to say the short-range LIDAR, which enables a very wide field of view, can allow us to use the same optical performance of the ultra-long range of the 1 kilometer, you can say, in the same field view.

When it comes to the defense market and specifically come to U.S., you can imagine that the KPIs that customers are looking for is very wide field view because you're looking at a very large scene and sky, and you want to capture a very small object at several hundreds of meters. To be able to do so, you need have to have both very wide field of view, very high resolution and very high sensitivity. Innovus products, which are off the shelf, same products that we are currently offering for the ID buzz is being -- is able to do so.

So our ability to serve immediately customers that are looking to localize, find, et cetera, drones is already served by the existing product. In terms of their sensitivity on size, et cetera, of course, there is less sensitivity. But I would say with a caveat today, 1 of the biggest programs that were involved is related to counter UAS for vehicles.

One of the most challenging problems today in the world is related to drone threat on convoys and vehicles because they have no way to protect themselves. When you talk about infrastructure, you can possibly invest hundreds of thousands of dollars in infrastructure that can allow you to have some defense capabilities.

When it comes to -- you can buy hundreds of thousand dollars radars that can possibly give you some capabilities. This is a theoretical capability that is obviously very expensive and could be done the same by using our liters. This is a theoretical capability, but for mobility, for convoys is completely impossible. You cannot mount 4 huge expensive radars on every vehicle. And therefore, the advantages related for a single LiDAR that can capture can solve the problem of counter U.S. is very unique for Leidos. And therefore, it's 1 of the things that we believe would be very material to our ability to sell in this market.

And then as you see kind of the increased number of applications for the hardware, I'm curious about the need or opportunity for you guys to migrate into software in a more robust way. and what that might look like from an internal development spending perspective or if there's acquisitions that might make sense for you guys?

So let me start by saying in the automotive space, Innovus acting as a Tier 1, where we are -- we are responsible end-to-end for the LIDAR integration into the vehicle. And in some cases, also for the software. When it comes to defense and homeland security, our motivation is time to market. We are looking for ways to penetrate the market as fast as possible. For that reason, we are acting as a Tier 2, working with different system integrators that are already selling today defense systems to the end customers. This allows us to reach the market faster -- and in many cases, by the way, we are already operating in the field operationally. You can imagine that if we are already installed in villages for perimeter security, it did not require us to go through the RFI and RFQ, et cetera.

This was done by a partner that was already awarded and decided to displace the radar that they were using so far, with the LiDAR that we are offering. This gave them the opportunity to improve the customer satisfaction and while keeping the same price point. And because of the maturity of the product, it was possible. They tried -- they believed it was the right thing to do for them because they understood that while showing the capabilities they can achieve with the LiDAR, they will be able to convince many others to do the same and give them the advantages. In those kind of applications, the overall system is not only a LiDAR. It's also a fusion with a camera and control system into the control rooms, et cetera.

So our desire was not to be involved in that category. When it comes to the counter U.S., the situation is slightly different because counter U.S. is a new market. And for that reason, any any company today that wants to offer counter U.S. by using lidar and basically counter U.S. can be split to 2 parts. One is detection. When it comes to detection, you can use a camera or radar, you can possibly detect a drone even at 2 kilometers away. This gives you the ability to become aware that there is a drone. The problem with today is that the threat of FPVs, and fiber optic or autonomous drones, they are undetectable until they reach the last mile. In this category, there are no available solutions. And therefore, the companies that we work with are looking to close the gap.

Today, companies that are selling into defense they provide multiple solutions to deal with different threats. And they see the need to close the gap when it comes to FPV, which everyone is interested with. So we work with these teams.

Alongside, we are providing them not only with the LiDAR, but also with software capabilities, reminding you that we are developing the LiDAR and the smart and the smarter, the smarter that we announced beginning of the year, it's a platform which includes processing power, which can run applications on the layer itself, specifically for the drone market. We are not offering the LiDAR, only delight that we are offering as well the compute and the tracking system that can allow our customers to run faster.

So there are different ways that we can monetize not only from the LiDAR, also for the compute and the software and will continue to evolve over time. But now our focus is time to market.

There are no further questions. I'm handing the call back to Omer for closing remarks.

Thank you very much. I want to repeat and say we are in a very interesting time for the company. There is -- there are many activities related to the defense market. I'm spending much time with drones. And it's exciting to see that we are able to offer a product that is ready for such an important task. And I hope that we'll be able to show you more and more how that this market will materialize for us. Thank you very much.

Thank you.

Ladies and gentlemen, thank you for standing by, and welcome to Innoviz's First Quarter 2026 Earnings Call. [Operator Instructions] I must advise you that this call is being recorded. I'd now like to hand over the call to our first speaker, Ada Menaker, Head of Investor Relations. Ada, please go ahead.

Good morning. I would like to welcome you to the Innoviz Technologies First Quarter 2026 Earnings Conference Call. Joining us today are Omer Keilaf, Chief Executive Officer; and Eldar Cegla, Chief Financial Officer. I would like to remind everyone that this call is being recorded and will be available on the Investor Relations section of our website at ir.innoviz.tech.

Before we begin, I would like to remind you that our discussion today will include forward-looking statements that are subject to risks and uncertainties relating to future events and the future financial performance of Innoviz. Actual results could differ materially from those anticipated in the forward-looking statements. Forward-looking statements made today speak only to our expectations as of today, and we undertake no obligation to publicly update or revise them. For a discussion of some important risk factors that could cause actual results to differ materially from any forward-looking statements, please see the Risk Factors section of our Form 20-F filed with the SEC on March 4, 2026. Omer, please go ahead.

Thank you, Ada, and good morning to everyone joining us for our first quarter earnings call. In the early months of 2026, we reached critical technical milestones with our new products, made progress on existing programs and continue to engage with new automotive and nonautomotive customers. We also announced our entry into the defense and homeland security market. Some of our first quarter NRE milestones, which can be variable, shifted forward in part due to customer requests for additional content. As a result, we generated revenues of $7.1 million. We believe we will be able to recognize the delayed revenues, all of which have POs in place in the coming quarters. Our outlook for the full year remains unchanged as we continue to target revenues of $67 million to $73 million. Our long-term outlook likewise remains unchanged.

It is driven by our view that LiDAR is the most reliable method for digitizing the physical world and is indispensable to the rise of physical AI. Over the past year, we broadened our scope beyond automotive and introduced our smart products for physical AI applications. Just a few weeks ago, we announced our entry into the defense and homeland security market, a rapidly expanding and high-margin space that requires performance, reliability and resilience. We are excited about what's ahead, and we are already seeing strong traction here. Yesterday, Kela, a fast-growing defense company, announced its intent to field Innoviz LiDARs across their unified situational operations platform with the potential to scale the engagements in the coming years. I'm also happy to share that we have reached an agreement with another large holding group, which will offer Innoviz LiDARs in their defense and security solutions.

We look forward to their announcement naming Innoviz as their partner soon. These 2 opportunities with the potential to generate significant InnovizSMART sales starting this year show that we are on the way to becoming a meaningful player in the defense sector. In automotive, we are advancing towards SOPs with customers, including VW Group, Mobileye and Daimler Truck. On Wednesday, we announced an agreement with a leading autonomous driving technology company to evaluate the development of enhancement on-sensor LiDAR perception capabilities. And last week, we signed an LOI with LOXO to integrate the InnovizTwo long-range into its Level 4 digital driver platform, subject to a successful completion of testing. Global interest in both Level 4 and Level 3 automation continue to expand. And there are a number of new opportunities arising at both traditional and new automotive OEMs and in areas such as heavy equipment and agriculture.

On the technology and production front, we recently launched the InnovizTwo ultra-long range, which delivers up to 1 kilometer sensing, unlocking new capabilities across physical AI applications. The Fabrinet ramp is going well, and we are delighted to be able to tell you that we shipped a record number of units in the first quarter. Our shipments were about half of what we shipped in all of 2025, and we expect them to further accelerate in the second half of the year. In all, our products and customer pipelines are robust, and we are continuing to execute on our 2026 plan. In 2025, NREs made about approximately 70% of our revenues. Over time, we continue to expect NRE revenues to remain a stable part of our business on a dollar basis as our current programs reach SOP, and we expect to win additional programs in our existing and new end markets, including security and defense, we believe we will see a significant step-up in LiDAR revenues and gross margins.

This will likely drive meaningful growth and a shift in our revenue mix away from NREs and towards LiDAR sales. Further, we believe that sales of LiDARs in nonautomotive physical AI applications will increase from approximately 1% in revenues in 2025 to up to 10% of our revenues in 2026. We expect this trend further to accelerate in the coming years as LiDAR plays a key role across a variety of physical AI applications. And now let's jump into the details. Starting with our entry into defense and homeland security. Last month, we announced that the InnovizSMART and the newly launched InnovizTwo ultra-long range are now available for defense and security applications. This is a rapidly growing market with premium pricing and higher margins. We believe that many existing sensing solutions face limitations in this space, and we see an opportunity for our high-performance LiDAR to address gaps in detection range, weather resilience and reliability.

We're in active discussions with tens of potential customers and system integrators to provide holistic solutions, including sensors, perception and analytics. We have a dedicated team focused on expanding our position in this end market. In the defense and security space, we will focus on a broad variety of use cases. We think our LiDARs are ideally suited to applications such as perimeter intrusion and border surveillance, where they can offer reliable around-the-clock monitoring in all weather conditions. Traditional radar and camera systems can be easily evaded, especially in challenging or busy terrain and their weaknesses are well known, leaving them ripe for exploitation. Our LiDARs deliver a combination of long-range 3D detection, weather resilience and ease of deployment. In applications such as mapping and situational awareness, our dense point cloud provides rich 3D environmental data for mission planning and terrain mapping in complex environments.

Our LiDAR's fine angular resolution at long range is designed to support detection and tracking of small, fast, low-reflectivity targets that are difficult for radar and cameras to detect, adding a new layer of security when applied to drone detection. Small drones are increasingly being flown at low altitudes where radar cannot detect them, literally under the radar. LiDAR adds a level of protection that is now just starting to be understood as crucial. Finally, the InnovizSMART and the InnovizTwo ultra-long range can be deployed in autonomous and defense systems, providing the perception, accuracy and reliability required for safe navigation and optical avoidance. We believe that our automotive-grade product performance, reliability and resilience can offer game-changing capabilities to these applications. Our efforts in defense and security are already starting to pay off. We are seeing robust early traction.

Yesterday, Kela, a fast-growing Israeli defense company, announced its intent to field our LiDARs in deployments across its unified situational operations platform, including applications such as drone detection and perimeter security. Kela anticipates that the cooperation may scale in the coming years. In addition to Kela, we recently signed an agreement with a large holding group to incorporate Innoviz LiDARs into their defense and homeland security offerings. We look forward to their upcoming announcement that we will serve as their LiDAR partner. We have already received a prepayment, completed an installation and are excited about the opportunity to continue to work with this customer in the future. The intent in both of these collaborations is that our clients will utilize the combination of our long-range, short to mid-range and ultra-long range across a variety of applications.

I'm tremendously encouraged by these partnerships, which we believe demonstrate the market's need for high-performance, reliable LiDAR solution and our product suitability for these important use cases. Let me update you on our automotive business. Our programs with our existing customers are progressing well. For our Daimler Truck program in collaboration with Torc, we are delivering units to support milestones through SOP. MOIA has announced that they will deploy the VW ID Buzz on the Uber platform in Los Angeles by the end of the year as well as with Beep in Orlando. Each of these vehicles is planned to have 9 InnovizTwo LiDARs, 3 long-range and 6 short to mid-range, delivering, driving meaningful content per vehicle. We expect the vehicle to be in multiple cities around the world by the end of the year, and we were happy to hear Mobileye say a few weeks ago that their robotaxi ecosystem has progressed significantly during the first quarter.

Through the same Mobileye Drive Level 4 platform, we are supporting Holon and other customers. We are seeing strong momentum for this platform with potential for faster expansion than we expected initially. Additionally, the feedback from our customers on our sensors performance has been very positive. On Level 3, we are advancing on our SOPs with the Mobileye Chauffeur and programs such as with Audi. In addition to the advances on our existing programs, we recently entered into an agreement for a development program with a leading autonomous driving technology company to evaluate combining our LiDAR with on-sensor perception software for future autonomous vehicle programs. As autonomous vehicle programs advance towards series production, OEMs require that perception capabilities extend beyond the sensor compute stack and execute directly on the sensor.

The on-sensor approach is designed to deliver standardized safety-critical outputs that operate independently of the vehicle broader architecture. Finally, we just announced an LOI with LOXO, a Swiss pioneer in autonomous last-mile delivery. LOXO and Innoviz are currently in advanced stages of testing and evaluation of InnovizTwo long-range LiDAR for LOXO's autonomous vehicle platform. Subject to the successful completion of this process, LOXO intends to nominate Innoviz as its LiDAR supplier with multiple LiDARs per vehicle. LOXO had previously evaluated other LiDARs, and we would potentially be replacing an FMCW LiDAR in this platform. LOXO's feedback thus far has been very positive, and we are excited to be working with them on the next generation of driverless delivery vehicles.

Currently, there are several RFQs open for both Level 3 and Level 4 around the world, and we see robust interest in Level 4 from traditional and new automotive OEMs as well as industrial and agricultural customers. We are actively participating in multiple processes with a few decisions expected to be made in the second half of the year. For programs prior to 2028 SOP, we are offering our suite of InnovizTwo products. For programs with laser SOPs, we are also offering the InnovizThree, which we unveiled earlier this year and which includes an option for a color image along with the 3D data. The Holy Grail for automotive LiDAR is behind the winches installation that does not compromise vehicle design or in-carbon environment. The InnovizThree with its robust performance, smaller form factor, lower power consumption and reduced costs meets the OEMs most stringent requirements.

The reception has been outstanding, and we believe that the InnovizThree is well positioned to win a number of these upcoming programs. To support our customers' needs, we've recently launched the InnovizTwo ultra-long-range or ULR LiDAR. This device delivers up to 1 kilometer sensing and higher point cloud density resolution. It is designed to set a new standard for wide area sensing, covering terrain, borders, runways and large installations with the precision and reliability of our automotive-grade LiDAR technology. The ULR addresses critical gaps in several applications by detecting and classifying small hazards at long ranges. It lets autonomous vehicles drive faster while maintaining safety, even for heavy trucks with longer stopping distances. It can also enable perimeter security systems to identify humans, vehicles and animals over vast areas while reducing false alarms.

Additionally, its long range and high resolution can support drone detection and tracking. In all, the ULR would give customers in a wide range of industries, a tool that did not exist before and one that can perform reliably in harsh conditions. The first samples of the ULR has been delivered to key customers. Now let's talk about our outlook for '26. We are reiterating the '26 targets we set earlier this year. Driven by the ramp of LiDAR shipments and ongoing NRE payments, we expect to grow revenues year-over-year by approximately 27% to $67 million to $73 million. In 2026, we expect up to 10% of our revenues to come from nonautomotive physical AI applications, up from approximately 1% in 2025. We expect new NRE payments plan of $20 million to $30 million in addition to our existing plans, and we expect to add 2 to 3 new programs this year. And now I'll turn it over to Eldar to discuss our financials.

Thank you, Omer, and good morning, everybody. In the first quarter, revenues were $7.1 million as some of our revenues were pushed into the coming quarters due to NRE milestone variability. As Omer stated earlier, POs are in place for the delayed revenues, and we are already closing the gap. A significant contribution to revenues came from unit shipments in the quarter, which were a record high. We ended the quarter with approximately $60.1 million in cash, cash equivalents, short-term deposits and marketable securities on the balance sheet, and we continue to have no long-term debt. For the quarter, cash used in operations and capital expenditure was approximately $15.8 million, the quarter-over-quarter increase in cash used was influenced by higher working capital needs due to our ongoing production ramp at Fabrinet as well as the shift in NRE payments.

Gross margins in the quarter was approximately minus 22% due to the revenue mix as well as lower absorption of fixed costs associated with unit production. Fixed cost absorption is expected to significantly improve later this year as volumes ramp, driving uplift in gross margins. For the full details of our operating expenses and stock-based compensation, please see the tables in our press release. Despite lower revenues than expected, our full year and long-term outlook remains unchanged due to the existing customer demand as well as orders from new customers. We view LiDAR as indispensable to the rise of physical AI, and we believe the new end markets we entered into will further expand our reach in this area. With that, I'll turn the call back to Omer for his closing remarks.

Thank you, Eldar. Before I wrap up the call and open for Q&A, I want to recap our recent developments. We are very excited about our entry into the fast-growing and high-margin defense and homeland security space, where our performance and reliability offer significant advantages. This end market is undergoing rapid expansion, and there is an enormous demand for new sensing technologies. We stand ready to address this demand. We are seeing strong traction with our offerings. And in addition to our engagement with Kela, we expect another large customer to make an announcement naming us soon. Our automotive business is progressing well, and we have products launching this year to support programs set for SOPs across Level 3 and Level 4. These include programs with VW Group and other customers on the Mobileye Drive and the Chauffeur platforms as well as with Daimler Truck and Torc.

We announced a new development program to evaluate combining our LiDAR with on sensor perception software. We also announced an LOI with LOXO, where we're in advanced stages of evaluation for inclusion in their autonomous vehicle program, potentially replacing an FMCW LiDAR. We recently launched our InnovizTwo ULR LiDAR, which offers up to 1 kilometer range for a variety of applications. Our production capabilities continue to grow. And after record levels in the first quarter, we expect shipments to accelerate further. The outlook for the full year remains unchanged, and we are pleased with the operational business momentum we've seen so far this year. And with that, operator, let's begin the Q&A.

[Operator Instructions] Our first question will be from Mark Delaney with Goldman Sachs.

For the nonautomotive program that Innoviz has won, I'm hoping you can help us better understand how much revenue those programs will represent when they're fully ramped and how long that might take? And then if you could also talk about the profitability in the nonautomotive applications.

Yes, sure. Gladly. So this is based on the InnovizSMART solutions. Obviously, the ASPs are significantly higher than the ones that we are offering in the automotive space. And in terms of the ramp-up, part of the applications that we are offering today are solutions for drone detection. So really based on the application, there are -- I would say there are -- there is a high sense of urgency in some of those topics. So those could actually grow quite fast. As far as we understand today in the world, there is no viable solution for defense solution for drones.

We are working very strongly with the different teams to offer the solution to solve this very difficult problem. And of course, we are also very proud to be able to provide a solution for this topic. Over the last month or 2, I don't think there was a day I did not get a call or 3 calls a day on this topic. This is a very important element. And I think that the sense of urgency related to that could drive fast adoption. In terms of the volume, then as you can understand, there is a high demand and the ASPs are relevant to the nonautomotive space, which are high.

Understood. Secondly, I was hoping you could give more of an update on the competitive environment that Innoviz is seeing in the vehicle market. It sounds from your comments like the LOXO engagement would potentially be a competitive win from a competitor. But can you speak more broadly on what Innoviz is seen in the competitive landscape, including with the top 5 auto OEM program where you had the SoDW that was complete. I think you were waiting for feedback as of the last report. And just more broadly, either with that OEM and more generally, what Innoviz is seeing from the competitive standpoint?

Sure. So I believe that the competitive landscape has not changed. Today, there are less and less solutions offered by different companies. There is also the geopolitical discussion related to that. When it comes to a solution that can be set well within the design of the vehicle behind the windshield. I'm not familiar with a solution that is optimized as InnovizThree. I believe that on that front, we are definitely in the lead.

When it comes to robotaxis, et cetera, so there are platforms where we see the desire of some of the platforms to move away from spinners to directional sensors. And InnovizTwo is a very strong offer in terms of our performance, our readiness our full portfolio of short to mid-range, long range and now the ultra-long range. So I think that on that matter, we are also in a very strong position. There are several programs that we are competing on. I think that in all of those, we are in a very strong position, and we are waiting to see how they are making progress.

And just specifically to that top 5 auto OEM where you've had the SoDW, any more color you can share on when you hear back? And if you think you're going to ultimately get a series production award?

No, there is no update to that specific program. There are many other programs that we are making good progress with. I think that generally, Level 4 programs are moving faster than Level 3. But even on Level 3 opportunities, we see that when programs are designed for behind the windshield, this is where we're seeing a lot of interest and good feedback from customers.

Okay. And just lastly for me, you mentioned some timing elements of NRE revenue that affected 1Q. Any more color you can share around how the scope of those programs change? It sounds like you have to do more work, but the timing of when you're going to be able to recognize revenue is a little bit more extended. But if you could share a little bit more around what's going on there, that would be helpful. And just confirming, do you expect to get all of that back this year? Or would some of that be beyond '26?

First, I'll address the second question. So we expect to be able to meet all of our targets for milestones this year. This specific milestone is actually related to an ask from the OEM to pull in some of the activities that were planned for later because of the sense of urgency of the specific program that we are working on. That led to additional tasks that were added that went beyond the quarter. We have already made deliveries on that milestone, and we are working on other milestones for the rest of the year. And I believe that we'll be able to complete all of them within the year.

[Operator Instructions] Our next question is from [ Ryan Casey from AmerX ].

Great update. So I just wanted to ask a question about what we consider programs because it feels like you're announcing quite a few customer wins and opportunities. But what are we to think about in terms of program? Is that something that's very long ranging and maybe tied to automotive specifically, but can we dig into what program means in terms of your goals?

Sure. So we're referring to programs where we have an agreement, a yearly planning of ramp-up, primarily in the automotive space. We have also programs where we are working on trucks and basically vehicles that are going to be on ground, whether it also could be agriculture related or construction. Those are mostly related to automotive space.

Okay. Okay. So automotive and maybe potentially mining and agriculture, something kind of sort of vehicles and vehicle count. Great. There's been a lot of discussion about the addition of color into solutions, tell me how important color is or color is really for a specific market like smart cities or some other specific vertical in your view?

Sure. I mean sensor fusion has been used for a very long time. We introduced color in InnovizThree early this year, as you probably recall from our last earnings when we actually showed a video live from InnovizThree with a color point cloud. From our perspective, the decision to integrate color into InnovizThree comes from our desire to optimize the solution for behind the windshield integration. Currently behind the windshield are hosting cameras. And behind the windshield, it's a packaging problem. So from that regard, we decided to include color within the LiDAR. So the solution would be more integrated. In nonautomotive solutions, that level of packaging is, I would say, probably less of a concern. But of course, we can offer color within the LiDAR for other applications as well.

Okay. Terrific. And then just sort of one question, one final question about autonomous trucking. It sounds like in talking to people in the industry that there may be 2 types of trucks, sort of this concept of like a lead truck and follow trucks and that maybe their LiDAR configurations would be separate. Do you view the market as having 2 primary form factors? Or do you think most trucks will be equipped with the same LiDAR counts and technical specs, I guess?

Well, eventually, the truck programs that we're involved with are related to long-haul autonomous driving. The count of LiDARs is, of course, related to the geometry of the vehicle in terms of providing it zero blind spot configuration. Usually, there is a mix between short to mid-range, long range and ultra-long range in some cases. I think that they don't vary that much between the different players.

Okay, all right. Well, it was a great quarter with a lot of exciting update. Looking forward to more on the coming quarters.

Our next question is from Colin Rusch from Oppenheimer.

Can you please talk a little bit about the evolution of the competitive landscape? Obviously, there's a lot of innovation happening right now, and you guys have done a lot as well. I'm just curious about consolidation in the market, some of the functionality that's being rolled out, your ability to start looking at LiDAR with color integration capabilities and how you see that kind of segmentation starting to happen amongst some of the leaders in the space?

Sure. Again, as I said earlier, eventually, the LiDAR space is still evolving. And over the course of the last 10 years, you've seen LiDARs come from 50 meters to 1 kilometer and resolution in several orders of magnitude improving, cost being reduced, new features are being introduced and LiDARs are going to serve many, many sectors, whether it's automotive or defense or smart cities, ITS and basically, physical AI is overlapping everything now. LiDARs will continue to evolve. You'll see smaller form factors, you'll see cost reduction.

You'll see integration into the LiDAR with compute such as we are working now on this new program where we are adding brain into the LiDAR I think there are many directions where LiDARs can evolve into. I think that it depends on the market that you are focusing on and understanding the customer needs in each of them. Where we see -- where we saw recently a big gap was in the defense market, and this is why we believe that we can fill that gap and actually help in a way. In the automotive space, we saw an opportunity to improve our offering by including color into the LiDAR in terms of solving behind the windshield integration.

I'm sure there are many applications where sensor fusion is helpful. I can also talk about perimeter security for drones where you see sensor fusion between LiDAR and radar and sometimes LiDAR and camera. So I think we're still in the early days where you're going to see 3D sensing going to be incorporated in physical AI, physical AI is many, many things. And that will be -- you'll see different companies trying to optimize different areas. I think that so far, Innoviz has demonstrated the best optimization when it comes to the automotive space. We're starting to do so in the defense and homeland security. And obviously, we'll continue to do so on other markets as we see where we can provide our value in the best way.

Excellent. And then I guess on the cost side, as you start to see some scale and some more maturity in the space, I'm wondering about the opportunity to start driving cost structure to more optimal levels. Obviously, you guys are getting a lot of performance out of the same materials or a lot of performance improvement. I'm just curious about actual device cost reduction and the cadence of that, if there's an opportunity to accelerate it at all.

Yes, sure. I mean, look, between the first generation, even before InnovizOne, every step or every generation, we were able to produce a very significant cost reduction between InnovizOne and InnovizTwo, it was around 70% cost reduction. Between InnovizTwo and InnovizThree, there is another nice step of roughly 40% or 35%.

35%.

35%. And obviously, there is still much room to go. So when you think about LiDAR fundamentally, there's nothing expensive in the LiDAR. You're talking about an emitter, a diode, a receiver, which we are using silicon-based because we are using 905 and a processor where we developed our own ASIC. So there's nothing fundamentally expensive about LiDAR. We're still in the early days and volumes will increase, industrialization will help in terms of production and LiDARs will continue to be cheaper and continue to bring more value.

Our next question is from Jash Patwa from JPMorgan.

Congratulations on all the progress. I was wondering if you'd be able to share some early learnings from the initial ID Buzz test runs in L.A. Any insights you can provide on the role LiDAR is playing in driving decisions, specifically whether it's being used as a primary sensor or more as a backup, that would be great. And I have a follow-up.

Sure. What I can say is that the progress is really -- I mean, the feedback we hear is that it's going very well. And we're hearing, I would say, good indications on growth from this platform and things that we hope to conclude soon. There are many tests in many areas, including in Oslo in terms of tough weather conditions, snow, et cetera. We've conducted winter testing with the group. As per my understanding from Volkswagen, they see the ID Buzz as a very important asset on their future, and they talk about it on any event. Just the other day, I was in an event and the discussion on ID Buzz from the VW was the centerpiece. We are already talking about the next platform extension, et cetera. So it looks like this is a very important, I would say, part of VW plans for the future. Have I missed -- did I answer your question?

Yes. No, I think in the...

Yes. Okay. Sorry. Yes, on the regard of the LiDAR, yes, the LiDAR is a very critical -- it's a critical component in the sensor suite. Mobileye is doing the platform software, and you're probably familiar with their architecture when you have the camera and the LiDAR incorporated used as redundancy to each other. So the LiDAR is a very critical component, both the long range and the short range.

Understood. No, that's very helpful color. And I appreciate all the discussion on InnovizSMART and the end markets thereof in the prior questions. But I was curious if you are working -- currently working with any humanoid robotics developers -- it seems like that could represent another long-term volume growth opportunity. And wondering if you could share any additional color on the technical or specification requirements needed to gain traction in this market and whether there are any unique nuances compared to your core automotive or industrial use cases today?

Sure. I would say we are probably -- I think that any device with machine vision would benefit from a 3D sensor. As a company, we are trying to find the markets that are at the growth stage in terms of our ability to benefit from our mature product. Of course, we are always in discussions with next generation, next market to understand the needs and understand how potentially next generation could provide value to them. In terms of where our -- I said earlier on the call that we have over 100 open opportunities right now with the smart application, maybe 150. Those are focused on applications that are already in ramp and we -- and there is a sense of urgency around. The humanoid market is interesting, but I think it's still in a very early stage. But again, whenever that market would grow, we will -- we are keeping an eye on its needs, and we believe that we'll be able to provide it with the best solution.

There are no further questions. I'm handing the call over to Omer for closing remarks.

Thank you very much for attending our earnings. I believe that our entrance to the defense and homeland security market would allow the company to share with you more and more updates. Also on the automotive space, we're making good progress, especially when it comes to the InnovizThree. And we hope that we'll be able to share with you some of that news soon. So thank you very much, and see you next time.

Hello, everyone, and welcome to the Innoviz Physical AI webinar. Before we get started, I would like to remind you that our discussion today will include forward-looking statements that are subject to risks and uncertainties relating to future events and the future financial performance of Innoviz. Actual results could differ materially from those anticipated in the forward-looking statements.

Forward-looking statements made today speak only to our expectations as of today, and we undertake no obligation to publicly update or revise them. For a discussion of some important risk factors that could cause actual results to differ materially from any forward-looking statements, please see the Risk Factors section of our Form 20-F filed with the SEC on March 4, 2026.

So Omer, nice to be with you today. My name is David. I'm Director of Industry Solutions here at Innoviz. I'm leading our implementation of our LiDAR and non-automotive spaces and Omer.

Yes. So I'm Omer. I'm Omer Keilaf. I'm the CEO and Founder of Innoviz, and happy to have this session today.

Great. So I'm super happy to be with you. We're going to talk about your white paper that you've just recently released, and we posted a request for questions. So we will go through some of these questions today and hear your take on Physical AI.

Yes.

Great. So let's start talking about the Physical AI and the world models. Why is it so important in your view? And why did you decide to deep dive into this topic right now from Innoviz's perspective, sorry?

Yes, sure. So I think, obviously, AI has been a very big topic over the last couple of years. And every company talks about how they utilize AI. And I think it's really hard for people to really make the difference between AI that you just utilize language models, what I call -- what they call digital AI. Digital AI is where you take data such as text or images and you use language models in order to generate the next pixel, the next word and you generate a lot of content with it.

And there are many companies that have been utilizing those language models to do that. But there is a term, which is called Physical AI, which I think is very important to understand because it differentiates between the digital AI and Physical AI in a way that help us to explain what we do. Physical AI has been practiced for many years and the first application that was designed to scale was autonomous driving.

When you think about autonomous driving, it's where you take real data, unstructured mechanism where there is a car that needs to maneuver in many uncertainties in environments and roads, and you need to utilize AI in order to make sense of everything you see around you and make decisions on how to proceed. Now on top of Physical AI, which is now growing to different domains, there is another term that is important to understand, which is the world model. There are now companies that are building platforms for the next generation of Physical AI, where they intend to provide platforms that allow you to train models that would learn how our physical world behaves.

NVIDIA just released just a month ago, I think, a new platform called Cosmos, where they plan to allow developers to study and train algorithms that are meant to predict how the world will behave based on trained data. Most of the data or I would say, the platform that they are developing is based on simulations on emulations of how these environments operate. They talk about digital twin cities. When I think about digital twin cities, it's very exciting because you can create a model that allows you to monitor and experience and analyze and study and train.

But when I think about it, it makes a lot of sense to me that these simulations, I call them statues that you generate either by simulations or 3D reconstruction. When I see the capabilities that our sensors can add to create those digital twin cities, I see it as if we are bringing life to those world models. And you can use these sensors not only to utilize the application, but you can use it to study. You can create a digital twin city in real time and use it in order to really analyze how the world behaves and build those real models -- world models in a more accurate manner.

And why now? So why did you decide to deep dive into this topic now?

So autonomous driving was the first application for Physical AI. And while AI has been tremendously developed over the last few years, and there is a desire to use these capabilities on more applications. Again, coming from, for example, very standard process like a production line, right, where you have a very strict process of how things work, robots that move things from one point to another, where AI actually brings a lot of value when you have behaviors that are unstructured, where there's a lot of uncertainties.

And we live in a world where it's very hard to really predict how things will really happen. And you need to use -- if you want to really be able to automate and to optimize these applications, you need to create models that are trained by real data. And now that there is a desire to take this AI to additional applications on top of autonomous driving, it's clear that there is a missing part. There is a missing part in the story of how those applications will eventually be developed and how they will be utilized.

When I am asked about what Innoviz is doing, so usually, people -- when I tell people that we are developing a LiDAR, then the first instinct or the first reaction is, oh, I know LiDARs from autonomous driving. And it's like as if Innoviz is developing LiDARs that could only be used for one application, and it's obviously not the case. When we started to operate or offer our LiDAR to other different industries, it was very hard to even explain which industries are we working in.

And I think Physical AI is actually setting a certain umbrella, where you can explain that what Innoviz is developing is a technology that can grow Physical AI and can be an infrastructure for Physical AI. And I think those are terms. It's not like it's a new world because, as I said, autonomous driving was Physical AI, but it's a new term that allows people to understand better about the capabilities of such technologies to other industries.

Right. And then, yes, of course, perception is a bottleneck to Physical AI, right? So why do you think 3D sensing is so critical to this space? And why do you think LiDAR is the solution here?

I'll start with the fact that when -- even in autonomous driving, people refer to LiDAR as ground truth, right? Even when you are trying to train an algorithm for a vision-based system, you use LiDAR as ground truth. And that's a very strong statement because when you're trying to develop a Physical AI or world models based on inferred data or you're trying to develop your model based on simulations, obviously, you are deferring from the truth. You are reaching a bias in your model.

When you use a 3D sensor with high capabilities, you are getting an error less data, and you can create 3D models that can help you eventually get to results, which is better. So I think the affiliation to LiDAR is obvious. And I think it's also important for me as a CEO of a LiDAR company is to be able to educate investors to understand the potential, right, of the company and where things are going to be. And through this paper, I'm -- the paper is split between 2 parts. We released the first part several weeks ago. It talks about the terms of Physical AI and world models and the size of the market, et cetera.

And then in the second part, I'm trying to also try to give a certain prediction on where things would be because there are still several LiDAR companies or LiDAR technologies, less than they were in the past, but I believe there will be continuous convergence. And I'm trying to explain how LiDAR, which is going to be a very meaningful and important infrastructure of Physical AI, how it's going to shape out. And it's -- the LiDAR space have changed quite dramatically over the last 10 years. And that's part of what I'm trying to do and explain in the second part.

Right. And tell us more about the space of automotive. I mean, Innoviz has been playing very strong in this space. And how has this transformed over the past decade with respect to autonomy?

Yes. So eventually, it's a long journey, right? Over the last decade, there were probably 200 or maybe more LiDAR companies. And in the paper, I'm trying to explain how the market evolved because like any industry that went through disruption, there is a certain way these markets behave. And I'm referring to the Gartner Hype Cycle, which I appreciate it. I think it's a good way to study any industry. Gartner every year, they are publishing a report that tries to pinpoint where each industry is at in the hype cycle, understanding that it's a very traditional trend.

It's -- there's always a certain disruption. It's a disruption is an opportunity for newcomers to step in and take a big part of a very big market. And this is a case where investors jump on the opportunity because they want to put their chips on the players they believe will eventually become the meaningful players. And you can see it in many sectors, and you can see it on different reports of Gartner. But taking specifically on the automotive space, in 2015, 2016, autonomous driving was a huge hype because everybody knew that this is going to change, and it does -- it is changing.

And there were probably 200 LiDAR companies understanding that LiDAR is one of the biggest challenges of the decade. And behind it is a huge market. So billions of dollars have been invested in hundreds of companies. But as always, in this hype cycle, there is this trend where you can see wake-uping to the reality that the market eventually cannot absorb too many suppliers, especially in automotive, they tend to consolidate around very few suppliers.

So there was a race to get there. And it was -- obviously, when you see 190 companies fail, then you have 190 CEOs going around the market telling it's not my fault, it's a really bad market. It's like you have a lot of people now try to push away the failure by saying there is no market, there is no opportunity. It's not true, okay? There is a market, just there is not a market for everyone. And the automotive market have moved its targets all the time. So you have the requirements that you got for a LiDAR in 2013 is very different from the spec that you got in 2016, in 2019 and in 2026, okay?

Because your customers always become more educated about what's more important and they've experienced these programs for the first time. And as long as the requirements, the knob continue to change, to move, you've seen less and less companies that were able to meet the cut. And one of the things that I'm talking about also in this white paper is that it's going to continue. And I'm talking about the different phases of the automotive market. In the first phase, 2015, 2016, you had many start-ups with prototypes that were able to demonstrate certain capabilities, but many of them did not meet the cut.

And in the second phase, I think it was also around many situations, macro situations such as the COVID-19 and the semiconductor situation and the EV, there were many disruptions, bad disruption to the automotive space. But eventually, there were much less LiDAR companies. And some of them managed to, I would say, get an award for an OEM, even myself, -- there were times that I would say, because it was super noisy and crowded the space of the LiDAR, I would say the only real way for you, for investors to really appreciate if a LiDAR company is successful or not is whether they have or they don't have an award by an OEM.

Because in a way, you can see it as a good scrutiny by the customer that he says, okay, this is the right one I want. And today, I'm saying it's actually I was wrong. I don't think it's the right way to look at it because now when you see in perspective of the last 5 years, there were several LiDAR companies that got an award but failed. So it's not enough to get an award. And when you realize how difficult and challenging it is to get from an award to deployment, you understand that it's not enough to just flag, oh, I got one customer to get excited about what I do and believe my promises, it takes a bit more than that.

And to me, it helps to kind of push back on some of the claims that I see because you see a lot of press releases by many. And -- but the reality is slightly different. And on the white paper on the second part, at least, I'm trying to explain a little bit about those challenges, like what really is needed to get to series production, real series production, not just getting someone to be convinced. I'll pause here for questions.

Yes. So as we see the LiDAR being implemented and driven through the automotive industry, how do you see what happens in the automotive market? How do you see that impacting other nonautomotive Physical AI applications?

Yes. So again, I think that the automotive market is still setting the standards. And there is still no other market that can provide any LiDAR company any contract to volumes that are offered in the automotive space, okay, because of the size of the market. On the other hand, it's also setting a very high bar on the requirements. And those requirements, as I said, they keep moving. They are moving all the time.

One of the requirements, for example, that I'm seeing in the automotive, which I know that people are less familiar with, but I see them as very dramatic is related to the LiDAR, not only -- people know about range and about resolution and frame rate. Those are the KPIs of 2019. It's like in the old days where you would compare digital cameras by the resolution, right? That's the only way to compare. It's obviously not the case. The quality of the image is also affected by many other things.

When you talk about autonomous driving and safety, then I usually like to talk about what I call the dirty secret of the LiDAR space. When you think about an autonomous -- when I think about autonomous car, I think about a car where you have a family sitting in the back seat, and the car is driving without any ability of anyone to intervene, right? That's where we are targeting. Now the claim to fame of LiDAR in the space is that it provides redundancy to the camera, right? That's what we are all flagging.

We are providing safety by providing redundancy to all of the failures of the camera. Now where camera fails? It fails in direct sun, it fails in weather conditions, it fails in rain, droplets, right? And you'll be surprised that many LiDAR solutions, architectures are actually unable to work under those conditions. To me, it's quite surprising. But there is another element that is usually disregarded or not thought well. I talk about the dirty secret is when you think about the functional safety, it talks about the correlation of the failure mode.

If the camera fails by -- in a certain failure model, you need to prove that the other sensor does not fail simultaneously together. That's the only way to get redundancy. Now if the car drives over a paddle of mud and the mud is now thrown on the vehicle, it is very hard to prove or to even claim that both sensor will not become covered by mud. And how do you solve this problem? Because I'm not talking about an unrealistic situation because it could be mud, it could be bugs, it could be many things. I'm not familiar with any LiDAR, but ours that deals with it.

And to me, it's shocking that for a Level 4 system, we can argue about Level 3 that you have a driver that is maybe reading a book, but he can be called to reengage while the system is cleaning the car, the sensor in a few seconds. But when there is no driver at all like Level 4, to me, it is a catastrophic -- really catastrophic and alarming situation, assuming that the sensor is uncapable of dealing with these situations. The reason that Innoviz was able to solve this problem is because we already launched our first generation, InnovizOne, and we tasted the road.

And by understanding real-world problems, we knew that in the second generation, we need to bring it to a different level. So we redesigned the system. So even if you throw mud at it, you will still see it very well. And to most customers, it's like black magic and they think that we are doing things in software or AI or something, but it's not. It's really just optics. And to me, I sleep well at night when I -- seriously, when I think about I'm offering a product I believe can actually work in Level 4.

And I think that others can't. So to me, it gives confidence that I have a robust road map to actually enable these applications. I don't know how others can do that because it's a very unique design that we've done. And I don't understand how anyone can use anything other than that. So I think that just to kind of push the nail on this, there is a difference between a LiDAR for Level 2, a LiDAR for Level 3 and a LiDAR than Level 4.

And I think people are not very familiar with this differentiation because they usually think if the LiDAR has higher resolution, then it's good for Level 4 or if it has good range, then no. It's actually nothing to do with that. The only thing that differentiate between Level 2, Level 3 and Level 4 is the availability of the sensor. In Level 2, you have a driver that is -- has his eyes on the road and is ready to engage. Theoretically, you can say the LiDAR can not work basically, you can -- it's kind of like you don't -- you have the driver as a redundant sensor. Even if the LiDAR works sometimes, it's fine. It does not cause the vehicle to lose its function safety.

When you go to Level 3 and the driver doesn't look on the road any longer, you need a very robust sensor. You need a sensor that is highly available. The only cases that you are allowed that the driver is requested to reengage is if the sensor is now -- has a certain degradation. For example, if it's covered with mud, right? And then the driver is called to reengage, take the wheel and let the sensors to be clean. When you go to Level 4, it's done like -- there is no option for any degradation in a way.

So you need a highly available sensor. So the level of quality between Level 2, Level 3 and Level 4 is a quantum leap. It's like several orders of magnitude. And I believe that -- and kind of maybe closing kind of the brackets on the question, autonomous driving is setting the requirements. It's driving the volume. And eventually, it will help to companies like Innoviz to offer really the best technology to any Physical AI application because eventually, -- if you talk about security, it's also safety, right? And if you talk about logistics where you have machines that are moving in environments where there are people, it's also safety.

And certainly, intelligent traffic systems and...

And when you talk about, yes, intersections, it's also safety. So functional safety, it's not only autonomous driving and the compliance that we are having for automotive is meeting the requirements for all of those other markets. And of course, the higher performance, the higher resolution and of course, also the lower cost potential coming from the volume from automotive will eventually drive the Physical AI market.

Yes. You definitely -- you managed to connect those 2 dots, right, between the automotive and nonautomotive.

I try to remember what you really are.

So let's talk about technology. I know you're very strong in technology. And there's been a lot of excitement about different LiDAR technologies over the years. Can you talk about the evolution of the various approaches and where you think we are now?

Yes. So I love this topic because, look, at any point of time, you will have an emerging technology that is calling out to change the world and basically be the technology that the whole market would pivot to. Unfortunately, it didn't work well for many of those technologies. When I founded Innoviz on the first day I started the company, -- it was the 7th of January 2016. On the same day, there was a press release by a company called Quanergy. At the time, it was a different company. They claim that they have a solution based on a technology called OPA, optical phase array.

You can look up in the Internet. You can find the 7th of January 2016 press release on a product called S3. And there was a huge hype around OPA. It was the future of LiDAR. It was fully solid state. It was $250 can I remember they said they can see 8% at the target reflectivity at 200 meters. It's in mass production. It already had like partnerships with Mercedes. And like it was -- and I remember looking at this and I'm asking myself, what am I doing?

First day.

And it's like I'm only starting, and this company is already claiming that they are in mass production with all of the companies, and it's meeting performance that I can only dream of.

And this is a totally different technology, right?

Yes. And lucky for me, I was stubborn enough to learn a bit about the technology, what the real technology is about. And I actually came to the conclusion very quickly. I think after a week, I already -- it was clear to me the technology doesn't work. And I talked to many professors and -- like people who were actually involved in developing the technology, the technology did not work. And for 3 years, I was asked continuously by investors, how am I capable of competing with such a technology that is already in mass production. And I was really confused like seriously, do your due diligence. What are you talking about? The technology does not work.

And obviously, that product never came to life, even though they raised a lot of money and this had never really reached the public. And after that, there was a different type. It was 1550. I remember 5 years ago, I was asked daily 905 can ever compete with 15 50 nanometer. And like I said, I'm technology-driven. I go into the details, and I couldn't understand how people could really be that confused. And I just didn't know other than giving evidence by look at my product, look at the competing product and make your own assessment. Put aside all of I'm saying about the technology.

And now there is a new hype, right? There is always a new hype. And the problem is that people don't really spend enough time to understand the differentiation of the technology. And now in essence, automotive is a very difficult market. The requirements are very high. And as I said earlier, the more you turn the knob, you will leave less margins, less capable of technologies. In 2016, due to the hype, any way you can imagine developing a LiDAR, you would find a company trying to do it for LiDARs and raising a lot of money around it.

And there are really very research-driven, interesting ways to look at it, but they are not -- they have nothing to do with this capability with the requirements. And I always tell people like just see the product, see the size of the product, see the performance of the product, see the power consumption of the product. These are things that other companies don't really show. I tend to show real footage and videos of our point cloud because I think it's really the only way -- that's my product. I need to show it, right? That's the only way for me to give confidence to investors and customers to really evaluate.

Like I can always say, I'm the best, I'm the best I'm the best. But look, here's my product. And when I see others not showing their product, they -- and I see them showing videos that are processed, which I have a very sharp high to see when someone is lying about the data they are showing. To me, it's the best evidence that they just don't have anything to really to show. Now -- now the automotive market is going into a new phase. I call it Phase 3. And I'm talking about where I believe eventually the market will consolidate to.

And look, I was saying the OEMs have always increased their demand. They want it smaller, cheaper, et cetera. And there were different types of installations, green installation, roof installation. They've always hated those options. They didn't -- they always wanted to put it behind the windshield because aesthetically, it looks the best.

The problem was that in order to bring it behind the windshield, you need to have a very small device because there is no room in that area. You have very small area. It takes all of the flux from the sun. So it needs to be consuming significantly less power consumption than the solutions that were available.

And you need much higher performance because you need to overcome the tenuation you get from the window. So those extra requirements probably 5 years ago would kill anyone ever able to offer something. So they were willing to compromise, put it in the grill, put it -- sorry, on the roof, but the holy grail was always behind the windshield. And I think today, now stepping into our third generation, we can benefit from the fruits of our work that we've done with InnovizOne, reaching Level 3 to the road and InnovizTwo, it's a product that is going to series production end of the year with Volkswagen, Level 4 gives us a very robust baseline that allowed us to take another step and develop InnovizThree, which is -- you can compare it to InnovizTwo, right?

It's just totally incredible the size reduction.

It really is a very small product. Now I believe that this phase has many implications. One, I think it will stop the madness. Even for us, moving from one generation to another requires a lot of effort. And in terms of scale, you want to stabilize. You want to keep in one -- have a design that...

Not having to reinvent the wheel every time.

Now because of the desire of the OEMs to move to behind the windshield, I believe that it will stay there. It will no longer move from the grill to the roof behind the windshield, I don't think it will move to behind the seat or something. I really hope so. But I think that this is where the market will eventually converge to. And I understand that also these extra demands would likely to move -- to live in the history of the LiDAR space, more companies that will not be able to meet it because their solutions are too big, they consume too much power and their performance is not good enough.

So I think that this is a good reason, at least for me to believe that the LiDAR space is going to even further decrease. And I think that those technologies, emerging technologies like OPA, 1550 and FMCW, those are all technologies that are not a good fit for the automotive. And the only technology that has a sufficient capability in terms of volume, in price, in performance, in power consumption, the only technology that has managed to do so is time-of-flight 905 nanometer. And this is how -- this is -- these are the lenses I wear when I really look on what's my competition.

Great. Actually, that's a great step to talk about the competition and how do you see the landscape -- the competition landscape today?

Okay. So after we -- again, so I tried to put the different other companies under the different buckets of which are the technology they are using. And to me, it's clear that the technology of 905 time-of-flight is the right one for automotive. And under those glasses or lenses, the competition landscape look very different. And I'm talking about automotive. I'm not talking about nonautomotive. In the nonautomotive, you have many solutions that were possibly not good enough for automotive. So they started to develop a certain other applications. But when I kind of put it down on like who are the sensors that are offered today with time-of-flight 905 in automotive, it's in the West, it's primarily us and Valeo.

And then you have the Chinese sensors, right? And the Chinese vendors, they've -- I think they went through all of the solutions. They've learned very well from many suppliers on how to do -- how to bring up LiDARs. They've benefited tremendously by the fact that, one, the LiDAR is a strategic technology by the government of China and got a lot of funding. It's because the new electric vehicles companies that had to leapfrog into the market and compete with the Western market, they had to bring software that was premature and make it more robust by using L2 with LiDARs.

And that's the main reason why L2 in China was really flourishing and provided a lot of business to the Chinese market. There is a different problem where all of those cars are sold at a loss, but put that aside, it helped the ecosystem to develop. Now there is -- there are several acts now in the U.S. about the use of LiDARs from other countries, from China due to national security. And you can already see 2 acts that are being pursued. One is the LiDAR Safe Act. And there is a new act just came a few days ago from the DoT.

And the reason is because eventually, a LiDAR is a mapping tool. And going back to the Physical AI, LiDAR is going to be the infrastructure for the perception of the future AI -- Physical AI. You will have LiDARs not only in cars, you will have LiDARs in the infrastructure, in security borders, it's going to be in robotics, in drones. Eventually, LiDAR, which is a 3D sensor is going to displace or added to any 2D sensor. In any point of perception, you will eventually have a 3D sensor. And the richness of the data and the ability to create those twin cities digital twin cities and live digital twin cities, it obviously creates a lot of sensitive information.

And from that perspective, I believe -- I cannot predict, but I believe that the market will stay split between LiDARs that are offered by Western suppliers and Chinese suppliers to be operated in China. And so when I kind of nail down this competition, you can see that eventually, there is not a lot of competition. Of course, there are the emerging technology, but they are likely, in my point of view, not to be good enough for the automotive space.

Yes. So I think it's almost time to start wrapping up. Considering everything we've discussed so far about the need for perception, the requirements in the automotive space and LiDAR technology, can you try and tie it all together and tell us how you think Innoviz is positioned in the market right now?

Yes. Well, look, eventually, it's a long journey. We are developing a new ecosystem, okay? LiDAR is going to be a dominant sensor in the future. When you look in the white paper, I try to estimate the size of the market, the TAM, the total addressable market for LiDARs. Now the obvious one where usually you'll find a lot of coverage is analysts talk about the TAM of LiDARs in autonomous driving because it's -- as I said, it's like the obvious almost only application for LiDARs. And there were many studies around it, and it's a market of its own. And those figures talk about $10 billion in the next decade.

Now the more difficult, I would say, analysis is to understand the size of the market for LiDARs in Physical AI. And here, it's more difficult because it's less discussed. People are not familiar. Most of the people are not familiar about the capabilities that LiDAR can offer. I'll give just one example. We've started to offer our LiDAR to the security market. In the security market, the dominant sensors are camera and radar. The use of radar in physical security is, to me, just -- it's hard for me to explain because it's so horrible. It just doesn't work well. But it's the only technology that is available...

That is available.

And when you see the ASPs, the average selling point of these radars, it boggles my mind, right? It's -- it could be tens of thousands of dollars and in volumes that will blow your mind. Now when we show these customers what our LiDAR is capable of in terms of range and resolution and ability of solving those very obvious problems you want to deal with in physical security, a very stupid kind of example is radar cannot see beyond the fence.

How could be that for a security system, you have a system that doesn't see beyond the fence, I don't know. But that's the reality. And now in those situations, I look on the TAM of radars. And I try to -- there is a lot of work because radars are around for a long time. And you can actually see the size of those markets already today. And if LiDAR is going to displace radar in security, which I believe will happen massively, you can actually get an estimate of what might be the size of the market for LiDARs in security.

Now I'm not saying it will displace all of the radars in those applications, but it will take a bite, a nice bite. And those markets are continuously growing. And you see the same in agriculture and in smart cities, in logistics. Eventually, in my point of view, a radar is a good technology for a space that is empty, void in air. If you want to see something in clear sky, radar is a good option. Once you talk about a complex visual scene, a radar is pretty useless because of the very lack of resolution and noise.

And LiDAR is excellent there. And if you take a LiDAR like ours, which is automotive grade resilient to dirt and can see very long ranges, we have things coming up in terms of improving our capabilities in those domains, it's actually really -- it's going to be a huge success. So I see eventually Innoviz's position in the automotive as a ground our baseline. The market will continue to consolidate. I said it's a long journey. So we are now entering the Phase III, and I expect Phase III to leave behind less companies.

And that will be our base camp from where we can start penetrating the different markets. We started with security because it's -- I see it as a premium market because it demands performance that other LiDARs cannot offer. We try to see who will compete with in the LiDAR space in security, and there's no one because no one is actually able to meet those requirements, and that leaves us a nice premium. But nothing holds us back for offering our LiDAR to other more established markets where customers are already familiar with the LiDAR space and already understand the disadvantages with the solutions they already have.

So I think that I see it as a long game. I don't check the score because the game didn't end yet. I understand that it's a long journey. You need to make bets on your strategy. We made our bet on our position in automotive, and I believe it will be in our strength in the nonautomotive. So eventually, I see Innoviz as the market leader in the future. And I expect that it will be a very fun thing to do.

Yes, moving forward. Maybe just the last question on my side is some of the proof points that you're seeing in terms of customer wins and traction in the automotive space and beyond. So you touched on that a bit, if there's anything you want to expand on that.

Sure. So right now, we are working towards the launch with Volkswagen for Level 4 with the ID.Bus. It's the first series production robotaxi in Europe by an OEM. And we are working in collaboration with Mobileye. So -- and through that relationship, we also reached a commercial agreement with Mobileye where they are using our sensors on other programs that they are involved with. So they are using the same set of sensors. We are using 9 LiDARs per vehicle in Level 4, and they're using it on other platforms.

For example, Holland. It's another company that is going to SOP also after the ID.Bus. And then we have Daimler Truck, where we are -- we've been selected for the sensors, and it's also multiple sensors around the vehicle. And we are working -- and there is a program with Audi for Level 3. And we are continuously working with the industries on the different RFIs and RFQs. I expect this year that we'll be able to get more awards either from InnovizTwo or InnovizThree, really depends on the customer. If it comes to the Windshield integration and InnovizThree, but if it's robotaxi and they want to launch tomorrow, then InnovizTwo is a great product. It's -- I think InnovizTwo is an amazing product. I think the best-in-class today. And I think InnovizThree will definitely will be a successor, a very sweet one.

Great. It's been amazing speaking to you, Omer. And I think for me, personally, one of the nice parts about selling LiDAR is initial reaction that you get showing someone for the first time a point cloud, and it's like showing them the future. And I think, yes, definitely, your piece on Physical AI definitely gives us a bit of a glimpse to the future. So it's been really great talking to you today.

Thank you.

Thanks very much for your time.

Thank you.

Ladies and gentlemen, thank you for standing by, and welcome to Innoviz' Fourth Quarter 2025 Earnings Call. [Operator Instructions] I must advise you that this call is being recorded.

I would now like to hand over the call to our first speaker, Ada Menaker, Head of Investor Relations. Please go ahead.

Good morning. I would like to welcome you to Innoviz Technologies' Fourth Quarter and Full Year 2025 Earnings Conference Call. Joining us today are Omer Keilaf, Chief Executive Officer; and Eldar Cegla, Chief Financial Officer. I would like to remind everyone that this call is being recorded and will be available on the Investor Relations section of our website at ir.innoviz.tech.

Before we begin, I would like to remind you that our discussion today will include forward-looking statements that are subject to risks and uncertainties relating to future events and the future financial performance of Innoviz. Actual results could differ materially from those anticipated in the forward-looking statements. Forward-looking statements made today speak only to our expectations as of today, and we undertake no obligation to publicly update or revise them. For a discussion of some important risk factors that could cause actual results to differ materially from any forward-looking statements, please see the Risk Factors section of our Form 20-F filed with the SEC on March 12, 2025.

Omer, please go ahead.

Thank you, Ada, and good morning to everyone joining us today on the call. 2025 was a pivotal year for Innoviz in terms of customer engagements, production readiness and end market expansion. We achieved the financial and operational goals that we set for ourselves at the start of the year, growing our market presence and strengthening our financial foundation.

Since the last earnings call, we announced that the major commercial vehicle OEM with whom we have an agreement for series production of Level 4 trucks is Daimler Truck and its subsidiary, Torc Robotics. We also announced our next generation InnovizThree with a smaller form factor and lower power consumption for behind-the-windshield integration, the holy grail for automotive applications. Combined with an RGB camera, the InnovizThree is a compact sensor fusion model that simplifies integration and deployment. The InnovizThree is also more affordable than the InnovizTwo, which increases its potential TAM. You can actually see right now, we are being filmed using our InnovizThree LiDAR. I'll tell you more about it later on.

Our InnovizSMART, which we introduced last summer for nonautomotive applications, is available for shipment, and we are seeing excellent traction with a variety of customers. We are very pleased with the inroads the InnovizSMART is making in the security market, and we recently announced that an InnovizSMART-based solution has been deployed across several sites in critical infrastructure as an off-the-shelf system comprising the LiDAR, cameras and analytics software.

At CES, we demonstrated InnovizSMARTer, integrated with NVIDIA Jetson Orin Nano to enable edge compute deployments in bandwidth constrained areas, simplified installation and cloud applications. To meet the demand of our automotive and nonautomotive customers, we have continued to ramp capacity at Fabrinet and expect production this year to be 3x to 4x higher than last year.

On the financial front, in 2025, we grew revenue to $55.1 million, more than double the level achieved last year. Our gross margin for the year was 23% versus approximately minus 5% in 2024. OpEx for the year was $80.6 million versus $100.8 million in 2024, a 20% decrease. As we kick off 2026, our NRE payments plan stand on approximately $111 million versus $80 million at the start of 2025. We've recognized approximately $45 million of revenues [ off ] these NREs agreements in 2025. We have $66 million remaining. We expect to recognize almost all of our existing NREs in 2026 and 2027. And we expect to sign additional NRE payment plans in 2026.

As our current programs reach SOPs and we win new programs across automotive and nonautomotive, we expect to see significant growth in LiDAR revenue over the coming years. Longer term, as sales of LiDARs expand, we expect them to make a growing proportion of revenues versus NREs. We believe that sales of LiDARs into the nonautomotive physical AI applications will grow from approximately 1% to up to 10% of our annual revenues, accelerating further in the coming years.

In all, we believe Innoviz is in a very strong position for 2026 and the years ahead as we expect to play a significant role in what could be one of the most important technological advances of the future. After transforming digital workflows through software and large language models, AI is moving into the physical world. It will power vehicles, robots, infrastructures and machines that must perceive, reason and act under real-world constraints and real time. This transition, often referred to as physical AI, represents one of the largest and longest duration technology opportunities over the coming decades.

Physical AI must function in safety critical environments, tolerate environmental variability and scale at infrastructure level. As a result, it requires a fundamentally different foundation with perception at it's center. Perception powers [ world ] models, models grounded not in text or images, but in physics. And they are meant to emulate complex real-world systems.

LiDAR is emerging as the most reliable method for digitizing the physical world into accurate real-time 3D representations, creating trusted world models that can drive machine decisions. Earlier this week, we published Part 1 of a white paper on the role Innoviz is playing and will continue to play in the rise of physical AI and how we bring world models to life. I invite you to read it on our website. Part 2 will be out soon. And in March, we will also host a webinar on the subject with Q&A. Please stay tuned for details.

As the need for LiDAR as part of this new phase of physical AI becomes better understood and as the technical become more stringent, many players have been driven out of the market. We expect additional fallout in the future, with the market consolidating around just a few players. Automotive OEMs need behind-the-windshield solutions with lower power and smaller form factors. Nonautomotive applications, especially in the areas of industrial and security, demand enhanced reliability and safety.

Innoviz stands ready to meet these challenging customer requirements. With the maturity and production readiness of our InnovizTwo and the smaller size, lower power consumption and lower cost of InnovizThree, we believe we are well positioned to become the world's premier large-scale supplier of [ LiDAR ] solutions, enabling autonomous driving and the rise of physical AI.

And now let's jump into the details. Starting with our trucking customer win. Back in September, we announced that we were selected for series production of Level 4 autonomous trucks by a major commercial vehicle OEM. In December, we were very pleased to be able to name the customer, which is Daimler Truck and its subsidiary, Torc Robotics. Under the terms of the engagement, Innoviz will provide multiple LiDARs per vehicle for the customer's L4 Class 8 Freightliner Cascadia platform. We have already begun shipping units to support Daimler's trucking fleet. This partnership positions Innoviz' technology as a critical component in Daimler's truck strategy to bring autonomous trucks to the market.

Deployment is planned across highway and regional routes in North America to help fleet operators improve operational efficiency and enhance road safety. Having met the requirements of one of the world's largest commercial OEMs, we believe we are well positioned to gain additional wins in the trucking space. And as we roll out new technologies, including an upcoming ultra long-range solution, we will continue to work with Daimler to explore additional opportunities based on our full portfolio of products.

The agreement with Daimler that we just discussed underscores the traction we are seeing in Level 4 applications. As we said before, the case for Level 4 has become very clear to the automakers. They see the benefit of adding content to a vehicle, eliminating the driver and deploying the vehicles in fleets.

Waymo's success in pushing others forward, and at CES, about 2/3 of the customers and potential customers we met were focused on Level 4 applications. We are working towards Level 4 SOPs with Mobileye, Volkswagen and Daimler Truck, and we believe we are the LiDAR company with the most significant Level 4 Western SOPs.

I just recently toured the VW ID. Buzz production line in Germany, and it was truly impressive. This is the first automotive series production of a Level 4 robotaxi in the world. And it was very exciting to see our suite of 9 LiDARs being installed on each vehicle as part of the automated process. We expect fleets of these vehicles in 6 cities in the U.S. and in Europe this year, targeted to ramp in the second half of the year.

We are also progressing on our Level 3 SOPs with the Mobileye Chauffeur and programs such as [ Audi ] expected in 2027. In terms of new programs, in addition to the strong interest in Level 4, we are also very excited about the increase in Level 3 activity as well as our continued work with NVIDIA. Level 3 is now viewed as a KPI for upcoming car designs. And there are multiple RFQs for programs aiming for 2028 and beyond. Many of these programs are targeting behind-the-windshield deployments. Several OEMs have recently discussed their Level 3 efforts, specifically mentioning LiDAR as a key component. With significant progress in LiDAR designs and the availability of mature technologies, automakers are exploring their options, and we are poised to compete and win on new RFQs with our solutions.

To support our customers' efforts, we've introduced the InnovizThree. Over the last 10 years, the LiDAR space went through 2 phases. And we are now entering a third phase. In the first phase, there were many players, and the devices were largely proof of concepts. In the second phase, the automotive OEMs needed a mature, durable working product, and the number of players declined. As far as we are aware, there are only 2 companies that were able to launch a Level 3 product during the second phase, and Innoviz was one of them. The time, development and effort that Innoviz invested in the first 2 phases are the foundation of the InnovizThree, designed to enable us to meet the elevated requirements of this next phase.

Here, the holy grail of automotive lighters is behind-the-windshield installation that doesn't compromise vehicle design or in-cabin environment. The InnovizThree has been designed to meet these challenges with a smaller form factor and lower power consumption. The InnovizThree also offers a lower price point. While the InnovizTwo cost approximately 70% less than the InnovizOne, the InnovizThree offers an incremental 35% cost reduction. This could make it a compelling solution for L2+ applications as well.

At CES, we even showcase the InnovizThree combined with the camera. This solution simplifies as OEM sensor integration and sensor fusion, streamlining packaging and enabling faster deployment. The LiDAR+ camera can also be used in applications such as drones, microrobotics and humanoid, further enabling physical AI.

And by the way, as I said at the first of the call, we are using InnovizThree to make this call. I think you'll agree with me that this is unlike any other LiDAR image out there. By adding color capabilities directly into our LiDAR, we are giving OEMs a cleaner, more efficient, lower-cost path to multi-sensor perception without compromising vehicle design.

While the automotive space remains our primary area of focus, let me touch on our progress with the InnovizSMART, which is now available to order and the newly announced InnovizSMARTer. The InnovizSMART is based on the InnovizTwo platform and optimized for nonautomotive applications such as security, smart city, robotics and others. One example is an InnovizSMART-based perimeter security solution which has already been deployed in several locations. This is an off-the-shelf system for protecting critical infrastructure and municipal areas. It combines our LiDARs with our partner's PTZ cameras and analytics software. Unlike radar and camera systems, the solution can detect movement behind obstacles such as trees and fences, maintains performance in harsh conditions and deliver reliable detection of slow-moving or camouflaged targets.

The InnovizSMARTer integrates InnovizSMART LiDAR with an NVIDIA Jetson Orin processor that to deliver a one-box edge solution for real-time 3D perception, enabling wireless deployment of LiDARs in bandwidth constrained environments. At CES, we showcased the InnovizSMARTer by livestreaming a point cloud of the Las Vegas Strip, which was compressed at the edge.

The video you've been seeing in the recorded output, as you can see, it flawlessly show the landmarks, people working, moving cars and even the textures of buildings. These are all great examples of what LiDAR can do in terms of helping [indiscernible], and we are seeing a lot of interest in our smart products for a variety of end markets.

Now let's talk about our outlook for 2026. Driven by ongoing NRE payments and the ramp of LiDAR shipments, we expect to grow revenues by approximately 27% to $67 million to $73 million. In 2026, we expect up to 10% of our revenues to come from nonautomotive physical AI applications, up from 1%. We expect new NRE payments plan of $20 million to $30 million in addition to our existing plans. We expect to add 2 to 3 new programs this year.

And now I will turn it over to Eldar to discuss our financials.

Thank you, Omer, and good morning, everybody. Innoviz experienced significant growth and operational momentum in 2025. Revenues were at $55.1 million, a record year for Innoviz. We ended the year with approximately $72.1 million in cash, cash equivalents, short-term deposits and marketable securities on balance sheet. And we have no long-term debt. Cash used in operation and capital expenditure in the year was approximately $49.3 million. For the quarter, cash used in operations and capital expenditure was the single digit at $7.3 million, which included proceeds from sales of machinery. This was the second quarter of a single-digit burn in the year, demonstrating our commitment to lowering cash burn over time. We believe that our strong balance sheet and continued focus on operational excellence will provide us with the runway to reach customer SOPs into 2027.

Now turning to income statement. Our 2025 revenues of $55.1 million more than doubled year-over-year, supported by NREs as well as sales of LiDAR units. Gross margins in the year was approximately 23%, an important step towards profitability. Going forward, we expect that we will continue to see quarter-to-quarter variability in margins due to the revenue mix and customer timing.

Our operating expenses in 2025 were $80.6 million, a decrease of approximately 20% from $100.8 million in 2024. This year's operating expenses included $10.7 million of share-based compensation compared to $17 million in 2024. Research and development expenses for 2025 were $56.5 million, a decrease from $73.8 million in 2024. The decrease is primarily related to the allocation of costs related to sales of NRE and to operational realignment in Q1 of 2025. The year's R&D expenses included $6.2 million of share-based compensation compared to $11.2 million in 2024.

2025 was truly a pivotal year for Innoviz, and I look forward to what is ahead as we ramp the new product and secure additional program wins across the automotive and nonautomotive space. With that, I'll turn the call back to Omer for his closing remarks.

Thank you, Eldar. Before I wrap up the call and open for Q&A, I want to recap some of our recent developments. In 2025, we reported record revenues of $55.1 million, more than twice the previous year. We improved our gross margin and reduced our cash burn. We were selected to supply LiDARs to Daimler Truck for their autonomous trucking platform and made significant progress on our L3 and L4 programs. We continue to see a lot of interest in L4 and see a step-up in engagements in Level 3.

We introduced the InnovizThree, which we believe meets the holy grail of automotive requirements for behind-the-windshield installation. We are building a strong presence in smart applications with InnovizSMART and InnovizSMARTer. 2025 was a truly pivotal year for us, and we look forward to continued momentum in 2026.

The transition to physical AI has begun, and perception is a foundational layer in bringing world models to life. Physical AI cannot tolerate ambiguity, and LiDAR is critical to the establishment of [ ground truth ]. LiDAR offers accurate, reliable data, and critically, it meets privacy requirements. We believe Innoviz is uniquely positioned at this inflection point. I look forward to telling you more about this later in March, when I will host a webinar to discuss our technology and its role in the implementation of physical AI. Please stay tuned for details.

And with that, operator, let's begin the Q&A.

[Operator Instructions] Mark Delaney with Goldman Sachs, please go ahead.

Yes. I was hoping you could give more color on the guidance for new wins in 2026? And in particular, I'm hoping for color on where you think those wins could come from and how close you think Innoviz is on converting on those new opportunities.

Yes, sure. So Mark, there are several programs that we are currently active on that are on Level 4, actually, that we expect to converge. On top of that, there are a few Level 3. So those are the ones that we are, I would say, more tangible, and we see good cadence and progress, and generally, we're in a good position for.

Other than that, there are Level 3 programs which we are competing on. And they are split between InnovizTwo and InnovizThree. The InnovizTwo is based on programs that are trying to launch earlier. They kind of give advantage to an already automotive grade product that is going to production. And there, obviously, the InnovizTwo is a very mature product that we can offer.

For those that are -- they need a product that is for behind-the-windshield, this is where we are offering the InnovizThree. And there, I believe that we are also in a good position, but those decisions probably will take a bit more time, maybe towards the second half of the year. But overall, those are the activities that we were pointing at.

And could you also speak specifically to where Innoviz stands at converting on the SODW with the top 5 auto OEM and the potential for that to convert into a series production award?

So we completed the SODW, and we're in discussion with the OEM about the next steps. It's unclear yet what is -- how it will convert and when.

Okay. And then lastly, guidance for revenue for 2026 I believe assumes that 10% of the revenue comes from the nonauto market. Could you talk about how well covered that is in terms of bookings? In other words, have you already secured the design wins and orders to support that revenue outlook outside of the auto market this year? Or is there still work to do to achieve that?

So part of it is booked through our ongoing effort in the security market. This is where we're seeing quite high demand and a good fit. We went through several RFQs competing on different opportunities and came out with the upper hand due to the very impressive performance that our LiDAR offers. While many LiDARs that are active in the nonautomotive market, they are relatively low resolution and range, and therefore, were not really suitable for that market. Our LiDAR, due to its unique high resolution and long range, we were able to unlock that market. And those are very premium market in terms of -- it's safety level applications. So basically, everywhere we're going, we see a very, I would say, good appetite for what we're showing.

We're also working on an ultra long-range LiDAR that I hope to be able to share a bit more soon. That will even take us even further in that market. And of course, we are still also in discussion with a very wide range of applications where are already being served by different LiDARs. But see the benefits of using LIDAR which is automotive grade with high resolution and resilience to dirt, et cetera.

So it's growing. It's growing fast. It's also, I would say, it's fun in a way, after working only with automotive customers, it's some -- breath of fresh air sometimes. But it's -- generally, it brings a good vibe also to the team seeing the -- really, the variety of different opportunities and the excitement that we're seeing from our customers.

Jash Patwa with JPMorgan, please go ahead.

Congratulations on all the progress this quarter. I was having a hard time distinguishing between the LiDAR and camera feeds, so appreciate that intuitive demo. I wanted to start with a high-level question on the technology landscape. With AI disintermediation risk front and center for many investors, could you share your perspective on how LiDAR technology might be insulated from or even benefit from AI advancements? Relatedly, like do you see any risk that AI-driven improvements in alternative sensing solutions could ultimately limit the longer-term TAM for automotive LiDAR? Thanks, and I have a follow up.

Sure. I'm more than happy to talk about. Physical AI was practiced already in the last 10 years when it comes to autonomous driving using LiDARs in order to practice and develop AI to allow the car drive autonomously. It is actually only in the last couple of years where AI made a lot of progress and availability to many other sectors. And what we're seeing is that while for a very long time, AI was practiced on digital content, whether it's text or images. Where the generative AI was only trying to predict the next pixel or the next word, you see a desire to go into the physical world, where you can use AI to understand the world better, to analyze it and also possibly even predict it by being able to train those world models.

The missing factor or the missing link, as I try to point that in my white paper, is related to the fact that all of those world models are based on simulation data that are also generated by AI. That creates a big problem when your AI is trained by data that is also provided by AI. You are creating a very big [ error ] that is inflated and you create a bias in your models that are targeted to create models that try to predict how the real world acts.

What we're trying to point at is that by using a high-resolution LiDAR, you can actually connect to those world models and those digital wins that companies like NVIDIA are talking about with the [ SOC ], where you connect those digital wins to life. The LiDAR will bring life to those models and will enable development of AI on the real world. And this is where we're seeing today, AI being practiced in different industries, whether it's industrial or security or maritime.

And basically, everywhere, you'll see -- in the future, you will have LiDARs that are going to be operated, whether it's outside our houses, and by cars or by infrastructure or by robots that are going to use LiDAR within our houses. So that data is going to allow AI to understand better, how the world really acts. There's obviously a lot of sensitivity when it comes to collecting all of that data. But I see the LiDAR as if we are connecting the world model to the Internet in a way that we are feeding it with real-time accurate information. And we see that more and more people are aware of AI capabilities and how it can be deployed in many applications, not only autonomous driving. And that's what we are currently working with, with different partners. And we'll elaborate more on our AMA, ask me anything session.

Awesome. I appreciate all the color there. Just as a quick follow-up. Congratulations on the Daimler Truck announcement. I think you already touched on this in your prepared remarks, but I'm curious if you could peel the onion further on why Innoviz was selected as the preferred short-range solution, but not for the long range [ of areas ]. Could you provide any feedback from the negotiation process? And were there specific technology considerations or limitations that led the OEM to pursue your dual sourcing strategy?

Sure. With the full transparency at the time that Daimler Truck were evaluating for a long range, we were not even in the process, for whatever reasons that was. And only when the short range opportunity came up, they became aware of our solution. I can share with you that the relationship is very strong, and we are currently discussing about further expansions where Innoviz technologies can benefit Daimler and Torc on their mission.

As we were mentioning earlier also, we are working on an ultra-long-range LiDAR that would actually be very efficient and valuable, not only for the security market, but also to the truck market. So this is the first -- this is only our first engagement, and I believe it will grow.

Colin Rusch with Oppenheimer, please go ahead.

As you get deeper into the physical AI space, can you talk a little bit about any sort of need to invest in incremental sensor fusion capabilities as well as functional safety and what the demand for functional safety might look like for you guys and how long you would -- it would take for you guys to bring that to market?

So actually, the requirements we're seeing from customers [ in gas ] for functional safety, they are well aligned with what we have already achieved for the automotive market. What we get people very excited about is our resilience of the sensor. The sensor -- the InnovizTwo sensor, for example, is very resilient to weather conditions and dirt. Those are the situations where an autonomous truck or car or taxi, you wouldn't want it to be in a blind spot whenever something happens, such as dirt on the window. That's a very unique proposition that Innoviz is providing. And that's part of those that want to install LiDARs in different infrastructure, they want to see available.

Other than that, as I was referring to at the beginning of the talk about the InnovizSMARTer, that's our, I would say, next-generation InnovizSMART where we embed processing power to the edge, which helps in equipping the LiDAR in different end points that allow us to [ speed ] the data with compression and connection into the cloud. Once you are able to connect the LiDAR into the cloud from different points and create a world model, it's actually quite easy to connect it to the other platforms such as the one that NVIDIA is developing in order to train your models and develop on top of it.

So we understand the requirements for that flow. We're developing the tools that are needed. It does not require changes on the LiDAR design itself. And as you saw, we are also offering a LiDAR and kind of a fusion out of the box. So basically, we have all of the design already set up for such an infrastructure.

Great. And then my follow-up is really around customer engagement. Certainly, there was an enormous amount of activity at CES. And I'm sure there's a lot of folks sampling. I just want to get a sense of the scope and scale of the customer engagement for you guys right now. Like working with the distributor is helpful, but I'm sure you've got a wide range of folks that you're engaged with directly. I just want to get a sense of how that's grown over the last year and really in the last couple of quarters from a kind of numbers perspective? Any color you can provide us in terms of the sampling activity would be helpful.

Sure. So obviously, the answer is split between automotive and nonautomotive. In the automotive market, we are well connected with all of the customers and engaged, I would say, periodically on a weekly basis with all of the customers. Most, if not all.

When it comes to the automotive, this is where we see a huge step-up in our leads and engagements, just to give you a reference. So 2 weeks ago, we were in -- we had a big conference at Innoviz, where we invited around 80 security consultants from Israel when it comes to the airports, harbors, train stations, et cetera. And we did some kind of an exposure visit where we showed them the technology. And I think we probably left that event -- only that event with tens of opportunities. The following week, we visited a defense conference and left the conference with, I think, a few tens of leads.

So this is a market where we are growing our awareness, I might say, where we are getting in touch with customers that still require some exposure to the capabilities of the technology. Right now, we feel that in the defense market, security market. We actually are already having quite nice exposure as we are getting leads already, I would say, passively and reaching out to us. We are growing our business development in the States, while we already have a nice position in Europe and Asia.

So we are growing our, I would say, footprint in this domain. I think that this is why we are expecting 10x growth between last year and this year. And I actually think it's a modest assumption on what I believe our opportunity within this market, having that we have a good product in production, automotive grade that is actually solving problems that others don't.

Itay Michaeli with TD Cowen, please go ahead.

Great. Hi, everybody. Just wanted to dig in further into the comments on increased L3 activity on Slide 9. And specifically, we've seen a few announcements where the Level 3 hardware is going to be equipped standard fit across all vehicles. I'm curious if in your discussions and your pipeline, are you seeing a similar trend there? Or is generally, Level 3 still going to be sort of at initially low attach rate and then growing from there?

No. Actually, what we're seeing -- and this is also something that -- I think it's already in Part 1, but I'm probably going to touch that more deeply on our second part of the white paper. We're going to go deeper on the Level 3 automotive competition, et cetera. So -- we -- the LiDAR space over the last 10 years went through 2 phases, where the first phase was mostly prototyping and customers were becoming educated of what they need.

In the second phase, you've seen several programs already going into production, but only actually eventually only 2 of them. I think the third phase, which we are -- that we see that we -- the automotive space is entering is where the programs are targeting higher volumes. They see that the pricing of LiDARs have come down where it can enable it. The installation behind the windshield removes one of the last frictions as far as I see it. Because I saw a lot of friction in the past where LiDARs either in the grill were not optimized in terms of the height or on the roof in terms of the design of the vehicle. And I saw back and forth between the design team and the engineering team of the car company, where they were really struggling on how to make it work across all of their models.

Being able to deploy it behind the windshield removes quite a big friction in that regard. Bringing a LiDAR to behind the windshield requires a very significant size reduction, power reduction because your -- the flux of sun that you need to absorb behind the windshield is quite high. The temperatures that you need to be operating is higher. And obviously, you need the performance that you need to offer is higher due to that innovation that is slightly expected from the window.

So that's -- I see it as another notch where the complexity, or I would say, the moving target of the LiDAR requirements is kept moving. Over the last 8 years, you've seen 200 LiDAR companies don't meet the requirements of the first phase. The last 50 didn't meet the requirements of the second phase. And now we see the third phase where the requirements are elevated again to be behind the windshield. And to be honest, I'm not familiar with any technology other than the one that we're using that is a better fit for that with some of the other technologies just are not valued for that. So I'm actually excited about behind the windshield because I know that Innoviz is able to serve that market. And I believe that we'll be able to position ourselves as the leader here.

Terrific. And as a follow-up -- and I apologize if I missed it earlier in the call on Slide 5. With the growth in non-auto LiDAR and physical AI, can you just mention how we should think about the impact to gross margins and ASPs for the company over the next few years?

Sure. I mean, obviously, those markets, just to give you some perspective, when it comes to the defense market or the security market, the technologies are priced at around $10,000 per sensor. Obviously, the sensor that we are offering is significantly better than the ones that are used today due to our ability to see beyond trees, beyond fences, small objects, and obviously offer many more features that were not even possible to even ask for.

So the ASPs in these markets are higher. Since it's related to safety, then the need is clear, of course, in the landscape of the world that we live in. So this is why we focused on those markets early on because we also saw that, that's a market that other LiDARs are challenged with because they don't meet the range, they don't meet the resolution, and that's where we can come in without too much resistance.

And of course, we can also penetrate other markets that are served today by LiDARs, such as the ITS, airports and the trains. Today, I had a discussion with someone from the team, which was talking with me about discussions with the electricity company, with the water company. I told them it's still like monopoly, like that we are starting to cover all of the infrastructure around us. It's a world of opportunities when it comes to physical AI. And what we're seeing is that the market that is today in opposed to automotive, we are not displacing the radar or the camera. We're just coming on top. This is where you see the analysis talk about $10 billion of market size in a few years. When we talk about physical AI, we are looking at the TAM of cameras and radars because we believe we can replace them. And those TAMs are quite big. Meanwhile, we are providing a better value than them.

Casey Ryan with WestPark, please go ahead.

Thank you for a really great update, Omer and Eldar. Maybe one quickly for Eldar. And maybe you said this on the call, what do we think about OpEx, kind of the run rate? Or are we sort of going to be in the same level as we move forward? Or should we expect some meaningful changes for any reason, up or down, I guess, in '26?

So till now, the company has shown its ability to be very, I would say, efficient and modest in the way it conducts itself. Going forward, I think we will continue with this method of running the company. So I'm not expecting any dramatic change in that respect.

Okay. And then more broadly, maybe Omer can talk about this, too. Does the drivetrain matter as you look at automotive and trucking? It feels like a lot of the innovation for L3, L4 robotaxis have been on EV drivetrains. I'm not sure if that matters. Maybe that's just newer designs and they're more willing to integrate new technologies. But are the opportunity sets different in sort of ICE vehicles and sort of ICE production plans?

No, I'll say this, the following. So several years ago, the OEMs when they had to pick or design their future vehicle, they don't develop it on a yearly basis. They do it on a cadence of 4 to 5 years when they set a certain design, start working on it and eventually cut out of its different brands, but eventually, the platform itself serves multiple vehicles.

Now several years ago, many of them have picked Level 3 and EV as kind of like what they need to do on their next vehicle. And in a way, I believe that the LiDAR market or the Level 3 market in the Western market was suffering due to the challenges that came up with the EV transition. And some of those platforms were delayed or even canceled. And I think that part of the reason, and I would say even my surprise, beginning of the year when we were meeting several OEMs that came up and we're talking about RFQs for Level 3, it became clear that their strategy related to EV or ICE is behind them in terms of like they've made their decisions, and that turmoil kind of settled.

And from that sense, Level 3 is back on the table because there are now, again, discussions on what exactly would be their platform. And they want to launch it because they eventually -- Level 3 was always on their map, but because of issues that they had with the platform of the EV, I think the LiDAR market was slightly delayed.

So -- on the technology part, there is no correlation between EV or ICE to a LiDAR. You can operate autonomous driving on any type of vehicle. You just need that the platform would be developed.

Got it. Okay. That's helpful. And so it sounds like '26 is setting up great for maybe a meaningful jump in terms of commercial revenues versus its percentage contribution in '25. I think in your initial comments, you said that production would double or triple, Omer? I missed that. I wanted to get...

The production is going to be up 3x to 4x. Our production site at Fabrinet is ramping up. We are prepared -- preparing towards the SOP of the Volkswagen and Mobileye, where we are expecting fleets of vehicles in 6 cities in the U.S. and Europe. On top of that, there are Mobileye, other customers that are going to follow that in terms of SOP. So definitely, our production ramp-up is going to increase our sales of LiDARs, and that would also add in ourselves in the nonauto market.

Yes. Well, that's a very exciting outlook, I think, and a great trend point. Just one last point on the NREs that you have, the 111 in total. Could you just give us a count on how many people made up that group of NRE contributors, if it was, say, if it was double digits or single digits in terms of the number of customers?

So we're currently supporting multiple programs. I'm not sure what you mean about people, but they are currently -- in parallel, we are supporting 4 or 5 programs in parallel, whether it's different programs within Volkswagen, different programs with Mobileye and Daimler Truck. So this is kind of like the number of programs that we are currently committed to and working towards an SOP.

Okay. And then last question. Of the new NRE opportunities, would any of those be outside of automotive or trucking? Do you think they could fall into the physical AI category?

I think that our assumption right now is that, that still would come from the automotive market. That's our assumption right now.

Thank you. It's a very exciting outlook for '26. So thanks for the update.

There are no further questions. I'm handing the call over to Omer for closing remarks.

So thank you very much for taking the time to listen to our end of year earnings. We are experiencing a very exciting time where we're seeing LiDARs being used on so many different opportunities. As I was saying earlier during the Q&A, the vibe within the team is very high due to, I would say, the excitement that we see in our customers. So thank you very much, and see you soon.

Thank you very much for your participation. This concludes our call. The session will now be closed.

Okay. Thank you, everyone, as we continue the conference. I'm very pleased to have with us Omer Keilaf, the Founder, CEO of Innoviz. Innoviz, a leading LiDAR player, senior may be one of only a few LiDAR players.

[indiscernible] a few, yes.

But a leading player in the field of LiDAR. So we're going to go through a series of fireside chat questions. Anyone that has questions, you can e-mail my colleague, J.R. Young, [email protected], he can ask your questions.

But I want to start, Omer, maybe you could just talk us -- zoom out and let's look at -- because Innoviz from a product perspective has been on a journey. So maybe you could just give us sort of an overview of where you've been in the last couple of years, where you are on the product road map and how everything has evolved. And I like the fact that you brought a little bit of show and tell.

Yes. Yes. Yes, so we are working very close with the car manufacturers. And we understand where they are trying to get. Level 3, highway, Level 4, robotaxis. And at every point of time, there are -- you see that different OEMs have different ideas on where the LiDAR should be mounted, whether it's in the grill, on the roof, behind the windshield, speed of the Level 3 they want to support. And I think from -- you realize that there are many perspectives that you need to embed in the sensor. I'll give you an example. When an entrepreneur decides to develop a LiDAR, the last thing that he is thinking about when LiDAR is considered one of the most challenging technologies in the world is how it acts in -- after the car bumped into a puddle of mud. You -- people are -- 5 years ago, 6 years ago, we're still focused on range, resolution and cost, but you learn that eventually the car needs to drive driverless even when that he drives over a paddle of mud and the sensor is now dirty because you realize that if it doesn't work well in those conditions, it's all meaningless, right?

It's like you've done all of this effort and developed the best technology in the world, but it only works when the car is clean. So I think one of the advantages that we had in Innoviz working with BMW, our first customer was actually seeing those, I would say, more challenging conditions. And we've baked into our second generation and our third generation, all of those learnings. And we show customers the way that our sensor is working even when we throw mud at it. I always get the question of what's the magic? Like what are you doing here that I should know? That's, by the way, a different topic is the trust that the OEMs have on LiDAR companies right now. But this is, I think, one of the key advantages that we have. We really have our scars on our backs. And we have a product that can actually work in a Level 4, Level 5 because it's a very resilient automotive grade. It meets the highest requirements of range and resolution.

Now we introduced the InnovizThree, which we just talked about in our last earnings. And you can -- I hope you can agree, it's a very small design. This is a compilation of many requirements we got for customers that once to embedded behind the windshield. This is where OEMs are now looking to deploy. Everything I can talk about LiDAR is actually driven from design of the vehicle. It's like #1 rule. The car may still look good. And for several years, the engineers were somehow able to push away the designers and tell them, yes, but it still needs to work. And putting a LiDAR behind the windshield adds 2 levels of complexities on top. And as we said, LiDARs were a challenge by itself before it -- you brought it to behind the windshield. We are at a point where our new technology, our next generation is allowing us to place it behind the windshield where other LiDARs have failed.

And I believe this will be the leading, I would say, position for the front-looking LiDAR. Of course, when you talk about Level 4, it doesn't end there. You don't have windshields around the vehicle. So even there, we have a very interesting solution, which we haven't yet talked about. So yes, we -- in a way, we are helping the OEMs to design their future vehicles based on the capabilities that we are able to show them. Because designers can imagine anything they want, right? They can, I want the LiDAR somewhere fixed like here in this size. But they can't really know if it's doable or not and whether it will meet the requirements.

So in a way, we are actually inviting OEMs to see our capabilities and design their future cars, concepts based on the capabilities that we are able to provide them. So this is a product that we've designed for Level 3 highway or front-looking sensors. But when you talk about Level 4 or Level 3 urban, which this is what would be next, where a person that buys a car doesn't want it to drive autonomously only on the highway. He wants it to drive autonomously also in other areas. But then it needs to be cheap -- sorry, affordable and designed well, right? So you cannot put 9 LiDARs in a privately owned vehicle. As much as I would love to sell 9 LiDARs per vehicle, it probably will not work, right?

Maybe in China.

Maybe in China. Yes, if it's empty, then yes. It's -- I've seen already cars where the LiDAR was actually an empty box. That was funny. Yes, it became like a luxury thing to have a LiDAR on it. But in any case, if you want to have a Level 3 urban or Level 4 in a privately owned vehicle, you cannot assume that it will be able to absorb so many sensors around it. So it's actually on us to understand those challenges and the design the future technologies of LiDARs that will solve it. It will not come from the carmakers. It will come from us. And these are the things that we are doing. So starting from LiDARs that were this big, right, to sensors that are this small and will be smaller and more affordable and better to a point that every car would have full autonomous capabilities in an affordable manner.

Okay. A lot to unpack there. So maybe we can just chip away at this. And I want to just ask on the LiDAR opportunity more broadly. I think there has been -- there was a narrative over the years that the LiDAR opportunity was really on the scaled ADAS, L2+, L3, what have you, as an advanced driver assist feature. Doesn't seem like that's played out in the industry as broadly. And now it seems like we're pushing more toward really the LiDAR opportunity being on L4 fully autonomous, which is getting sparked interest. So maybe you could just walk us through the LiDAR opportunity. Where is the market emphasis and/or your emphasis from a sort of L2+ scaled ADAS versus L4?

Sure. So I actually like to point at China when -- as kind of a crystal ball. right? Because when you see how the industry in China has evolved to host any -- many LiDARs on cars, I can see how that can be a good way to think how the future might look like in other areas around the world. Now part of the reason that LiDARs were used in China was because they had a premature software, and they use LiDARs to overcome the challenges of using just a camera based for a Level 2 system. And they use the LiDAR to add safety at a shorter time with the software which is possibly more mediocre. Now the market is shifting towards Level 3 in China, and I think that will also push the Western OEM. Level 4, I actually see it as the reason -- I think there is a gold rush right now. This is what I see, and I'll explain where I'm -- how I -- why I think it's like that.

Eventually, in any big city, you have a certain limit of number of cars that are -- that will be allowed to give service because of congestion. If any car -- if any company would now push in hundreds of thousands of cars, nobody will make money. The car -- the traffic would be horrible and nobody would allow it. So there will be a certain cap, and there will be first an early mover advantage. So I think that the fact that Waymo is growing their business right now, and I'm sure that you are seeing it, is pushing many players to move faster now into the Level 4. They understand that it needs to be scalable, automotive grade. We are seeing a lot of success right now because when you look on opportunities to use a LiDAR, which is automotive grade in the time frame that these programs are targeted, there is no alternative. It's kind of mind blowing.

But when you think about it, the only LiDAR that reached Level 3 so far in the market was either through Mercedes several years ago, but it was using a very low resolution LiDAR. And due to that, it was providing very low availability of the system. And the second one is Innoviz. And we are going to SOP with Volkswagen next year. So we are the only LiDAR that is going to be available for SOP in the next probably 2 or 3 years. And that's a big advantage that we have. So I see actually quite a lot of sense of urgency from the Level 4 players. It's also coming from the truck market. We just announced that we are -- we were selected with a big truck company. And we see it also in other areas such as tractors and some other domains.

So I think that I would still say that Level 2 will transition to Level 3. I think probably towards 2028 when you see a bigger kind of volume. It will start end of '27 and then probably will start to ramp up. I don't have a doubt in my mind that it will. I think that it will -- the fact that we are now going to enable Level 3 urban would increase the value to the customer because it's not only highway. And I think that people would want it because people -- the fact that you are using driver people as supervisors is, I think, a very poor product for humans because being passively responsible, it's a very horrible and tough position to be at. And I think people are really looking for the point where they don't need to do it any longer.

So if we -- and you said Level 4 is like a gold rush right now. I think that when people were doing, let's call it, like the napkin math or back of the envelope math, okay, you could see L2+ penetration going from X to Y, ASP even at $500, what have you, and you could see a very large opportunity. But once that penetration was cut, it sort of shrunk the opportunity. I think we know with Level 4, the issue you're facing is the fleet is much lower, but the ASPs are much higher. So...

And the multiples are higher, right? I have 9 LiDAR per vehicle.

Sure, right? So more and more -- so overall CPV is higher. So can you still with the Level 4 emphasis in the near term, achieve meaningful revenue growth? Is there enough revenue opportunity on a smaller base of vehicles, but with a much higher CPV to generate a type of meaningful revenue growth?

Yes. And I'll say where it can come from. Other than robotaxis, Level 4 is also trucks. And also the count of LiDARs there is pretty high. You have buses and shuttles that are going to be -- there is a huge demand. By the way, I just read in Israel, they are going to bring people -- foreign people -- foreign drivers because of the lack of availability of bus drivers. There is a very obvious problem of professional drivers everywhere around the world. And if you think about a robotaxi task compared to an autonomous bus, I hope you agree with me that training a car to drive in a predefined route is probably easier, and it's much easier to scale. So I have no doubt that these charters such as the ones that we are part of are going to be a growing market and the multiples of LiDARs around it is going to be substantial. But I don't really see it just as Level 4.

There are many other markets that we are -- agriculture, which I was referring to earlier, companies like Caterpillar and John Deere and many tractors that are trying to improve the -- I would say, the efficiency and I would say, lowering the human intervention in several tasks is really growing. And of course, the nonautomotive, we are seeing today a huge demand of LiDARs in -- I just start -- to be honest, Innoviz just started going into the nonautomotive, I think, 5 months ago when we announced InnovizSmart. And I'm overwhelmed, really overwhelmed with the value that we are going to add there. I'll give you an example that I think will -- I was surprised -- I use any opportunity because I'm so surprised. I'll give you a very simple task, security, perimeter security. In Israel, there is a lot of discussion about the fake feel of security when you put so many smart systems and eventually, you don't trust them. I've learned that just the best-in-class solution yet today is far from being safe. We are...

They're all vision-based.

I'm talking about a solution that is used all around the world, okay? We were in a conference in GSX, it's like a big conference for security. it's the same security solution that is offered by everyone. And we were positioned next to a similar -- a solution that was just recently picked in an RFQ for perimeter security of villages. And the team there brought a talented, I would say, educated team that knows how to penetrate fences. With the other solution, they were able to penetrate 4 out of 10 times. They were able to get to the fence and cut it. With our system, it was 0. And they were shocked. And the funny thing is that if I tell you how easy it is to do it, you'll be shocked because all you need to do -- it's not like a James Bond. You need to go and put music and flip flops. You just need to go slow enough or go between the trees. I saw the videos of how the team has managed to penetrate those systems, and I was like laughing.

Like seriously, this is still the best-in-class solution that you're using for perimeter security. When you're using a LiDAR, you cannot avoid light. You cannot. You're just seeing. And it's -- to me, it was really surprising, an eye opener. And I expect that all of those systems that were expected to be installed with that unit will be replaced with ours. This is what we're heading. And this is just one example. And I see the same in ITS, and I see the same in -- really in tolls. I'm quite surprised to see how technology haven't really evolved in so many areas. When I come and show our LiDAR in these events, I'm looked at as if I landed from the moon, really. I showed them the LiDAR and the point cloud and the 3D and people think that I just landed from some other planet. And yes, I think that there is a big opportunity there. The ASPs are significantly higher than automotive. And...

Yes. So maybe just to peel that one back. Can you just outline for us, remind us where ASP or CPV, however you want to define it, between what was a scaled ADAS vehicle which I'm guessing was probably in the $500 to $1,000 versus a full AV. So let's call it, for instance, one of the ID. Buzzes that we've seen that you're spec-ed on versus a nonautomotive solution or perhaps versus a tractor, how do the ASP or CPVs differ?

Yes. So we always look on the cost of the product, the total product, understanding the sensitivity of the pricing. When you talk about a tractor that cost $350,000, you can imagine that they are probably less sensitive on the piece price of the LiDAR if it gives their customer an edge, right? And therefore, we price differently. So the -- if you talk about a low-cost car or a premium vehicle or a vehicle that the total cost of the platform is high, we are trying to make, I would say, our value in the right position. Of course -- the sensitivity, of course, is very high to everyone, and we are also working towards new generations to improve.

But generally, the piece price, if you talk about nonautomotive, it can be up to $10,000 per device, right? And when you talk about high-volume automotive, it can be $500. And it also depends on time and -- I mean, the first year of SOP where the ramp is still occurring, then the volume is lower, then the price are higher. It's not $500. And if the car has 9 LiDARs, like we have with the ID. Buzz or the platforms that we are working with Mobileye or the truck company that we were just awarded, we also have multiple sensors there. Then obviously, the -- you can obviously multiply it by 9, you get the general so...

9X $500 or it's [ $4,500 ].

No, more. More than $500. It's -- for automotive, we price it between $500 to, let's say, $850 depends on volume and time. And yes, it's a value product. It's a...

So we're talking about $6,000 to $7,000 of content in a vehicle.

Yes.

Okay. What about, let's call it, the commercial justification. Because one of the early problems that ADAS faced, and it's not just LiDAR, and we saw this with -- I can think of other companies that have been out there that they would get these robotaxi bids and they would spend money on a program, and there's a lot of upfront validation cost to meet the specs of each program and then it's on a very small number of vehicles, and that's how -- that's a recipe for losing a lot of money. And that was always the whole justification for why scaled ADAS, if you're on a program with 100,000, 200,000 vehicles, all of a sudden, you have an upfront spend, but you can amortize over a wide set of vehicles. So with presumably smaller set of volumes, how do you justify from a commercial standpoint, expanding to these other areas where the scale may not be there? Or is there not that type of validation expense?

Okay. So you're asking about the commercial motivation of carmakers to work on those programs? This is the question?

No, I'm asking. How do you justify it from a P&L standpoint if the problem is that each program you take on has a lot of upfront spend, the volume.

No, no. So first, from our point of view, okay. So there are many overlaps. I mean, basically, today, we are selling the Innoviz to all of our customers. It's the same product, right? So there are many overlaps. And they are all coming from the same production line, from the same testing facilities. There are some, I would say, freedom of design that we are allowing at the outer shelf, window slope, the connector, the interface, et cetera. And therefore, we are actually -- our ability to benefit from additional programs in terms of offsetting our spending is really high. we are not allowing a lot of creativity on the customer side. By the way, it's also from their benefit because they get a more mature product, a shorter time to the market. And yes, we understand that eventually that -- and also the OEMs understand that they are not paying for the entire cost of development. They are participating in it. And therefore, they don't get ownership of the technology because they are not paying for the entire program, but it's offsetting our spending.

Okay. So you're not -- so there's not necessarily that risk of sort of for every program, even for small volume programs, validation.

No, no. I mean, look, we announced just last earnings that we have over $110 million of NREs that we've booked that are going to be paid between this year and next year primarily and also in 2027. That's a really high number that substantially offsets our spending. And this comes on top of everything other that we are selling as products and of course, new programs that we expect to be awarded too in the future. And there are several RFQs that we are also participating now.

Okay. Maybe you can talk about the competitive dynamics because I think you mentioned the LiDAR market. It is consolidating. You see a winner takes more scenario. Most. So I know we've seen some pressures at some of the other players. But what is the competitive set right now? How is it looking? When you're going to RFQs, how many other serious players are you going up against?

Not many. Maybe I want to say one, but I'm not really even sure who, depends on the need, okay? What we've learned over the last couple of years is that it depends on the application, Level 3 and Level 4, I would say that there are segments that we don't have competition because, look, the segment of LiDARs is split between long range and short range. On the short range, we were super successful recently because actually, there's no one is offering short range. It's one of the key advantages of our technology, its ability to be very flexible to allow us to provide different configurations. InnovizTwo was a platform that allowed us to generate multiple variants of it, one that was a fit to Audi and one that fit for Volkswagen and one a fit for Mobileye. And it's all modifications that were done very easily.

On top of it, we've provided a short range that was set for Volkswagen and then another one that was for the truck company. And they are all based on the same technology base. The optical backbone is identical. Nothing changed. The only difference that we allowed are related to the scanning pattern or the outer shell, et cetera. So we are trying to always be very conservative. And this is something that our competitors are uncapable of doing. You have a company that is only focused on automotive, so irrelevant. You have a company that is focused on very niche highway truck, very narrow field of view, which is irrelevant for, I would say, 99% of the market. And that's it. Surprising, right? It sounds like how could it be? And -- but that's the situation, right? Of course, there are many Chinese LiDAR companies, which -- with good products, but they have their own issues, right? So -- but that's where we are.

Okay. So on that, right? Okay, I think we've known there is this bifurcation between China and the West. We know that China has had much more LiDAR uptake. China, in general, on everything has a cost lead, okay? If we take a player like Hesai -- and we don't need to talk about anyone specifically, but the opportunity for Chinese LiDAR players to sell into the West, is that possible?

Look, eventually, it's a political discussion, right? And I'm not a politician. What I can tell you is that LiDARs are security sensitive sensors. From a national security point of view, a LiDAR is a mapping instrument. And when you think about what you can -- you are capable of doing by just collecting data, enormous data when traveling in a car, you can imagine that why people are not really happy about the idea that you will use a technology that possibly is somehow involved with government support. And you see that DoD is intervening, and there are many Congress people that are intervening. And I would say that the U.S. OEMs would have -- will take a huge, huge reputation risk if they will work with a Chinese-based technology.

That's something that I think will not happen because when you think about the U.S. OEMs, they are selling many cars to the government, to the Army. And you think that the Army will not want an autonomous car if they are developing? Of course, they will. I mean, we assume that a U.S. company that developed an autonomous vehicle, their -- one of their key segments would probably go to Defense and Army. Do you think they will use a technology that might be forbidden by the DoD? Probably not, right? And they will not develop something specifically for the Army and for the consumer environment. So I think from that perspective, that's, I would say, how I see it. Again, I'm not a politician, and I don't set those rules. I follow the news.

And I think just yesterday, there was some new adjustments for 2 new LiDAR companies that are now from China that are going to be included in kind of in a list of fighters not to work with. So I would say the dynamics are in the direction that I would say probably not a risk. And not only automotive, also nonautomotive, I can tell you that we are talking with different municipals that don't want to have a sensor that was developed in areas that might create a problem for them. So I think that even from that perspective, when you look on the nonautomotive market, it's Ouster and us, right? I mean it's kind of like 3, 5 years ago, you would say, there are so many other companies, right? It's not the case any longer.

When we -- okay, so if we add all that up in your commercial path specifically the next few years, can you just walk us through you started on BMW on...

i7.

i7. You won a program with Volkswagen. Can you just sort of add it all up for us over the next few years, what is driving sort of the path to commercialization and scale for you and just sort of the specific programs you have? And this new program you have on trucking, sort of the timing and any parameters you can provide?

Yes. What I -- okay, sure. So BMW was our first customer. And following that, we were awarded by Volkswagen for a Level 3 program for the long-range LiDAR. Following that, they decided to use our long-range LiDAR for the ID. Buzz for the Level 4.

With Mobileye.

With Mobileye -- and then they -- in a way, they asked us to develop a short-range LiDAR. They had to replace -- to displace the short-range LiDARs that they were using for reasons that -- some of that we've talked just now. And this was actually an unplanned tour to develop a short-range LiDAR, realizing that we will eventually be the only LiDAR company in the West offering a short-range LiDAR and it became a huge success. So once we were on that program, Mobileye decided to stop their internal development of -- for LiDAR and use our LiDAR sets, long range and short range to all of their other customers. So in terms of the rollout of programs, we have the ID. Buzz Level 4. Following that, there are several Mobileye platform-based customers such as Verne and HOLON that are going to come out following that. There is a program with Audi, Level 3, which are using InnovizTwo that will follow those.

That's Mobileye Chauffeur.

That's a Mobileye Chauffeur. And there is the truck program that we were just awarded that will be in a similar time frame. We didn't say at the time. So -- and since we didn't yet name the customer, we hope to do so, by the way, very soon. I just came back from -- they are U.S., they are going to operate in the U.S. So those are the customers that I think we've already shared. As I kind of hinted, there are several other Level 4 activities that I see now. They -- many of them are changing their sensor suite because many of them have developed their sensor suite based on products that were available and for geopolitical reasons or just the fact that LiDAR companies they've used are going out of business, et cetera. So there are many opportunities now at our table. So that I hope during 2026, we probably will share more. And they have similar target time lines. So I would say, '27, '28, that's the automotive space for you.

I guess, questions?

And there is the top 5 OEM that we talked about Level 3. Yes.

Just maybe on that issue, I don't think you're playing about the politics and security. But just outside of that, how is the cost structure of the product that you've developed? Can you talk about your cost curve over the next 3, 4, 5 years, whatever time frame you're comfortable with? And then how you do compete in some regions at least where you will be competing against the Chinese. How can you do either better technology, quality or even close the cost gap?

Yes, sure. So we've -- we are now offering InnovizTwo, our second generation. The cost saving between the first generation and the second generation was I think 70 more percent. We had a huge cost reduction. And in terms of performance improvement, it was 50x better, okay? InnovizTwo was a revolution. Now we are introducing InnovizThree. We're going to show it working at CES for the first time. It's 60% lower in volume. It will also have an impact, obviously, on cost saving of using less material, less electronics, less size of optics, et cetera. We talked about prices of $500 to $800, so you can understand where this is heading. Eventually, LiDAR technology doesn't -- there's nothing fundamentally expensive about it. When you think about it, there is a laser diode very much like you have in any lead environment. You have a silicon detector that is actually smaller than a camera in terms of the footprint of the dye.

And you have a lot of electronics around it that today haven't gone through yet the vertical integration to a chipset that you put 3 chips and a flex. These are all industrialization steps that will be done over volume, right? Because now obviously, our BOM is reducing by technology, but we haven't done the vertical integration. Like in iPhone, you had multiple chips that eventually were diodes stacked of ICE, right? If you open the box, you will still see several boards inside. It will not be like that in the future. Eventually, it will be one board with a flex, and that's it. And the assembly will be easier. These are things that we are not doing yet because the technology or the market hasn't stabilized yet.

You make those investments when you know that you will not need to change the technology any longer. I will not invest $40 million to make the bond so significantly cheaper. If I know that in 2 years, I need to do a new design because this customer wants this and that customer wants this color. And so this is a very standard process where technologies go through these cycles. We are now in our third generation. I think that this technology is obviously going to produce a significant cost reduction. I hinted also about Level 4 technologies. So I think there are still cycles that we are developing. But eventually, there is nothing fundamentally that LiDARs would not be as cheap as cameras. I know it's kind of like people can't really grasp it, but it's -- there's no reason it shouldn't.

Right, okay. We'll leave it there. Omer, thank you so much.

Thank you.

Ladies and gentlemen, thank you for standing by, and welcome to Innoviz's Third Quarter 2025 Earnings Call. [Operator Instructions] I must advise you that the call is being recorded today.

I'd now like to hand over the call to our first speaker today, Ada Menaker, VP of Investor Relations and Corporate Development. Ada, please go ahead.

Good morning. I would like to welcome you to the Innoviz Technologies Third Quarter 2025 Earnings Conference Call. Joining us today are Omer Keilaf, Chief Executive Officer; Eldar Cegla, Chief Financial Officer. I would like to remind everyone that this call is being recorded and will be available on the Investor Relations section of our website at ir.innoviz.tech.

Before we begin, I would like to remind you that our discussion today will include forward-looking statements that are subject to risks and uncertainties relating to future events and the future financial performance of Innoviz. Actual results could differ materially from those anticipated in the forward-looking statements. Forward-looking statements made today speak only to our expectations as of today, and we undertake no obligation to publicly update or revise them. For a discussion of some important risk factors that could cause actual results to differ materially from any forward-looking statements, please see the Risk Factors section of our Form 20-F filed with the SEC on March 12, 2025.

Omer, please go ahead.

Thank you, Ada, and good morning to everyone joining us today on the call. The third quarter marked another strong period for Innoviz from a financial and business perspective. Since the last earnings call, we made meaningful progress. And recently, we announced that the major commercial vehicle OEM selected us for future serious production of Level 4 autonomous trucks. This agreement, alongside our L3 and L4 automotive wins and the recent ramp of the InnovizSMART for nonautomotive applications, showcases Innoviz's expanding momentum across all segments of the [ latter ] space.

From a financial standpoint, the quarter continued to build on the first half trajectory. We generated $15.3 million in revenues. And year-to-date, we generated $42.4 million, approximately 2.3x more than in the same period of 2024. We are expecting to meet all of our targets for the full year. Cash burn in the quarter was $14 million, and we expect this number to decline sequentially, in line with our guidance for declining year-over-year burn.

On the production side, we are very pleased with the ramp at Fabrinet. In Q3, we shipped significantly more LiDAR units than in Q2, in line with our plans to ship an order of magnitude more LiDARs in the quarter. Our labs achieved the key automotive standard certification for LiDAR testing, which drives meaningful value for our customers and we can now avoid costly and time-consuming external testing. These significant achievements confirm that we are well positioned to ramp InnovizTwo, scale our operations to meet growing demand [ and across ] customer SOPs. Critically, we see that the LiDAR market continues to consolidate. The number of relevant automotive LiDAR players is declining. We believe that there are a few competitors remaining that offer manufacturable technologies that meet OEM performance requirements. The [ winner takes more ] scenario that we've envisioned for quite some time is emerging as we expect to see even fewer companies participating in the space over time.

As these competitive dynamics develop, we are gaining traction across multiple end markets and delivering on our mission to be the world's premier large-scale supplier of best-in-class LiDAR solutions for autonomous driving and beyond. Our growing number of engagements across diverse segments underscores the strength and versatility of our technology.

With that, let's jump into the details. Starting with our recent tracking agreement. In September, we announced that we were selected for serious production of L4 autonomous trucks by a major commercial vehicle OEM. Under the terms of the engagement, Innoviz will provide LiDARs for the customer's L4 Class 8 semi-trucks. We are already shipping units to support the OEMs data collection tracking fleet. Over the past several months, we've made significant progress on this collaboration with respect to meeting customers' requirements and making software modifications to the platform. Next week, I'll be traveling to the U.S. to meet with companies on the East and West Coast, and I have several sessions scheduled with the OEM's management to discuss technical and business details. We expect to be able to share the name of the customer in the coming weeks, and we are tremendously excited about this partnership. It is a validation of our technology and a milestone that reflects our ability to scale across different sectors. It demonstrates that our InnovizTwo platform meets the stringent requirements of the heavy trucking industry and cements our position in the autonomous tracking market.

We are confident that our time-of-flight LIDARs, which can now provide a range of up to 450 meters as well as short and midrange capabilities are ideally positioned to gain additional wins in the trucking space due to the resolution, range, reliability and availability. As with many customers, we hope this is the start of a collaboration that will lead to expansion over time.

The trucking agreement we just discussed highlights a shift in gears in the industry that we've noted over the past year. The race to roll out Level 4 solutions is hitting up significantly. Customers are rushing to bring solutions to the market. And to do this, they need a full set of validated, auto grade and manufacturable LiDARs to enable true autonomy. Aside from Innoviz, we believe few of our competitors have proven to be equal the task. Plans to deploy Level 4 robotaxis around the world are accelerating with several programs featuring the InnovizTwo scheduled for SOPs around the corner. The ramp-up in our collaboration with VW and MOIA in support of the rollout of the ID. Buzz across multiple locations is going well, and we are receiving excellent feedback from our customers on our devices performance in their programs.

As Level 4 plans speed up, we are also progressing on a variety of Level 3 programs, which are targeted to S4 SOPs in '27 and beyond. In the third quarter, we continue to support the top 5 OEM with whom we announced an [ SOW ] over the summer. As part of our automotive development and validation efforts, we are gearing up for our forefront of winter testing in Northern Europe, where our sensor will undergo another round of comprehensive validation under a variety of extreme winter conditions such as rain, snow and fog. This testing is a critical component of enabling automation proving that LiDAR technology provides sufficient redundancy under all conditions.

To prove you with more color on our Level 4 collaboration with VW and the critical role that our LiDAR place, I recently spoke with [ Christian Sender ], the CEO of VW's Autonomous Driving, Mobility and Transport Group [indiscernible] which is spearheading the Level 4 ID. Buzz urban autonomous driving project. Here is our conversation, the full version of which will be available on our website.

[Presentation]

Christian, it's really great to see you here in Israel.

Absolutely.

Christian, what would you say is MOIA contribution to the transformation happening in the urban mobility? .

Fully autonomous mobility becomes now really real. And our ID. Buzz [ and driven ] by the turnkey solution from MOIA. We enable large [ professional needs ] to do people and good trends for urban environment. We are combining actually this self autonomous vehicles, this a self-driving system [indiscernible] MOIA [indiscernible]

Interesting. What do you say is the ID. Buzz most important component that allow you to be safe, [indiscernible]

It all starts with [ safety cost ]. This vehicle [ is 27 centers ] and 9 LIDARs from Innoviz, 3 long range, as you know, and 6 short range. And the combination of all sensors on a strong compute platform gives the performance to understand the [ world ].

The ID. Buzz has 27 sensors. What would you say is the role of the LiDAR in providing reliable perception, safety and performance operation?

LIDAR is more than 350 meters of [indiscernible] gives us the range we need for highway speed and we have the precision to identify objects in the manner [ in heat ]. The great thing about LiDAR is there are really good -- no difference in day and night. We have a great result when it comes to rain [ even 4 key ] conditions, it helps, especially the cameras to understand the environment better than [indiscernible]

What would you say leads to a successful partnership with Innoviz?

We are creating together subsystems which haven't been there ever. And I think what is really special what we do. It's not only high-end performance. It's also industrial scale and fully automotive grade. And what I really love in our collaboration is the openness, fast reaction. And I think we are bringing from both sides, enormous competency to create these new products.

Christian, me and Innoviz are firmly proud for being part of this amazing project. Thank you very much.

It's a great honor.

I would like to thank Christian, VW, MOIA and Mobileye for their partnership, collaborating with such talented and committed teams as we advance the industrialization of autonomous mobility is truly a privilege.

While the automotive space is our main area of focus, let me touch on our progress with the InnovizSMART, which we introduced over the summer. The InnovizSMART is based on the InnovizTwo platform and optimized for nonautomotive use cases. We've already been able to announce several engagements with a variety of diverse customers. We've also completed our first perimeter security installation after ongoing significant testing. And we are expecting to install dozens more by the end of the year. The InnovizSMART was compared to a security solution that has been widely adopted around the world over the last several years. A team of professional auditors tested the pre-existing solution by emulating different types of intrusions. 4 out of 10 times, the team avoided detection. They were able to reach the fence and penetrate it by using several easy tricks that took advantage of the systems underlying weaknesses. Under the same conditions, the auditing team was not able to evade a solution based on InnovizSMART at all.

After such experiments, we have seen customer interest in replacing existing camera and radar-based solutions with [ Innoviz-based One ]. As we expand our presence in the nonautomotive space, we are benefiting from a shorter path to the market and lower acquisition cost for these applications that come from engaging through distributors and integrators. In all, we are continuing to broaden the scope of use cases that we are addressing, and we are in discussion with a number of companies interested in exploring our solution the InnovizSMART. Our traction here validates our approach of first engaging the high-volume automotive end market and after developing an auto-grade production-ready product entering the established industrial market.

As we talk about our business momentum, it's important to understand the advantages of our time-of-flight technology that underpin our success. After evaluating a variety of approaches, including taping out and testing our own FMCW chip, we are now more confident than ever that time of flight will remain the way forward in automotive LiDAR for the foreseeable future. Our time-of-flight LiDAR has demonstrated excellent range, resolution and field of view as well as reliability, durability and availability, which meet the requirements of the automotive OEMs versus competitors using FMCW. We offer 450 meters range with high pixel rate density, better performance in adverse conditions such as rain, fog and dust. And our LiDAR users a mature, auto-grade qualified supply chain, especially in autonomous driving, where the sensor needs to be ready to support a variety of edge cases and have proven durability and reliability. Time of flight has established its advantages versus other technologies.

After many years of testing and experimenting including [ OPA, 15 15 ] and FMCW LiDARs, it's clear to us that [ 905 ] time of flight is the customer's preferred solution. This industry can only scale on the solid ground of a proven mature technology, and 905 time-of-flight has the capabilities, manufacturability and cost profile that meets customer needs in mission-critical applications. Some customers who are publicly committed to using FMCW are now expressing interest in transitioning to time of flight due to what we believe are the disadvantages of FMCW.

As we ramp the InnovizTwo at Fabrinet and continue to strengthen our in-house capabilities, we are also looking ahead. We are now happy to unveil the InnovizThree. The InnovizTwo was revolutionary, offering a new technology and meaningful improvement in many aspects, including cost, range, resolution, et cetera, a major step forward compared to the InnovizOne. The performance of the InnovizTwo advanced rapidly since its introduction. The [ perfect ] platform enabled us to develop the InnovizTwo short- to medium range and the InnovizSMART, which were evolutions of the InnovizTwo. We believe that InnovizThree will again revolutionize the industry. It will allow us to reach a better cost structure while enabling a 60% smaller form factor for easier integration into different [indiscernible] locations like in the cabin and behind the windshield, something many of our customers have requested. It will also offer better performance and power consumption.

Like the InnovizSMART and short range, the InnovizThree will enable us to develop new variants of LiDAR to better serve different and new automotive and nonautomotive applications. As we just discussed, we believe that the time of flight will remain the way forward for the foreseeable future. The InnovizThree will, therefore, be based on proven, reliable and manufacturable time-of-flight technology. LiDAR is an extremely complex and demanding field. Innoviz has successfully demonstrated ability to meet the most stringent requirements of the automotive industry.

Installation behind the windshield adds another level of complexity. And I'm confident that Innoviz will be the one to overcome this hurdle. You can expect to learn more about this groundbreaking device at CES.

Now let's move on to our outlook. Driven by the ramp of our production line and NREs, we continue to expect more than a twofold increase in our revenues year-over-year for 2025 to $50 million to $60 million. We continue to see a growing contribution from LIDAR sales versus NREs in our revenue mix. At the beginning of the year, we guided for $20 million to $50 million in NRE bookings since we had booked more than $20 million in the first half of the year. Last quarter, we increased our NRE booking guidance for 2025 to $30 million to $60 million. I'm happy to tell you that we are already within this range today.

As you recall, we started the year with $80 million in NRE payments plan with the expansion of existing NRE plans and the addition of new programs. Our NRE payment plans are now above $110 million to be paid between 2025 and 2027. As we recognize revenues for these NREs, we are continuing to expand our production capabilities, meet customers' milestones and pursue new opportunities across different end markets.

And with that, I'll turn it over to Eldar to talk about our financials.

Thank you, Omer, and good morning, everybody. In the third quarter, Innoviz saw continued financial and operational momentum. Revenues were [ $15.3 million ]. Year-to-date, we generated $42.4 million in revenues, 2.3x the $18.2 million in revenues we generated in the same period of 2024. We ended Q3 with approximately $74.4 million in cash, cash equivalents, short-term deposits and marketable securities on the balance sheet. And we have no long-term debt. Cash used in operation and capital expenditure in the third quarter was approximately $14 million, and we expect this number to decline sequentially, consistent with our expectations for lower year-over-year cash burn. Our strong balance sheet and operational improvements will provide us the runway to cross customers' programs into 2027.

Now turning into the income statement. Our Q3 revenues of $15.3 million was 238% up year-over-year supported by NREs as well as sales of LiDAR's units. Gross margins in the quarter was approximately 15% and approximately 26% year-to-date. Margins will continue to be somewhat variable going forward based on the timing of our product ramp and fluctuation in NRE payment based on customers' milestones. Our operating expenses for Q3 were $18.1 million, a decrease of approximately 30% from $26 million in Q3 2024. This quarter's operating expenses included $2.4 million of share-based compensation compared to $4.2 million in Q3 of 2024. Research and development expenses for Q3 were $12.4 million, a decrease from $19.7 million in Q3 2024. The decrease is primarily related to allocation of costs related to sales of NRE and to the operational realignment in Q1. The quarter's R&D expenses included $1.3 million of share-based compensation compared to $3 million in Q3 of 2024.

I'm very proud of our achievements this year-to-date and look forward to the opportunities ahead as we introduce the InnovizThree and secure additional automotive and nonautomotive design wins.

With that, I'll turn the call back to Omer for his closing remarks.

Thank you, Eldar. Before I wrap up the call and open for Q&A, I wanted to recap some of our recent developments. We reported record year-to-date revenues while continuing to meaningfully lower our annual cash burn. We've been selected to supply LiDAR for a major global trucking OEMs serious production of Level 4 autonomous trucks. Our InnovizSMART is gaining traction in a variety of applications, including perimeter security and [ ITS ]. Testing indicates that platform based on -- LiDAR outperformed leading solution. Our solution provides the safety and security required in a perimeter defense application. As in automotive, this is yet another case where our technology can save lives.

We continue to make progress with Level 3 and Level 4 automotive programs. We are unveiling our next-generation revolutionary InnovizThree, which will enable us to meet mission-critical safety requirements across a variety of new and existing end markets. It is based on industry-leading time-of-flight technology, offering better performance and cost in a smaller [ form factor ]. Over the past quarter, we grew our shipments by an order of magnitude, demonstrating the manufacturability and production readiness of our platform.

In all, we are tremendously proud of our progress as we work toward our goal of becoming the world's premier large-scale provider of best-in-class LiDAR solutions for autnomous driving and beyond.

With that, operator, let's open it up for the Q&A.

[Operator Instructions] The first question is from Mark Delaney with Goldman Sachs.

Yes. I was hoping you could start with an update on the L3 development program for consumer vehicles with the top 5 auto OEM that you previously announced? And what do you think needs to happen for that to become a series production award?

Sure. So over the last quarter, we were working on the [ SODW ] based on what we've signed on previous quarter. We delivered on several of the items which we are still in discussion with the customer. And we are pending for the follow, we'll say, following stage of the process. Generally, there are still technical commercial discussions to be completed before [ returns into a sales production ].

Just any sense on timing as to how long that may take to all come to completion?

I would say it's not -- I would say, it's in a very developed stage, trying to guess on how long it will further [indiscernible]. But I would say it's a very developed stage.

Okay. That's helpful. Another question was on the competitive environment. Omer, you mentioned the declining number of competitors you're now seeing. Can you zoom in on that? Has Innoviz seen any recent changes in the competitive landscape and a number of business opportunities that are available given that one of your merchant LiDAR competitors recently reported that it's facing financial pressure and then also in light of the current geopolitical backdrop?

Yes, definitely. I think that in general, we see that when we are approaching programs, our -- what we see in terms of competitive offers we have from others, it's obviously limited due to the, let's say, consequences of either geopolitical or the other solution and capable of fulfilling the needs and time line. And therefore, we expect -- we see that in modality, the competitive landscape for automotive LiDAR solutions is very limited. So this is what we are reflecting here and saying that we expect it to continue.

Our next question is from Colin Rusch from Oppenheimer.

Can you talk a little bit about the incremental investments you might need to make into sensor fusion with some of your partners as you kind of proliferate some of these applications, it seems like having some visibility into the software element of this could be useful for you. But just want to get a sense of how you're thinking about that as the market opportunity evolves.

Sure. So I think here, I would split the market between automotive and nonautomotive where the task of sensor fusion is somehow different than the softer opportunity also is in a way also in terms of commercialization and monetization is different types of opportunities. When talking about integrating into a platform such as Mobileye or NVIDIA, where we see in several cases where the OEM wants the platform player to take ownership on the sensor fusion there, our work with the customer is related to obviously providing them the details and doing the test with them. There is a certain softer components that we provide as a license for working with the overall software stack will include also a certain software layer coming from us, primarily in terms of doing some LiDAR management, weather conditions, range detection, degradation or things that are related to the LiDAR itself. And in some cases, we provide some, I would say, higher layers of the application.

And when talking about nonautomotive application, this is where there are different players related to background removal, and compression, object detection and classification. This depends on the application itself. We -- some of this, we are doing ourselves, some of that we are doing with partners. And in these programs, the business model is -- also involves a certain support and maintenance because some of these programs, I would say most of these programs are 24/7 operation. It's a different, I would say, operational mode of the sensor unlike a vehicle where it drives a [indiscernible] utilization. And then it means that it's a longer, I would say, working hours in terms of number of hours that -- the work. So there is a certain element of recurrent revenues coming from support over several years.

And we are working with different customers to understand their needs. And I was -- I elaborated earlier about a specific use case, which is the security -- perimeter security. I was literally blown away with how this sector is underserved. And it's not -- it's -- I would say, you would expect that such a domain will have a solution that will be hermetic. We are all aware of the situation in different places around the world and seeing that even the best solutions that are used in different cases that are super expensive, you see how easily they are compromised and [indiscernible]. And we see that we need to -- when we show our solution to different customers, they are literally, again, blown away [indiscernible] the only way I can express it.

And I think there, there's a lot of work to be done to integrate our solution to the different [ VMS ], the video monitor systems used by the common control channels. So I think this is where we expect to see a very nice development in the coming months. Adding to it also tolls, ITS and really some other things that I hope that we'll be able to share in the coming months.

So -- and a big part of it is related to the -- creating the right insights. I mean, in these applications, KPIs, data analytics that needs to be done to make use of [indiscernible] sensor different than an automotive market. So this is where we are currently diving into. And I'm sure we'll find more opportunities where our sensors with their performance, liability can create new markets. So we'll share more, but in this bundle, it will be a mix between sensors, compute and software.

Excellent. And just as a follow-up with the next-generation product and as you start to scale up volumes. Seeing some of the maturation of the supply chain, can you talk a little bit about the potential cost reduction trajectory that you're expecting here over the next couple of years and how that may impact your opportunity to address even larger pockets of demand?

No, I can talk about -- generally, LiDARs will continue to reduce cost. It will come through revolution, parts in technology where we keep doing so. And the InnovizThree relies on the new technology development that allows us to benefit from further cost reduction and we'll keep doing so. I think on top of it, I do expect that a major part of the cost reduction will come for industrialization.

When you think on really the baseline of what is a LiDAR, it's a light source, a laser chip detector, silicon-based processing units. I think that what I just kind of described can also be described by a [ CD drive ]. There are many electronics that used to cost a lot at some point of time and today are really priced at the tens of dollars. And there is nothing fundamentally more expensive in the LiDAR than these kind of technologies that maybe 20 years ago, have cost thousands of dollars, then hundreds of dollars and then lower. Eventually, there is nothing fundamentally different. And therefore, I do expect that as the technology will continue to evolve, you will do -- eventually, you need to have investments to do the right ROI in terms of cost reduction.

I wouldn't do a $10 million investment now to save $10 in the bill of [ material ]. It's not yet the time where the volume justifies it. But you can imagine that as the volume would grow these kind of opportunities are available to us. And we are no longer in a stage where we're talking about whether this technology can be enabled. We are in, I would say, industrialization stage where we need to do integration of discrete electronics into more chips. These are primarily, I would say, execution and R&D, just maybe without the R part of it. Straightforward processes that were done in other markets before starting Innoviz, I was working on several other industries such as mobile. And in these areas, we've done the same. So I expect to see LiDAR do cheaper and cheaper and eventually available even to consumer applications.

[Operator Instructions] Our next question will come from [indiscernible] from TD Cowen.

Great. Thank you. Good afternoon, everybody. I was hoping you can walk us through more of what you're seeing in some of your L3 and L4 discussions with automakers. And specifically, if we talk about what you think it will take to accelerate sourcing decisions kind of what are automakers looking for at this point to make those decisions? And then broadly in the next few years, as you talk to automakers and look at the market, how you're seeing L3 maybe L4 penetration kind of play out in the industry?

Yes, sure. I mean obviously, that's a question that comes up many times with investors. And the way I like to address it is when you look on the Chinese market, you could look at it as kind of the crystal ball of where the automotive market is heading. And the western OEMs are aware that the Chinese cars are becoming -- they are fast moving. They are equipped with more technologies, and they understand that they need to keep the differentiation going forward.

I think there is a lot of evidence seeing that Level 4 is coming to fruition. You see many players trying to move faster, understanding that it's going to be a point where seats are going to be taken around the table. Eventually, cities are going to be populated with robotaxis and there will be a limit of -- due to congestion of family cars could actually be allowed [indiscernible]. And the race has begun because several of these players are rolling out. And therefore, we do see a sense of urgency coming from others.

In terms of Level 3, I know I can also share that some of the discussions we're having right now with customers is also looking on the opportunity related to urban Level 3. As you might be aware, today, most of the Level 3 applications are [indiscernible] highway. Some OEMs are seeing the highway is a good first step, but some of the audience are looking to add an urban experience knowing that, that is what their customers are really interested with. So we are in discussions with OEMs around several concepts. I mean, obviously, Innoviz is very innovative companies. And we talked about InnovizThree as a new platform where we can design around the different variants. So in a way, [indiscernible] things that we are working on.

So definitely, I expect to see Level 3 urban highway at some point of time and growing very fast in the West. Level 4 is definitely already coming.

Very helpful. And as a follow-up, back to the InnovizThree, can you talk a little bit more about some of the performance improvement that you're targeting? And also just remind us when the [ star ] production is expected for that platform?

Yes, sure. So I think the next challenge related to L3 is where we're seeing some of the customers. I can take it into 2 different paths. One is the highway, the other one is the urban. Both of them are actually related to the design of the vehicle, right? Because when you talk about highway then you see some OEMs, they want to add the LiDAR behind the [ windshield ]. And LiDAR by itself is a very complex and challenging technology, even if you don't put it behind the windshield. Putting it behind the windshield as maybe another magnitude of difficulty because it adds restrictions, constraints related to the size and power consumption and also the integration into the windshield, which has its own kind of integration challenges.

So this is kind of something that, as I said in the -- earlier in the call, seeing these challenges, we are obviously working to show the customers that with InnovizThree, we can overcome these additional challenges by building a product that has a certain buffer related to the performance, significant volume reduction, 60%, and power consumption reduction. There are several additional nice design perspective that we included in InnovizThree, which we believe will give us even additional advantages related to this specific challenge.

And this is why, as I said earlier, there are only maybe 2 LiDAR companies that ever got to a Level 3 on the road. There many have announced Level 3. But I think Innoviz has probably provided a solution for the best Level 3 [indiscernible] available. And I believe that we will be the one solving this problem as well.

Taking into Level 3 urban. So again, it's a design discussion. It's also related to cost because it requires more than 1 sensor. You don't want to use 9 LiDARs as much as we would like, obviously. So it means that you do need to take into consideration design cost. And this is where another good design of the LiDAR and a good understanding also of the different use cases is where a good discussion between a LiDAR developer and the OEM is needed. So these are the 2 I would mention. Other than that, there are Level 3 programs will -- we have already integrated, whether it's in the roof or in the grill and the first one that is expected to launch is in '27.

Our next question is from Jash Patwa from JPMorgan.

Congrats to the team on all the progress this quarter. I wanted to start with a question on the L4 commercial OEM win. Could you maybe share any details around the SOP time line, the number of LiDARs per unit and the overall volume opportunity you expect as part of this platform? And I have a follow-up.

Sure. So we said that we expect to announce -- to do an announcement with the customer in several weeks where we are planning to share more information, and we want to be respectful for the [indiscernible] towards the OEM while we are working on the -- on this announcement. There is going to be multiple [ sensors per visual ], but I do want to be -- again, I want to wait for it. It's in the next few weeks, so we prefer to wait at this point.

Makes sense. And then curious if you could give us a preview for expectations into 2026 in terms of revenue and gross profit. How should we think about the contribution from the ramp of the contract wins under the Mobileye Drive platform and some of the ongoing development work with large automakers? Just wondering if you could give us a sense of what the strategic priority for the company looks like in 2026?

I think, obviously, we'll talk about the guidance in the next quarter. But other than that, of course, we are expecting growth with the deployment of vehicles -- Level 4 vehicles, whether it's coming from Volkswagen or other customers of Mobileye that we are working with. And we expect Mobileye also to grow their customer base, which we are already selling LiDARs to customers that are currently in those discussions. And obviously, we're waiting to see them mature to a program.

Other than that, we have different customers. [indiscernible] truck that we were awarded that is going to be deployed and the top 5 OEM depends on how, of course, things will develop. I think the [ Smart ] is where we are very excited around. We see where our solution really unlocks opportunities because when you think about the LiDARs that are currently available in the market, which are from also geopolitical elements are also very strong in those areas as well. And when you look on the available solutions for nonautomotive, they are relatively limited in their capabilities, being able to share and sell our long-range, high-resolution, automotive grade, unlocks several applications that were not available.

I think security is where we see an amazing fit because we have an extraordinary product that solve problems that other LiDARs as far as I am aware of, I'm capable of with the geopolitical element is giving us a big advantage. So I think we'll continue to grow on these markets. And there are still other OEMs that were in discussion. I mean, we talked about the top 5, et cetera, but they're actually other OEMs and Level 4 platforms, which as I said, once we announced on the award we got from a truck -- one of the largest -- truck companies in the world, obviously, it's both discussions with other truck companies and other Level 4 partners. There are RFQs being drafted. I believe it's -- I think we have a good fit to many of them.

Appreciate all the color, Omer. Thank you and good luck.

There are no further questions. I'm handing the call back to Omer for closing remarks.

Thank you very much. Thank you very much for joining our call. Next week, I'll be traveling to the U.S., meeting with different customers in the East and West Coast, I'll be in New York for the Barclays New York Conference. Happy to meet you there. And of course, the CES is coming along. It's always -- for us, it's an innovation celebration opportunity, national holiday at Innoviz. We're going to show our new technologies, and we look forward to meet with there. Thank you very much.