Endava ADR Stock price
Is Endava ADR a Top Scorer Stock based on the Dividend, High-Growth-Investing or Leverman Strategy?
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Key metrics
📘 Market Capitalization
📈 What is it?
Market capitalization shows how much a company is currently worth on the stock market.
🧮 How is it calculated?
🏛️ Why is it important?
It helps classify companies by size (Large, Mid, Small Cap) and indicates their market presence and relative stability.
🧮 Calculation
🎯 What does this mean for investors?
- Large-cap companies tend to be more stable, often pay dividends, but may grow more slowly.
- Smaller firms may offer higher growth potential but come with more volatility.
- Market capitalization is a useful indicator of company size — but not a measure of whether a stock is undervalued or overvalued.
📘 Enterprise Value (EV)
📈 What is it?
Enterprise Value represents the total cost to acquire a company — including its debt and excluding its cash reserves.
🧮 How is it calculated?
(= Market Cap + Net Debt)
🏛️ Why is it important?
EV gives a more complete picture of a company's value than market cap alone and is used in key valuation ratios like EV/FCF or EV/Sales.
🧮 Calculation
🎯 What does this mean for investors?
- Enterprise Value shows the true cost of buying a company, including all financial obligations.
- It is more accurate than just looking at market cap, especially when comparing companies with different levels of debt or cash.
- Professional investors prefer EV-based multiples because they better reflect the company’s full financial footprint.
📘 Net Debt
📈 What is it?
Net Debt shows how much debt remains after subtracting a company’s available cash reserves.
🧮 How is it calculated?
🏛️ Why is it important?
It indicates how dependent a company is on borrowed money and how easily it can service its debt in the short term.
🧮 Calculation
🎯 What does this mean for investors?
- Low or negative net debt signals financial strength and flexibility.
- Companies with strong cash positions are better positioned in crises.
- High net debt increases financial risk — especially in environments with rising interest rates or economic downturns.
📘 Cash
📈 What is it?
Cash represents all liquid assets a company can access immediately — including cash, bank deposits, and short-term investments.
🧮 How is it calculated?
🏛️ Why is it important?
It reflects a company’s financial flexibility and resilience — enabling investments, buybacks, or buffer in downturns.
🧮 Calculation
🎯 What does this mean for investors?
- A strong cash position means greater room for maneuver and crisis resistance.
- Cash-rich companies can invest, pay down debt, or repurchase shares.
- But excess idle cash might indicate a lack of growth opportunities.
📘 Shares Outstanding
📈 What is it?
Shares outstanding represent the total number of a company’s shares currently held by investors — excluding treasury stock.
🧮 How is it calculated?
🏛️ Why is it important?
It’s the basis for key metrics like Earnings Per Share (EPS), Market Capitalization, or the Price/Earnings ratio (P/E).
🧮 Calculation
🎯 What does this mean for investors?
- Fewer shares in circulation typically increase earnings per share — making each share more valuable.
- Share buybacks reduce the number of shares and boost per-share metrics.
- Issuing new shares does the opposite — diluting shareholder value and lowering per-share figures.
📘 Price-to-Earnings Ratio (P/E)
📈 What is it?
The P/E ratio shows how many times a company's earnings per share are reflected in its current share price — in other words, how "expensive" the stock appears relative to its profits.
🧮 How is it calculated?
🏛️ Why is it important?
The P/E ratio is one of the most widely used valuation metrics. It helps investors assess whether a stock appears cheap or expensive compared to its earnings power.
🧮 Calculation
📊 P/E (TTM) = Based on earnings from the last 12 months (Trailing Twelve Months):🎯 What does this mean for investors?
- A low P/E may indicate undervaluation — or signal underlying issues.
- A high P/E may reflect strong growth expectations — or an overvalued stock.
📘 Price-to-Sales Ratio (P/S)
📈 What is it?
The P/S ratio shows how much investors are paying for $1 of the company’s revenue – regardless of profitability.
🧮 How is it calculated?
🏛️ Why is it important?
P/S is especially useful for evaluating growth companies or businesses not yet profitable. It reflects how the market values the company’s sales.
🧮 Calculation
Market Cap = $115.79m | Revenue (TTM) = $968.26m
Market Cap = $115.79m | Estimated Revenue = $981.51m
🎯 What does this mean for investors?
- A low P/S may indicate undervaluation — or low profitability.
- A high P/S can reflect strong growth expectations — or excessive optimism.
- Especially helpful when evaluating companies where profits are low, volatile, or negative.
📘 Enterprise Value to Sales (EV/Sales)
📈 What is it?
EV/Sales shows how much investors are paying for $1 of revenue — considering not just equity, but also debt and cash. It’s the capital structure–adjusted version of the P/S ratio.
🧮 How is it calculated?
🏛️ Why is it important?
It’s ideal for comparing companies with different levels of debt. It reflects a company's true cost relative to its revenue.
🧮 Calculation
Enterprise Value = $368.68m | Revenue (TTM) = $968.26m
Enterprise Value = $368.68m | Forward Revenue = $981.51m
🎯 What does this mean for investors?
- EV/Sales allows for capital structure–neutral company comparisons.
- A lower ratio may indicate undervaluation; a higher one may signal strong growth expectations or overvaluation.
- Especially helpful when evaluating high-growth companies with low or negative earnings.
📘 Enterprise Value to Free Cash Flow (EV/FCF) | ex SBC
📈 What is it?
EV/FCF compares a company’s enterprise value with its free cash flow. The metric therefore shows the multiple of current free cash flow at which a company is valued. EV/FCF ex SBC additionally accounts for stock-based compensation (SBC). While SBC does not represent a direct cash outflow, issuing shares as compensation can dilute existing shareholders. Therefore, SBC is deducted from free cash flow in this adjusted version.
🧮 How is it calculated?
EV/FCF ex SBC = Enterprise Value ÷ (Free Cash Flow (TTM) − SBC)
🏛️ Why is it important?
EV/FCF provides a valuation based on free cash flow and therefore complements earnings-based valuation metrics such as the P/E ratio. The ex SBC version additionally accounts for the economic impact of stock-based compensation and provides a more conservative view from a shareholder perspective.
🧮 Calculation
🎯 What does this mean for investors?
- A low EV/FCF means that enterprise value is low relative to current free cash flow. The reasons should always be considered in the context of the company and its industry.
- A high EV/FCF means that enterprise value is high relative to current free cash flow. This can, for example, reflect high growth expectations or temporarily weak cash generation.
- When SBC is positive and adjusted free cash flow remains positive, EV/FCF ex SBC is generally higher than the standard EV/FCF.
- The metric is particularly useful for companies with relatively stable and predictable cash flows.
- If free cash flow is negative or very low, EV/FCF has limited usefulness and should not be interpreted like a standard valuation multiple.
📘 Price-to-Book Ratio (P/B)
📈 What is it?
The P/B ratio compares a company’s market value to its book value — showing how much investors are paying for each dollar of net assets.
🧮 How is it calculated?
🏛️ Why is it important?
P/B is commonly used for asset-heavy industries like banks or industrials. It helps assess whether a stock is trading above or below its net asset value.
🧮 Calculation
🎯 What does this mean for investors?
- A P/B below 1 may signal undervaluation — or weak profitability.
- A P/B above 1 implies the market expects future value creation (e.g., brand, IP, growth).
- Best used for companies with tangible assets and strong balance sheets.
📘 Equity Ratio
📈 What is it?
The equity ratio indicates what portion of a company’s total assets is financed by shareholders’ equity – in other words, how much it relies on its own capital.
🧮 How is it calculated?
🏛️ Why is it important?
A high equity ratio reflects financial strength and stability, especially during downturns. It’s a key indicator of a company’s solvency and long-term risk profile.
🧮 Calculation
🎯 What does this mean for investors?
- Companies with high equity ratios are generally more resilient and less dependent on external debt.
- Low equity ratios can signal higher risk or aggressive financial strategies.
- Important: Always assess the equity ratio in combination with the return on equity (ROE). This shows not just how stable the company is – but also how efficiently it uses shareholder capital.
📘 Return on Equity (ROE)
📈 What is it?
Return on equity (ROE) shows how efficiently a company uses its shareholders’ equity to generate profit. In other words: how much net income is earned per dollar of equity.
🧮 How is it calculated?
🏛️ Why is it important?
ROE is a core profitability metric. It helps investors understand whether a company delivers attractive returns on the capital provided by its shareholders.
🧮 Calculation
🎯 What does this mean for investors?
- A high ROE indicates that the company is using its capital efficiently and profitably.
- It’s especially meaningful for capital-intensive businesses or firms with high equity bases.
- Important: A very high ROE can also result from high debt levels – always interpret it alongside the equity ratio to assess financial health.
📘 Return on Capital Employed (ROCE)
📈 What is it?
ROCE measures how efficiently a company generates profits from its total capital – including both equity and interest-bearing debt.
🧮 How is it calculated?
It evaluates the return on all capital employed, regardless of how it’s financed.
🏛️ Why is it important?
ROCE is ideal for comparing companies with different financing structures. It shows how well management uses capital to create value for both shareholders and creditors.
🧮 Calculation
🎯 What does this mean for investors?
- A high ROCE means the company uses its capital efficiently – regardless of whether it's funded by debt or equity.
- The higher the ROCE compared to peers, the more value the company creates with its invested capital.
- Especially relevant for capital-intensive sectors like industrials, energy, or infrastructure.
📘 Return on Invested Capital (ROIC)
📈 What is it?
ROIC measures how efficiently a company generates returns from the capital invested in its core operations – regardless of whether the capital comes from equity or debt.
🧮 How is it calculated?
- NOPAT = Net Operating Profit After Taxes
- Invested Capital = Operating assets minus non-interest-bearing liabilities
🏛️ Why is it important?
ROIC is one of the most accurate indicators of capital efficiency. Unlike return on equity, it is not distorted by leverage and shows how much value is created for all capital providers.
🧮 Calculation
🎯 What does this mean for investors?
- A high ROIC shows how effectively a company uses the capital that is truly invested in its core operations.
- Unlike ROCE, ROIC focuses only on the capital that is actively used to run the business – and that requires a return (i.e. interest-bearing).
- Especially useful when comparing companies with large amounts of excess cash or non-interest-bearing liabilities – giving a more realistic picture of capital efficiency.
📘 Leverage Ratio (Debt-to-Equity)
📈 What is it?
The leverage ratio indicates how much a company relies on interest-bearing debt (such as loans and bonds) relative to its shareholders’ equity.
🧮 How is it calculated?
🏛️ Why is it important?
This ratio helps assess a company’s financial structure and risk profile. High leverage can enhance returns – but also increases exposure to interest rate changes and financial stress.
🧮 Calculation
🎯 What does this mean for investors?
- A low leverage ratio signals financial strength and independence.
- A higher ratio can improve returns in good times but increases risk during downturns or rising interest rate periods.
- 👉 Always interpret in the context of industry, capital intensity, and interest rate environment.
📘 SBC | in % Revenue
📈 What is it?
SBC (Stock-Based Compensation) refers to equity-based compensation granted by a company to its employees and executives. The percentage shows SBC relative to revenue.
🧮 How is it calculated?
SBC as % of Revenue = (SBC ÷ Revenue) × 100
🏛️ Why is it important?
Stock-based compensation is a real cost factor for shareholders. It can increase the number of shares outstanding and therefore dilute existing shareholders. The percentage of revenue shows how heavily a company relies on equity-based compensation and how significant this form of compensation is relative to the size of the business.
🧮 Calculation
🎯 What does this mean for investors?
- A lower figure is generally positive: Stock-based compensation is relatively small compared with the company's revenue.
- A high figure can indicate greater reliance on stock-based compensation and a higher potential risk of dilution. However, it is also important to consider whether the company offsets dilution through share buybacks.
- The trend over time should also be considered. A high but declining percentage presents a different picture from a persistently high or increasing percentage.
- A single-digit SBC-to-revenue ratio is not unusual among many growth-oriented and technology companies.
📘 SBC as % of FCF
📈 What is it?
SBC (Stock-Based Compensation) refers to equity-based compensation granted by a company to its employees and executives. The percentage shows SBC relative to free cash flow (FCF).
🧮 How is it calculated?
SBC as % of FCF = (SBC ÷ Free Cash Flow) × 100
🏛️ Why is it important?
Stock-based compensation is a real cost factor for shareholders. It can increase the number of shares outstanding and therefore dilute existing shareholders. The percentage of free cash flow shows how significant SBC is relative to the cash generated by the company. Since SBC is non-cash compensation, it is typically not deducted as a cash outflow when calculating FCF.
🧮 Calculation
🎯 What does this mean for investors?
- A lower value is generally favorable. Stock-based compensation is relatively small compared with the company's cash generation.
- A high value means that SBC represents a significant portion of the company's reported free cash flow, even though SBC itself is non-cash.
- The higher the value, the more significant SBC can be as an economic cost to shareholders, particularly when it results in share dilution.
📘 SBC Growth 1Y
📈 What is it?
SBC Growth 1Y shows how much a company's stock-based compensation has changed compared to the previous year.
🧮 How is it calculated?
🏛️ Why is it important?
SBC Growth shows whether stock-based compensation is becoming more or less significant for shareholders. If SBC increases significantly, it can lead to greater shareholder dilution over time. At the same time, SBC is a non-cash expense that reduces earnings on the income statement but is added back in the cash flow statement.
🧮 Calculation
🎯 What does this mean for investors?
- A high positive value is generally negative, as rising SBC can increase the burden on shareholders, particularly through potential dilution.
- What matters is whether the development of SBC is sustainable over the long term. Some level of SBC is common among many growth and technology companies.
📘 Share Count Growth 1Y
📈 What is it?
Share Count Growth 1Y shows how much the number of shares outstanding has increased or decreased over a one-year period.
🧮 How is it calculated?
🏛️ Why is it important?
The number of shares determines how many shares the company's earnings and assets are distributed across. If the share count decreases, existing shareholders' relative ownership increases. If it increases, existing shareholders are diluted. The metric therefore makes dilution and share buybacks directly visible.
🧮 Calculation
🎯 What does this mean for investors?
- A negative value is generally positive, as the number of shares outstanding is decreasing.
- A positive value indicates dilution of existing shareholders.
- A declining share count is not automatically positive: It also matters at what price the shares are repurchased and how the buybacks are financed.
📘 Shareholder Yield
📈 What is it?
Shareholder Yield measures how much capital a company returns to shareholders or uses to reduce debt relative to its market capitalization. It goes beyond dividend yield by also including share buybacks and debt reduction.
🧮 How is it calculated?
🏛️ Why is it important?
Dividend yield only tells part of the story. Companies can also return capital through share buybacks, while reducing debt can strengthen the balance sheet. Shareholder Yield combines all three components into one metric, giving investors a broader view of how a company uses its capital.
🧮 Calculation
🎯 What does this mean for investors?
- A higher Shareholder Yield generally indicates more capital being returned to shareholders or used to reduce debt.
- The mix matters: dividends, buybacks, and debt reduction can affect shareholders in different ways.
- Share buybacks are most beneficial when shares are repurchased at attractive valuations.
- Investors should also consider whether dividends, buybacks, and debt reduction are sustainable over time.
📘 Revenue
📈 What is it?
Revenue shows how much a company earns in total from selling its products and services – the gross income before any costs are deducted.
🧮 How is it calculated?
🏛️ Why is it important?
Revenue is one of the key figures to assess a company’s size, market position, and growth potential.
🧮 Calculation
🎯 What does this mean for investors?
- Growing revenue indicates rising demand and can be an early signal of future earnings growth.
- Comparing actual and expected revenue reveals trends in the market environment and analyst sentiment.
- Note: Strong revenue alone isn’t enough – margins and profitability matter just as much.
📘 EBITDA
📈 What is it?
EBITDA stands for “Earnings Before Interest, Taxes, Depreciation, and Amortization.” It reflects a company’s operating profit before the effects of financing, taxes, and accounting depreciation.
🧮 How is it calculated?
🏛️ Why is it important?
EBITDA is widely used to evaluate a company’s operating performance – especially across capital-intensive sectors or international comparisons.
🧮 Calculation
🎯 What does this mean for investors?
- A high or growing EBITDA indicates strong operational profitability – independent of taxes, interest, or accounting methods.
- It’s especially useful for comparing companies across sectors or geographies.
- Important: EBITDA is not a net income figure – it excludes key costs like depreciation and interest.
📘 EBIT
📈 What is it?
EBIT stands for “Earnings Before Interest and Taxes.” It reflects a company’s operating profit after depreciation, but before interest and tax expenses.
🧮 How is it calculated?
🏛️ Why is it important?
EBIT is a core profitability metric that shows how well the company performs in its main business operations – independent of capital structure and tax environment.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBIT indicates strong profitability from the company’s core business – before financial and tax effects.
- It allows better comparison between companies with different debt levels or tax structures.
- Compared to EBITDA, EBIT already accounts for depreciation and reflects capital intensity more clearly.
📘 Net Income
📈 What is it?
Net income is the company’s total profit – the amount left after all expenses, taxes, interest, and depreciation have been deducted.
🧮 How is it calculated?
🏛️ Why is it important?
Net income is the most comprehensive measure of a company’s profitability – showing how much actual profit remains after all business and financing costs.
🧮 Calculation
🎯 What does this mean for investors?
- Growing net income indicates that the company is managing all of its costs efficiently.
- It directly influences valuation metrics like P/E ratio and the company’s dividend capacity.
- Over time, net income trends reveal how resilient and profitable the business model really is.
📘 Free Cash Flow (FCF) | ex SBC
📈 What is it?
Free cash flow shows how much cash remains after a company has covered its operating and capital expenditures. FCF ex SBC additionally deducts stock-based compensation (SBC) to adjust the cash flow for the effect of non-cash SBC.
🧮 How is it calculated?
Free Cash Flow ex SBC = Operating Cash Flow − SBC − Capital Expenditures (CAPEX)
🏛️ Why is it important?
FCF reflects a company’s actual financial strength – independent of reported accounting earnings. It shows how much flexibility a company has for dividends, share buybacks, or debt reduction. FCF ex SBC also deducts stock-based compensation and shows how much cash generation remains after SBC.
🧮 Calculation
🎯 What does this mean for investors?
- High free cash flow indicates that a company has strong financial strength – independent of reported earnings.
- It is often a solid basis for sustainable dividends and share buybacks.
- Declining FCF can be a warning sign, even if reported earnings remain stable.
📘 Revenue Growth
📈 What is it?
Revenue growth shows how much a company’s sales have changed compared to the previous year – both on a trailing basis (TTM) and based on forward projections.
🧮 How is it calculated?
Forward = (Expected revenue ÷ Revenue in prior year − 1) × 100
Forward growth is based on analyst estimates for the current fiscal year.
🏛️ Why is it important?
Rising revenue signals growing demand, business expansion, and market share gains – especially important for growth-oriented companies.
🧮 Calculation
🎯 What does this mean for investors?
- Growth is the engine of long-term value creation – especially in tech and growth sectors.
- What matters is not just current growth, but its sustainability.
- Forward projections reflect whether analysts expect continued momentum – or a slowdown.
📘 EBITDA Growth
📈 What is it?
EBITDA growth shows how much a company’s operating profit (before interest, taxes, depreciation, and amortization) has increased or decreased compared to the previous year.
🧮 How is it calculated?
Forward = (Expected EBITDA ÷ EBITDA from prior year − 1) × 100
The forward estimate is based on analyst projections for the current fiscal year.
🏛️ Why is it important?
Growing EBITDA indicates improving operational profitability – regardless of financing or accounting effects.
🧮 Calculation
🎯 What does this mean for investors?
- Strong EBITDA growth signals operational efficiency and scalability – especially during growth phases.
- EBITDA growth can be an early indicator of margin and earnings expansion – but should be assessed alongside revenue and EBIT.
📘 EBIT Growth
📈 What is it?
EBIT growth shows how much a company’s operating profit (after depreciation, but before interest and taxes) has increased compared to the previous year.
🧮 How is it calculated?
Forward = (Expected EBIT ÷ EBIT from prior year − 1) × 100
The forward estimate is based on analyst projections for the current fiscal year.
🏛️ Why is it important?
EBIT growth is a direct indicator of a company’s business performance – taking into account capital intensity through depreciation.
🧮 Calculation
🎯 What does this mean for investors?
- Rising EBIT signals improving operating profitability – even after accounting for depreciation.
- It’s especially important for evaluating companies with significant capital expenditures.
- Combined with revenue and EBITDA growth, EBIT growth provides a well-rounded view of operational progress.
📘 Net Income Growth
📈 What is it?
Net income growth shows how much a company’s bottom-line profit has increased or decreased compared to the previous year – both on a trailing basis (TTM) and based on analyst projections.
🧮 How is it calculated?
Forward = (Expected net income ÷ Net income from prior year − 1) × 100
The forward estimate reflects analysts’ expectations for the current fiscal year.
🏛️ Why is it important?
Net income is the ultimate measure of profitability. Growing net income signals stronger efficiency, cost control, and sustainable earnings power.
🧮 Calculation
🎯 What does this mean for investors?
- Stronger net income boosts valuation, dividend potential, and investor confidence.
- If profits stall while revenue grows, it may signal margin pressure.
📘 Free Cash Flow Growth
📈 What is it?
Free cash flow (FCF) growth shows how a company’s available cash – after covering operating expenses and capital expenditures – has changed compared to the previous year.
🧮 How is it calculated?
🏛️ Why is it important?
Free cash flow reflects real financial strength. Growing FCF indicates more flexibility for dividends, share buybacks, and reinvestment.
🧮 Calculation
🎯 What does this mean for investors?
- Declining FCF may point to rising investments, increasing costs, or weaker operating performance.
- Especially for dividend investors, FCF growth is critical – since dividends are paid from actual available cash.
- A negative trend isn't always bad, but it deserves closer attention.
📘 Gross Margin
📈 What is it?
Gross margin shows how much of a company’s revenue remains after deducting the direct costs of goods sold (like materials and production). It represents the company’s “raw profit” before fixed costs, taxes, and interest.
🧮 How is it calculated?
Or simply: Gross Margin = Gross Profit ÷ Revenue × 100
🏛️ Why is it important?
Gross margin indicates how efficiently a company can produce or procure what it sells. It is a key measure of product-level profitability and pricing power.
🧮 Calculation
🎯 What does this mean for investors?
- A high gross margin suggests strong pricing power and efficient production.
- Falling margins may signal rising input costs or competitive pressure.
- Compared to peers, gross margin offers insights into the quality of a business model.
📘 EBITDA Margin
📈 What is it?
The EBITDA margin shows how much of a company’s revenue remains as operating profit before interest, taxes, depreciation, and amortization.It reflects operating efficiency without being distorted by financing or accounting factors.
🧮 How is it calculated?
🏛️ Why is it important?
The EBITDA margin reveals how much operating income a company generates per dollar of revenue – independent of capital structure and tax effects.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBITDA margin reflects strong core profitability – before accounting distortions.
- It allows for effective comparisons across companies and sectors.
- A stable or growing margin signals efficient cost control and business scalability.
📘 EBIT Margin
📈 What is it?
The EBIT margin shows what percentage of revenue remains as operating profit after depreciation but before interest and taxes.
🧮 How is it calculated?
🏛️ Why is it important?
The EBIT margin reflects a company’s core profitability while accounting for capital intensity (e.g. machinery, infrastructure). It’s especially useful for comparing businesses with different levels of depreciation.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBIT margin shows that the company remains efficient even after factoring in depreciation.
- It’s especially relevant for capital-intensive industries.
- Stable or rising EBIT margins over time are a strong indicator of pricing power and business quality.
📘 Net Margin
📈 What is it?
Net margin shows how much of a company’s revenue remains as bottom-line profit after deducting all costs, interest, taxes, and depreciation.
🧮 How is it calculated?
🏛️ Why is it important?
Net margin reflects a company’s overall efficiency – across operations, financing, and taxation. It shows how much actual profit is generated from each dollar of revenue.
🧮 Calculation
🎯 What does this mean for investors?
- A high net margin means the company is not only strong operationally but also manages financing and taxes efficiently.
- Peer comparisons reveal business quality and competitiveness.
- Declining margins despite revenue growth can be a red flag for rising costs or inefficiencies.
📘 Free Cash Flow Margin | ex SBC
📈 What is it?
The Free Cash Flow Margin shows how much free cash flow a company generates relative to its revenue. In simplified terms, free cash flow is calculated as operating cash flow minus capital expenditures. The Free Cash Flow Margin ex SBC additionally accounts for stock-based compensation (SBC). While SBC does not represent a direct cash outflow, issuing shares as compensation can dilute existing shareholders. Therefore, SBC is deducted from free cash flow in this adjusted metric.
🧮 How is it calculated?
Free Cash Flow Margin ex SBC = (Free Cash Flow − SBC) ÷ Revenue × 100
🏛️ Why is it important?
The Free Cash Flow Margin shows how efficiently a company converts its revenue into free cash flow. Strong free cash flow can provide financial flexibility for dividends, share buybacks, debt repayment, or further investments. The ex SBC version additionally accounts for the economic impact of stock-based compensation and therefore provides a more conservative view of cash generation from a shareholder perspective.
🧮 Calculation
🎯 What does this mean for investors?
- A high Free Cash Flow Margin shows that a company converts a high proportion of its revenue into free cash flow.
- This can provide greater financial flexibility for dividends, share buybacks, debt repayment, or investments.
- The Free Cash Flow Margin ex SBC additionally accounts for potential shareholder dilution from stock-based compensation.
- The long-term trend is particularly important. Declining margins can, for example, result from higher investments, changes in working capital, or weaker operating performance.
📘 Earnings per share (EPS)
📈 What is it?
Earnings per Share (EPS) shows how much profit is attributable to a single share – and is one of the most important metrics for evaluating a company's performance.
🧮 How is it calculated?
The diluted share count reflects potential new shares that could be issued through options, convertible bonds, or other rights.
🏛️ Why is it important?
EPS is the basis for many key valuation metrics like P/E ratio, PEG ratio, or payout ratio. It enables comparisons of profitability across companies, regardless of their size.
🧮 Calculation
🎯 What does this mean for investors?
- EPS captures per-share profitability and is especially useful for comparisons over time or with analyst estimates.
- Rising EPS may signal consistent growth or share buybacks.
- Important: Always use diluted EPS for more realistic valuations – especially in companies with stock-based compensation.
📘 Free cash flow per share (FCF per share)
📈 What is it?
Free Cash Flow per Share shows how much free cash flow a company generates per outstanding share – after investments, but before dividends or debt repayments.
🧮 How is it calculated?
Free cash flow is calculated as operating cash flow minus capital expenditures (CapEx).
🏛️ Why is it important?
FCF per Share reveals how much real cash is available per share – useful for dividends, buybacks, or reducing debt. Unlike net income, free cash flow is harder to manipulate and often seen as a more reliable metric.
🧮 Calculation
🎯 What does this mean for investors?
- High FCF per share signals strong financial flexibility.
- It shows how much capital the company can effectively reinvest or return to shareholders.
- Particularly relevant for dividend payers and capital-efficient businesses.
📘 Short interest
📈 What is it?
Short interest indicates how many shares of a company are currently sold short – that is, borrowed and sold by investors who expect the price to decline.
🧮 How is it calculated?
It reflects the percentage of a company’s shares that are being shorted relative to the total shares available.
🏛️ Why is it important?
Short interest serves as a sentiment indicator: A high value may signal skepticism or bearish expectations – but also increases the potential for a short squeeze if prices rise unexpectedly.
🧮 Calculation
🎯 What does this mean for investors?
- Low short interest usually indicates market confidence in the company.
- High short interest can be a warning sign – or an opportunity if sentiment shifts.
- Especially relevant in volatile markets or ahead of key earnings releases.
📘 Employees
📈 What is it?
The employee count shows how many people a company employs worldwide – offering insights into its size, structure, and business model.
🧮 How is it calculated?
🏛️ Why is it important?
It helps assess operational scale, labor intensity, and cost structure. Combined with revenue and profit, it enables key metrics like revenue per employee or productivity.
🧮 Calculation
🎯 What does this mean for investors?
- A high headcount can signal operational complexity – but also significant growth capacity.
- Revenue per employee is a key indicator of efficiency.
- Especially useful for comparing tech, industrial, or service-heavy companies.
📘 Revenue per employee
📈 What is it?
Revenue per employee indicates how much revenue a company generates on average per employee – a key measure of efficiency and productivity.
🧮 How is it calculated?
The employee count is typically taken from the most recent annual report.
🏛️ Why is it important?
This metric helps compare business models – especially between labor-intensive and technology-driven companies. A high value suggests automation, operational efficiency, or strong value creation per head.
🧮 Calculation
🎯 What does this mean for investors?
- A high revenue per employee indicates a scalable and margin-strong business model.
- A low figure may reflect labor-intensive operations or lower value-add.
- Especially helpful when comparing tech companies to industrial or service sectors.
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Endava ADR — Q3 2026 Earnings Call
1. Management Discussion
Good day, and welcome to the Endava Third Quarter Fiscal Year 2026 Conference Call. [Operator Instructions] Please note, today's event is being recorded. I would now like to turn the conference over to Laurence Madsen, Investor Relations Manager. Please go ahead.
Thank you. Good afternoon, everyone, and welcome to Endava's Third Quarter of our fiscal year 2026 conference call. As a reminder, this conference call is being recorded. Joining me today are John Cotterell, Endava's Chief Executive Officer; and Mark Thurston, Endava's Chief Financial Officer.
Before we begin, a quick reminder to our listeners. Our presentation and our comparing remarks today include forward-looking statements including, but not limited to statements regarding our guidance for Q4 fiscal year 2026 and for the full fiscal year 2026, the impacts of headwinds facing our industry and business, trends in our industry, including with respect to developments with AI, enhancements to our technology and offerings, the benefits of our partnerships demand from clients for our technology services, our ability to create long-term value for our clients people, our shareholders, our long-term strategic positioning and our business strategies, plans, operations and growth opportunities.
These statements are subject to risks and uncertainties that could cause actual results to differ materially from those contained in the forward-looking statements. Actual results and the timing of certain events may differ materially from the results or timing predicted or implied by such forward-looking statements, and reported results should not be considered as an indication of future performance. Please note that these forward-looking statements made during this conference call speak only as of today's date, and we undertake no obligation to update them to reflect subsequent events or circumstances other than to the extent required by law.
For more information, please refer to the Risk Factors section of our annual report filed with the Securities and Exchange Commission on September 4, 2025, and and in other filings that Endava makes from time to time with the SEC. Also during the call, we'll present both IFRS and non-IFRS financial measures. While we believe the non-IFRS financial measures provide useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with IFRS. Reconciliations of such non-IFRS measures to the most directly comparable IFRS measures are included in today's earnings press release as well as the investor presentation, both of which you can find on our Investor Relations website or on the SEC website. A link to the replay of this call will also be available on our website. With that, I'll turn the call over to John.
Thank you, Laurence, and welcome, everyone. We appreciate you joining us for our third quarter fiscal year 2026 earnings call. I'll address first the issues that are top of mind for the investment community today. This has been one of the more challenging periods Endava has faced in recent years. Demand conditions remain uneven across several sectors, deal cycles continue to be extended and clients are scrutinizing technology spending more carefully than at any point since the [ macro ] slowdown began.
Against this backdrop, the primary driver of the quarter's miss and the lowered Q4 [indiscernible] was a slower-than-expected pipeline conversion. Factors impacting the revenue miss in the quarter and the lower revenue guide include clients located in the Middle East, delaying work due to the ongoing conflict, a slowdown in overall client demand due to the macro and economic environment arising from the complex. Finally, large complex outcome-based contracts taking longer to execute than planned.
During the quarter, we took a goodwill impairment of GBP 364.6 million, which is a noncash accounting adjustment, which does not impact our liquidity, delivery capability, client commitments or ability to invest in the business. Mark will provide additional details on these items shortly. Although we are disappointed by these outcomes, we believe it's important to distinguish clearly between near-term execution challenges and long-term strategic positioning. Over the past several quarters, we have accelerated our transition towards AI native delivery, expanded relationships with leading hyperscalers, deepened our presence in payments transformation and increased engagement with senior client decision-makers, pursuing enterprise scale AI initiatives.
What we are seeing now is a market moving beyond experimentation. Clients are increasingly looking for partners who can help them operationalize AI securely, integrate it into complex enterprise environments and connect investment directly to measurable business outcomes. Each new wave of technology change has triggered the same entrepreneurial reflex inside Endava: move first, learn fast and scale what delivers impact. The rapid emergence of artificial intelligence is simply the latest inflection point. And in recent quarters, we have concentrated talent, investment and partner collaboration on embedding AI across our delivery model to ensure Endava is ready to lead clients through what comes next.
Robust enterprise-grade IT services are essential for enabling AI leaders to scale their products safely and quickly. And thanks to our deep AI native delivery framework and expanding partnership with both OpenAI and Google, we believe Endava is well positioned to provide the secure integration, cloud orchestration and compliance layers that make that growth possible.
This quarter, we made strides in our go-to-market approach and in the evolution of our business model. We are transforming our go-to-market approach by engaging directly with key decision-makers to show how AI can accelerate their transformation priorities while deepening partnerships. We're moving to outcome-based contracts. For example, PGX and modular accelerate core for next-generation payment platforms delivered through Dava.Flow ties our success to measurable improvements in clients' payment operations.
We're continuing to progress selected client engagements as part of our AI native shift with Dava.Flow. We now have 12 clients where Dava.Flow is deployed as compared to 3 last quarter. We're seeing progress in our shift from a traditional digital transformation business towards an AI-driven business. These initiatives and others like them, have moved our AI-driven business, up from 5% of total revenue a year ago in Q3 FY '25 to 15% of total revenue in Q3 FY '26 or GBP 27 million. This shows the scale of the pivot Endava has undertaken during the past 12 months and now gives us an AI-driven base that we believe will continue to expand. Margins on its AI-driven business are higher than our traditional digital transformation business.
Let me share a few headlines for progress on this shift in the quarter. As part of our go-to-market pivot, we expanded our strategic partner network enlarging our market reach and solution set. I want to highlight our recently announced collaboration with Mastercard which combines Endava's AI-native engineering and industry expertise with Mastercard's global reach and data-driven products and services. Together, we believe we have a powerful engine to accelerate the adoption and scale of next-generation payments and immersive experiences for Endava's clients worldwide. We aim to unlock value at pace, bringing solutions to market faster for Endava's clients with initial focus on high-growth sectors such as insurance and health care, with additional attention on telco, mobility and travel.
On AI adoption, clients are moving beyond isolated productivity pilots. They now aim to create AI native initiatives inside their existing organizations and to launch entirely new businesses that embed AI in both build-out and day-to-day operations. Although these engagements sit at different ages of maturity, we're seeing increasing numbers implemented into production. Adoption is becoming more operational, more open and more tightly linked to measurable results. Over the coming quarters, we will focus on expanding our delivery portfolio with the goal of turning this interest into larger outcome-based programs.
As part of our go-to-market strategy, we are investing strongly in partnerships, particularly those with the hyperscale. By combining our depth of industry expertise with the scale of AWS, Google Cloud and Microsoft, we are producing accelerators and marketplace dilutions that tackle our clients' most complex challenges. We expect to launch more than 15 marketplace offerings this year, of which 10 are already live. And we are aligning Dava.Flow with each hyperscalers platform. Together, these initiatives are expected to cut time to value and help clients realize measurable returns on their technology investments.
Today, I want to share some of the momentum we're achieving with Google. Through our collaboration with Google, we have added new clients this year, particularly in financial services, retail and gaming. Enterprises are partnering with us to accelerate their cloud transformation and harness Google's AI capabilities. The long book insurance, we migrated and set up the AI security guardrails on an AI-driven underwriting platform for warranty and indemnity insurance, making a transformative step forward in digital underwriting built on Google Cloud. The solution uses advanced AI to automate key stages of the underwriting cycle from submission triage and risk assessment to pricing and due diligence while keeping underwriters firmly in control through a human-in-the-loop dashboard. Their innovation in AI-powered insurance and InsurTech is designed to support considerable productivity gains, cost reduction and speed to revenue for Longbrook Insurance.
Building on our enterprise AI progress, Google has invited Endava to participate in the Google AI Agent partner program, a program traditionally limited to their largest global system integrators. The initiative now open to a small cohort of AI disruptive partners recognized for expertise at Gemini Enterprise and Vertex AI is already generating new strategic engagements in North America, APAC and Europe. For example, we recently finalized an agreement to implement Gemini Enterprise at a leading U.K. high street bank. The project is expected to deliver an enterprise-grade agent gallery, the less the bank's developer community, register, govern and discover custom-built agents, fully integrated with Google data platforms such as big query and cloud storage. The solution is expected to provide timely, actionable data that improves efficiency and supports revenue growth at scale.
A year ago, we began applying our AI-enabled engineering expertise to long-standing client needs in payments, a domain where we have more than 20 years' experience modernizing gateway and merchant services estates. We believe the sector now faces 3 concurrent requirements: one, lowering the marginal cost of scaling; two, tightening operational efficiency and control; and three, keeping room to innovate around embedded commerce, omnichannel acceptance, platform consolidation and marketplace models.
Our answer is PGX delivered through Dave flow. PGX provides a reusable core, spanning digital acceptance, orchestration and routing, merchant portals, onboarding, settlement, fraud management, developer tooling, partner/ISV enablement and back-office services so clients can modernize selectively and still differentiate the product and experience level. Shared configurable components cut scaling costs. Standardized orchestration and back-office services boost efficiency and leaves headroom to innovate. Crucially, PGX supplies the data and workflow layer needed to introduce AI-enabled operations and a genetic commerce across the front office, onboarding, servicing and back office.
Built with a genetic AI and strict human-in-the-loop governance, PGX demonstrates the accelerated AI-assisted engineering can meet the quality and compliance demands of complex regulated payments environments. Early market reception is encouraging, with new signings in the last 3 months. Interest is already expanding beyond financial services into other sectors where modern payment capability is becoming central to customer engagement, efficiency and growth.
First, we have been selected as a strategic partner with Tyl by NatWest, NatWest Group's merchant payments arm to modernize and expand its payments acceptance platform. Under the partnership, Endava will deploy Dava.Flow, together with components of PGX to speed the rollout of new fully integrated products and services while improving flexibility, scalability and and end-to-end performance across the payments life cycle. Working jointly, the 2 companies have mapped a business and technology road map that link specific feature deliveries to defined market opportunities and associated revenue targets.
For NatWest, the partnership represents a material investment in strengthening its merchant payment offering. For Endava, this partnership adds an additional and significant large-scale complex engagement with a leading U.K. financial institution, reinforcing our credentials in payments transformation.
Second, PDX continues to gain momentum with 2 additional wins, one with a global payments provider and another with a pan-European energy retailer. Both clients chose the accelerator to cut operating costs, simplify estates and accelerate time to market. Dava.Flow supplies the delivery engine that converts these modernization programs into measurable commercial value and seamless [indiscernible] to ecosystem partners such as payment schemes, acquirers, POS hardware and compliance providers.
Some other client wins. We have also recently renewed our long-standing partnership with Slovenia's Ministry of Finance and Financial Administration through to 2028, bringing the relationship to more than 2 decades. Under the new agreement, we will continue to operate and enhance [indiscernible], the national tax portal that serves hundreds of thousands of taxpayers, integrates over 200 tax-related services and processes more than 12 million electronic documents each year. [indiscernible] delivers a secure integrated experience that has eliminated postage costs, accelerated processing times and given the authority near real-time visibility across its core revenue systems, demonstrating Endava's ability to modernize mission-critical high-volume platforms at a national scale.
The insurance company, North Standard, now regards Endava as a trusted extension of its technology organization, combining strong cultural alignment with deep technical expertise to deliver consistently high-quality outcomes. The success of the partnership and the value delivered by our team gave our client the confidence to extend the engagement for a further 2 years and expand into additional roles and delivery teams.
Our collaboration with a global brand and vehicle manufacturer has progressed from stand-alone engineering projects to an embedded partnership that is designed, built and operated cloud-native data platforms for connected vehicle services, real-time performance monitoring provided around-the-clock support services and delivered logistics systems covering more than 80 facilities in nearly 30 countries. We are currently using AI-enabled delivery frameworks to create modern production operation systems designed to improve life cycle management, enhance data visibility and raise efficiency in production critical environments, all underpinned by our disciplined approach to high-performance, scalable and compliant architecture.
Let me turn to Dava.Flow and AI projects. Over the quarter, Dava.Flow has shifted from exploratory use to enterprise adoption. We enhanced the framework through a combination of partnerships and by applying it in 2 large-scale live engagements. Firstly, a large-scale implementation engagement in a regulated high assurance environment. And secondly, the TechNexus technical operator program, a previously announced engagement in the payments fiscal. We have also continued to advance an AI-enabled human movement analysis platform for a leading high-performance sports organization with the quarter focused on validation, robustness and operational readiness.
Working closely with domain experts, we refined evaluation logic to improve alignment between system outputs and expert expectations, strengthen the core analytics pipeline, and expanded synthetic data sets to improve performance across real-world scenarios. We also introduced more structured measurements through accuracy dashboards, regular comparisons to previous versions and standardized evaluation against label data. Although still early, the increasing level of stakeholder validation underlines that the program is moving steadily towards a production-ready solution.
We applied the same agent-centric principles to a very different challenge, streamlining engineering knowledge for a European-based media and entertainment group. The client struggled with fragmented engineering knowledge locked in Jira, Confluence, GitHub and Microsoft 365, which lengthened incident resolution, delayed sprint planning and hampered onboarding. Endava delivered a Google Cloud agent-based pilot that unifies these sources behind a secure role-based natural language interface, automatically retrieving the most relevant tickets, code and documentation in one view. Since go-live, engineers report a roughly 60% reduction in time spent locating material and cut onboarding time by 30%, translating into faster coordinization and measurable gains in overall delivery productivity whilst also validating our agentic approach and further strengthening our partnership with Google Cloud.
To conclude, I want to thank our employees across Endava. Our teams continue adapting quickly to technological change while supporting clients through increasingly complex transformation programs. We remain focused on disciplined execution, operational accountability clients' delivery quality and positioning Endava for long-term relevance in the next generation of enterprise technology services. With that, I'll hand the call over to Mark, who will walk through this quarter's financial performance and our guidance for the rest of the fiscal year.
Thanks, John. Revenue for the quarter ended March 31, 2026, was GBP 178.5 million. The revenue miss in the quarter was due to opportunities looking beyond March. As John mentioned, there were several factors that impacted revenue this quarter, along with the revised Q4 outlook. Mainly clients located in the Middle East delaying work due to the ongoing conflict a slowdown in overall client demand due to the macroeconomic environment arising from the conflict and finally, large complex outcome-based contracts taking longer to execute than planned. This compares to GBP 194.8 million in the same period in the prior year, representing an 8.4% decrease. In constant currency, our revenue decreased 6.4% from the same period in the prior year. .
Loss before tax for the 3 months ended March 31, 2026, was GBP 372 million, which includes a noncash goodwill impairment of GBP 364.6 million compared to a profit of GBP 13.6 million in the same period in the prior year. Our adjusted PBT for the 3 months ended March 31, 2026, was GBP 3.2 million compared to GBP 24.6 million for the same period in the prior year. Our adjusted PBT margin was 1.8% for the 3 months ended March 31, 2026, compared to 12.6% for the same period in the prior year. Our costs increased in the quarter due to higher go-to-market investments and an increase in the bench as we are training staff in AI and Dava.Flow skills. This is a key investment in skills for our new AI-driven business.
The market capitalization of the company and the reduced outlook has required us to assess the carrying value of goodwill and the deferred tax asset for U.K. tax losses in the U.K. As a consequence, we have taken an exceptional charge of GBP 364.6 million in relation to the impairment of goodwill and GBP 23.2 million regarding the derecognition of the deferred tax asset. Those charges are noncash and one-off in nature.
The deferred tax asset derecognition because it has occurred partly through the financial year impacts our adjusted tax rate, which for Q3 is 17% and is expected to rise to 37% in Q4 leading the estimated full year adjusted tax rate at around 25%. These adjusted tax rates do not change the amount of cash tax we are paying. Our adjusted diluted earnings per share was 5p for the 3 months ended March 31, 2020, calculated on 52.2 million diluted shares as compared to 34p for the same period in the prior year calculated on 59.4 million diluted shares.
Revenue from our 10 largest clients accounted for 40% of revenue for the 3 months ended March 31, 2026 compared to 39% in the same period last fiscal year. The average spend per client from our 10 largest clients decreased from GBP 7.5 million to GBP 7.1 million for the 3 months ended March 31, 2026, as compared to the 3 months ended March 31, 2025, representing a 5.6% year-over-year decrease. Office movement FX contributed to a 3.7% year-over-year decrease due to U.S. dollar weakness in the quarter.
In the 3 months ended March 31, 2026, North America accounted for 38% of revenue, Europe or 23%, the U.K. for 33%, while the rest of the world accounted for 6%. Revenue from North America decreased by 5.5% for the 3 months ended March 31, 2026, over the same period last fiscal year. The decrease was driven by an FX headwind of 6.1%. Comparing the same periods, revenue for Europe declined 3.6% due mainly to weakness in payments and TMT, and the U.K. decreased 15.4% due mainly to the reclassification of the large payments client from the U.K. to North America as the relationship with the client is now based there, which was mentioned last quarter. The rest of the world decreased 1.8%, driven mainly by the payments and other verticals.
Our adjusted free cash flow was negative GBP 3.1 million for the 3 months ended March 31, 2026, from a positive GBP 17.5 million during the same period last fiscal year. Free cash flow was negative in the quarter, mainly due to an increase in receivables as a large proportion of the billing for the quarter was issued in March. We anticipate collecting the majority of this by the end of June.
Our cash and cash equivalents at the end of the period totaled GBP 48.4 million at March 31, 2026, compared to GBP 59.3 million at June 30, 2025, and GBP 68.3 million at March 31, 2025. Our borrowings increased to GBP 195.8 million at March 31, 2026, from GBP 180.9 million at June 30, 2025 and GBP 136.5 million at March 31, 2025, primarily to support the funding requirements of our share repurchase program. Capital expenditure for the 3 months ended March 31, 2026, as a percentage of revenue was 1.6% compared to 0.6% in the same period last fiscal year.
Turning to the guide for the remainder of the fiscal year, as John mentioned earlier, we have lowered the Q4 guide due to slower-than-expected pipeline conversion, which is most marked in banking and capital markets across all of our regions.
Now moving to our outlook. Our guidance for Q4 fiscal year 2026 is as follows: we expect revenue to be in the range of GBP 181 million to GBP 185 million representing constant currency revenue decrease of between 3.5% and 1.0% on a year-over-year basis. We expect adjusted diluted EPS to be in the range of 9p to 13p per share.
Our guidance for full fiscal year 2026 is as follows: we expect revenue to be in the range of GBP 721.8 million to GBP 725.8 million, representing constant currency revenue decrease of between 60% and and 5.0% on a year-over-year basis. We expect adjusted diluted EPS to be in the range of 45p to 49p per share. The above guidance for Q4 fiscal year 2026 and the full fiscal year 2026, assumes exchange rates on April 30, 2026 when the exchange rate was GBP 1 to USD 1.35 and EUR 1.16. This concludes our prepared comments. Operator, we are now ready to open the line for Q&A.
[Operator Instructions]
Our first question today comes from James Faucette at Morgan Stanley.
2. Question Answer
Thank you very much wanted to dig in quickly into 2 topics. -- a little bit unrelated or I mean, always related, but separate. First, in terms of customer decision-making, I mean, obviously, there's a lot of AI and valuation, et cetera, going on. And you talked about projects moving to production. But we're still seeing kind of pressure on the rest of the budget and spend. And you talked about obviously extending decision cycles. Can you just help us bridge those and when or under what conditions you would expect to see that movement to AI production start to benefit you and we can start to see real movement on the bookings side.
And then on capital allocation, can you just talk about how you're thinking about what you should be doing around your debt and borrowings, especially -- obviously you've tried to take advantage of where the stock is with buybacks, but just wondering if delevering is an increasing priority, et cetera.
Thanks, James. So let me pick up the customer decision-making question that you had. We are seeing much more substantive AI-driven deals coming through. We announced NatWest and the collaboration we have with Mastercard in the opening remarks. And it's visibly growing as a proportion of our business, time what it was a year ago, taking it to [ $27 ] million in the quarter or 15% of the total business. So it's now becoming a substantive element of the business that we expect to grow from.
We're seeing that in respective deals that are coming through. They are more complex in nature, outcome-based, looking at serious transformation across the customers' business, and they've taken longer to close and get started. We do use AI very much as part of that sales process. So actually establishing what is going to be done, is a very AI-driven process.
You are correct. There is pressure on discretionary spend. I think in Endava, we are more exposed to that than many of our peers, a lot of our business is more in the discretionary camp. And we continue to see downward pressure on that. You can see that in the underlying shift of our business from our traditional business, digital transformation business, towards the AI-driven business that I highlighted in the opening remarks. So obviously, the digital transformation business has been declining whilst we've been seeing the AI side ramp up. However, that is the shift. That is the pivot that we are deliberately making as a company. And we're very comfortable to be seeing the AI-driven arena growing. Mark, do you want to pick up on the capital allocation?
Yes. So the cash generation in the quarter was disappointing. As I said, most of the billings arose in March. So the collections will take place between now and June. So we anticipate a significantly better cash flow generation in Q4. But notwithstanding that, leverage is something we want to focus on reducing. We do have a refinancing coming up during the course of FY '27. But looking at the wider funding of the business, it is something that we will consider as part of that. .
Our next question today comes from Bryan Bergin at TD Cowen.
So maybe a bit of a follow-up as it relates to the unplanned pressure here. So I understand the Mid East volatility causing the discretionary issues and large deal opportunities taking longer than planned. But in addition to that, is there vendor consolidation and broader shifts in client priorities playing out where the offering just isn't as robust yet as competitors. Really trying to understand how much maybe transitory timing dynamic versus a function of client setting programs and shifting those priorities elsewhere or the consolidation share loss or even other factors like over competitive pricing in the market? If you could just comment on that.
So we're not seeing a huge vendor consolidation headwind. The pressure seems to be coming from as we deliver more productively. We've been talking about our shift to AI native where more than 75% of our staff are now using AI in their daily work, and that is driving higher productivity. Clients are harvesting a little bit more of that benefit than we would prefer as we are not reinvesting it. But I think that is also part of the shift as they're looking to a much more substantive AI-driven transformations and that's very much part of the pivot that we are focusing on. Those projects are taking longer to come through. They continue to take longer. The thing that I'm highlighting is that they are coming through, and we are getting them signed there.
Okay. And then my follow-up as it relates to some of the actions by the foundational model provider. So obviously, with news flow around open AI deployment companies, some of the joint ventures, the Anthropic and OpenAI are looking to set up as well as they're looking for consulting and engineering talent I guess there are a couple of avenues here. But what's your perspective there? Just considering your base of engineering talent, it seems like it would be obviously an attractive potential opportunity for them to lean into partners like you more. But as you think about kind of competition versus cooperation kind of where do you land? What are your thoughts on them?
Yes. So we actually -- number one, I think, the foundational model companies are actually showing that they need services partners for implementation in the real world, and they're looking for how to accelerate that and push it along and that's the reason for some of these deploy co models that they're coming up with. We are in conversations with them very, very much. The expectation is that, that will become a new channel to market for us as they utilize our skills and capabilities in order to drive the commitments that they will be making to clients. .
So we see it much more as being a collaboration opportunity, a go-to-market opportunity than a competitive activity. A lot of what they're focusing on is complementary to what we do in terms of the heavy lift engineering capabilities that we've built in the AI space, and they recognize that.
And our next question comes from Puneet Jain with JPMorgan.
I want to follow up on Bryan's question on revenue weakness. I want to focus on both related to your estimates as well as your peers. So I understand that the Middle East surprised you in this quarter, but revenue has come in below your expectations many quarters in the last 3 years. So do you think like you need to change anything in the planning process, like to get a better handle of quarterly revenue or your -- even the quarter as well as full year guidance.
Yes. I mean the Middle East arena was not something we saw coming, we'd actually invested pretty heavily over the past 12 months. and had deals ready to sign literally about to kick off when the conflict kicked off. And it literally stopped all activity across our client base. And that had a noticeable impact on Q3 and a bigger impact on Q4.
Your question about the timing of how -- essentially how quickly we get these deals through the pipeline and into revenue is 1 that we're paying a lot of attention to. We're very sensitive to it. If you look at our Q4 guide, we've put a lot of work into the client conversations and the project plan, if you like, of getting these deals signed and the revenue ramping. So it is something that continues to need a lot of attention, and we definitely got caught by that in Q3.
Okay. Got it. And then it's been like, give or take, like a couple of years since you acquired Galaxy, and now you are also pushing ahead with this AI first model, AI first delivery. Talk to us about change management within Endava, like motor employees, motivating them to embrace AI to increase like this new way of delivery while also like the stock obviously has been down so much. So -- and some of those employees might also be worried about their jobs, given like the news flow around AI. So talk to us about the change management with the Endava, like how are you managing all those things?
Our approach to change here has been a pioneer and rollout model. So in each area, as we're driving change, we get a smaller group of people who pioneer what good looks like and then roll it out across the organization. So the first of those that we talked about around 18 months ago was the shift to AI native. That was done by getting small teams across each part of the business to engage with AI at that stage.
It was the agentic -- sorry, the generative AI that was in play and how to create GPTs, and how to drive usage across that each part of the business. We then moved into a rollout phase where adoption was pushed right across the business with everyone having access to -- we went for that GPT Enterprise as our standard across the business. And over the following 3 to 4 months, we saw usage across our staff base to move above 75% of people using it every day in their job, which was our objective to have that AI native shift.
The big shift that we're pushing at the moment is Dava.Flow. Now we've been developing Dava.Flow over the last 18 months or so. You'd be aware that we came out with our own genic solution ahead of the large vendors coming up with agenetic models. And so we were using that to initially start keeping how Dava.Flow would work. Dava.Flow being our method around how you develop business solutions and ultimately, software and agentic solutions in an agentive world where most of the work is done by agents rather than buy people that shift from agile, if you like.
So those pioneering groups actually defined Dava.Flow, created all the prompts, et cetera, that go into it, created the context warehousing, all of the pieces that go to make Dava.Flow work. We pushed that into our payments gateway, which I've talked about on the opening remarks so that we had an internal project where we could really drive not only the payments the way we were building but also the development of Dava.Flow.
And then over the last 6 months, we started to shift to spreading that step-by-step across the organization. I highlighted we've now got 12 clients using Dava.Flow in [indiscernible], up from 3 last quarter. So that's the rollout speed. Within the organization, we've got over 1,000 engineers who are actually using a training on Dava.Flow now or over 10% of our direct staff, and that's in anticipation of the greater use of Dava.Flow that we anticipate coming through both Q4 and as we move into Q1. All of that within a change management framework, we call it our Keystone management program that is driving that change.
And our next question today comes from Nate Svensson with Deutsche Bank. .
I wanted to ask about another one of the factors you called out is driving the miss and guide down specifically the outcome-based contracts taking longer to execute. So hoping you can give some detail around what exactly is taking longer to execute here. And then I guess more broadly, you've clearly talked a lot about the shift to outcome-based contracts over the last few quarters. So I guess I'm just wondering, if these problems or the things that are taking longer to execute are actually fixable or transitory? Or is there any sort of dynamic where clients just don't want to shift to outcome-based models to try and realize benefits on pricing or efficiency or your traditional time and materials contracts.
Yes. So we're not seeing that latter problem. It's just these are, by nature, very large transformative engagements in the tens of millions type category and nailing down. We're using AI to help give clarity on what it is that we're going to be delivering and getting that much earlier in the cycle and expecting that we would see a 3- or 4-month sales cycle from having shaped what it is that we're going to be delivering and how AI is going to be making an impact.
But seeing that turn into 5, 6 months to get the deals closed. There is an element of clients being on a learning curve, their legal departments, worrying about issues, worrying about regulation, worrying about how to contract these deals that is becoming visible and it's taking longer. We expect that to ameliorate as people become more familiar with the issues and can get these things through faster on their side. We're not seeing it being because they don't want to engage on outcome-based deals. These things are progressing. We announced some in the opening remarks, and there are others under the covers that a little smaller. We are seeing them progressing. They're just taking longer than expected.
Okay. Got it. And then for a follow-up, I wanted to ask specifically on 2 of the verticals. So I guess, first, what's happening in banking and capital markets that vertical have been growing nicely for you and the growth fell pretty dramatically in 3Q. I think you mentioned worse pipeline conversion, but more color would be helpful there. And then in health care, specifically, I think on the call last quarter, you talked about a large health care clients slowing down spend in 3Q, but you had expected them to return to spend in 4Q. So it looks like that played out in 3Q, but is that specific client still expected to return to spend here in the fourth quarter? .
On the health care side, yes, we expected one of our larger clients to slow, which they have continued to do. So they came in as expected. And we expect that actually to continue slowing into Q4. There is some offset to a certain extent as we go into Q4 because another client is actually growing quite quickly. The trouble is the decline of the larger client has happened more quickly than anticipated with the ramp-up of the newer client -- larger clients. And then we do have a ramp down from an existing client from Q2 through Q3 and Q4. So you're right, we've sort of come off a good sort of Q2. There's been a step down because of those sort of dynamics, but it stabilizes as we go into Q4 as anticipated in the guide. .
Got it. Anything on banking and capital markets or...
Yes. Sorry. So in banking and capital markets, we were pretty sort of stable through Q1, Q2. We did see a step down. This -- as we went into Q3, I think a [ couple of million, 1.5 million ] or so partly 1 client coming off project work that we've been doing for them and also some lumpiness in the delivery profile for another client. But we do expect recovery in BCM into Q4. But the point is it's not as strong as we were anticipating in the original guide that we set in February. And that sort of slowdown in banking and capital markets is most pronounced in the U.S. and the U.K. although we are feeling it to a smaller extent in the other geographies, but it's more significantly in U.K. and North America. .
And our next question today comes from Jonathan Lee at Guggenheim Partners.
Given what we saw in the quarter versus the mid-February commentary around 95% contract and committed visibility what are you seeing quarter-to-date in April and May on both demand and the slip contracts? And what's the coverage on the 4Q range today? What gives you confidence in that sequential improvement into 4Q that's implied in the outlook?
So if go back to Q3, we had a range of [ GBP 185 million to GBP 182 million ]. We were saying the contractual coverage at the high end I think it was about 90% and it rose, I think, about 92% for the low end of the guide. So the pipeline to convert in both high and low was about GBP 19 million and GBP 16 million, and we converted about GBP 13 million. So you've got a conversion which is below what we anticipate is at the low end, it's about 80%.
Now for the high guide in Q4, we have contractual -- contracted and committed of 95% for the low end of GBP 181 million, we have 97%. So that leaves about GBP 9 million at the high end to convert and 5 mill to convert at the low end. We have 3 or 4 opportunities that are sort of sizable. But we have taken a view that -- some of those are not going to convert as part of the high guide and then a severe downside, that's 1 converts when we get to the low end of the guide. So we have been sort of conservative, I believe. I know we have missed in the quarter with that sort of outlook. And in terms of the step-up, it's something like at the top end of the guide about I think, 3.5%. We do have some movement in terms of working days between the quarters, that actually does help us somewhat sort of step-up is not as strong as it may appear when you look at it on an absolute sort of growth basis.
But there is always pipeline in our figures, it's the nature of the business model. The issue going back to sort of John's initial comments has been the predictability of when opportunities convert.
Thanks for that color, Mark. And just as a follow-up, can you help us think through some of the earlier comments around AI productivity harvesting. As clients become more aware of the efficiency gains that AI is enabling, how do you think about the structural durability of pricing and contract profitability over the longer term, particularly as clients may look to extract more of those gains at the table. What's sort of the offset mechanism there?
I think the offset mechanism is the change in the business model, John was outlining in terms of AI-driven models, which is basically outcome based. Yes, there's been pressure in the traditional T&M space. We are being more productive. It sort of erodes revenues. But we're moving more to an outcome-based longer-term duration partnership arrangement with large clients, where we have stronger visibility of revenue and we can capture more of that benefit from the rollout of Dava.Flow to path more of that benefit. And therefore, sort of protect margins.
I think the sort of key thing. I mean, these are -- we're not going to quote numbers at you, but the new model revenue margins are significantly higher than our existing T&M margin figures, which are under pressure. It's a question of can we accelerate the new AI-driven business to offset that decline that we're seeing in the, let's call it, the traditional digital transformation business, which is largely T&M.
I mean I think the other thing just to add to that, it's not specifically around the productivity and the model style and the pricing attached to it. But our utilization availability is running much lower as we're going through this pivot we're investing in skilled retraining and so on. And actually, we need to do that to prepare our workforce for the enemies coming through. It's not an optional extra, and that is part of the -- or a big part of the margin compression that you're seeing rather than specifically a pricing issue. Pricing has been actually pretty...
It's pretty stable when you look at it also on an average work going measure. I think this is a sort of issue that sort of transition, the usual metrics of billability and average rate per work day are sort of flying a little bit as we go through this change.
And our next question today comes from [ Matt Desert ] at William Blair.
This is Matt, on for Maggie Nolan. I guess to follow up on that last point on AI, how are you defining your AI revenue? I guess what growth trajectory are you underwriting there? When do you expect that could become a majority of the business mix?
Yes. So we've pulled this out as what we're calling AI-driven business where AI is at the core of the business transformation proposition, often outcome-based typically, sold at the top of the C-suite. The 2 examples, NatWest and the collaboration with Mastercard and a number of the Google Cloud deals in the opening remarks fall into that category, and we're very focused on developing this type of pipeline.
It needs let me call them forward-leaning organizations who are up for this acceleration, and that is a subset of the market. It's not everyone who's up for that right now. But where we find those people we're getting really, really good traction around the AI-driven change. I would highlight, it's different to the AI native measure that we've previously published which has stabilized in the sort of 75% to 80% mark, which is a measure of how people are using AI in the organization. And if they're using it on a daily basis in their work, we're counting that as AI usage. That enables strong productivity, but it's not the same as the sort of AI-driven business transformation that we are classifying here.
Got it. And then I guess on the margins, what specific levers do you have to protect or expand margins given the revenue pressures you're seeing as you pivot the business? And how do you think about that going into next year?
Margins, well, we sort of managing to 2 dynamics, which is we'll call it the traditional T&M business and the -- which we can call the digital transformation business. So the way you've always sort of managed margin pressure there is actually just looking at cost and getting visibility, which we can do. You do have to have good visibility so that it's not disruptive, but that is definitely a lever.
The other offset is to actually build the new more quickly with the AI-driven work where you have longer-term visibility year-to-year. You have more control over how you deliver that work because it's not on a time and material basis. And it's about the deployment of Dava.Flow to capture that sort of benefit. So those are the 2 levers that you can -- you apply basically, is managing that sort of dynamic.
And I expect over the coming years, this sort of split between what is fixed price and what is T&M is going to start to shift. We don't have any figures at the moment, but we definitely do know at the moment that our T&M proportion of revenues is starting to come down. So I think last year, it was about GBP 77 million on a full year basis, FY '25. It's probably about 71% of our revenues in this quarter. So that is an indication of the shift that is going on where we are contracting through fixed price outcomes, not all through Dava.Flow. But that is one way that you can protect margin going forward about growing the new more profitable work.
And our next question today comes from [indiscernible] with HSBC.
I just want to ask on the update regarding your go-to-market with OpenAI. You have a partnership. Do you have any update on how it's going?
Yes, we continue to have a really strong relationship with OpenAI. It's global in nature, driven out of the -- out of the U.S. The conversations that we had with the new deploy code, a part of that relationship and through that, putting together thoughts and plans on how we're going to work together with the new deploy code. We continue to get early sight of some of the models and so on that they're putting out so that we can prepare go-to-market capabilities alongside them, and we continue to bid together on opportunities, some of which were in the large complex space. .
And that concludes our question-and-answer session. I'd like to turn the conference back over to John Cotterell for any closing remarks.
Yes. So thank you all for joining us today, and I look forward to speaking to you in September. .
Thank you, sir. That concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your lines, and have a wonderful day.
Endava ADR — Q3 2026 Earnings Call
Endava ADR — Morgan Stanley Technology
1. Question Answer
Thanks for joining us here as we are wrapping up the -- about to wrap up. We still have a keynote after this presentation here at the Morgan Stanley TMT Conference for 2026 on Tuesday, so the second of 4 days. Very thankful to the Endava management team for joining us. Before we get started with them, I'm James Faucette, senior IT services analyst here at Morgan Stanley. And we're very pleased today to have co-CEOs of Endava, John Cotterell and Alastair Lukies. We also have Mark Thurston, CFO.
Before we get started with the team, though, I do have an important disclosure to read. Please see the Morgan Stanley Research Disclosures website at morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative.
So I guess with that, I'll just kind of open it up. I'm sure you've gotten the same question multiple times as have we. And it starts with, hey, the recent commentary that you gave coming into the calendar year was actually really encouraging. And I'm wondering if you can walk us through the key factors behind that change. And in particular, what are the things you're looking at that inspires confidence in a stronger fourth quarter pipeline conversion rate?
Sure. I mean we've been, as I've articulated fairly frequently over the last year or so, on a strategic focus around, number one, getting into the C-suite and having conversations with our clients about what it is they're trying to achieve with their business and how AI can help drive that. Secondly, around moving more towards outcome-based contracts, aligned with those client objectives that we're talking about. And thirdly, establishing an AI native approach to delivery, which we call Dava.Flow.
When you put all of those things together, it's a very powerful proposition to clients. And that's what's been generating the pipeline that is giving us the confidence in the guide that we have put forward.
And Al, do you want to just expand a little bit on the sort of client-facing side and how the reactions that they're having to that?
Yes. I mean, I think, we -- a lot of our peer group and a lot of people in the technology world, certainly in this hype. We're in at the moment are selling a fascination or a religion around the technology. We're being very disciplined about talking to the customers, actually listening to the customers, two ears and one mouth, about what it is that they're trying to achieve with their business and then seeing where we can apply AI.
So if I look at the shape of the business and the way we're engaging in the C-suite now, recent wins like Paysafe with the CEO, Nexus, the biggest shift in the payments industry probably for 50 years. The rest of the pipeline where what I'm seeing is CEOs saying to CIOs, "If you can go and get me efficiency using AI, knock yourself out, right? You cut my costs. But in terms of ideation and where we can go in terms of competitive advantage, I want to talk to an expert in the field that's doing that." So it's a very different approach to, I think, most companies in the space, and it's starting to resonate.
Got it. So if that's the message, Mark, how do you bring that together and think about what the implied assumptions are of that current pipeline and what portion of it needs to close to get to kind of the targets you've set for the June quarter?
I mean the June quarter in terms of Q4, there is a step-up, which we articulated certainly quarter-on-quarter, 8% on Q3. Part of that is because of the number of days in the quarter. So we get about 2%. So you're looking at 6% uplift. And this is all at the sort of midpoint. It's underpinned contracted and committed. I think we're about 70%, 75%, which is typically normal. It's also underpinned by the recent sort of deals that we have won as well.
So we have great confidence in it, but it does also have a wide range on it, something like $10 million, which at this sort of stage in the year, we would usually sort of narrow because experience has told us over the last couple of years that things cannot play out as you might think they do. So it's underpinned by the deals we won earlier in the year, and it's the strength of that pipeline, that conversion assumption.
Got it. So I want to pressure test a few things, starting with kind of your largest clients, and then we'll talk about geographies outside of your top 3 customers. But how have spending intentions been across your top 3 customers? Is this message of the pieces that you can bring together, John, resonating, including with them? And how are they thinking about how much they can you engage with Endava and what the opportunity set is there?
Yes. So that's exactly what we're finding with our largest customers, is that, that level of conversation around what is it you're trying to achieve with the business and us working through how we can bring the appropriate programs, technologies, outcome-based contracts, the Dava.Flow approach to bear, is getting huge interest and huge traction. It's not only our existing customers that we're having those conversations with, but that's where we've had the earliest traction and are seeing the fastest returns out of those conversations.
Are we on track to be able to stabilize the businesses with those largest 3 clients? Or is there still kind of work to be done to flesh that out and to get them kind of on track with some of the newer capabilities of Endava, you think?
So I would say, yes, there's a lot of stabilization that's been done. There's been contracts and extensions and SOWs opened. We covered that on the earnings call. And actually lots of opportunity because the clients are also going through significant change themselves in their businesses and in their marketplaces and in the investments that they're making. And we're seeing opportunities come off the back of that, which we haven't really got in the forecast.
Got it. Interesting. Interesting. And then what about by geography, outside of these top 3 customers. Can you look across your -- where you're operating globally and say, "Oh, this particular geography is strong, this one is weak, this one is so so." Like I'd love to hear about what you're seeing geographically.
I'll let you take.
Well, it's sort of dominated by the end industry vertical. So we're seeing strength somewhat resurgence in financial services. And for us, it's payments, we've just been talking about, but also banking capital markets and insurance. And it's dependent very much on the relative strength of those sectors in each of the sort of geographies.
So we're a U.K. heritage headquartered company. We see sort of strength in the U.K. basically. We're seeing also come through in rest of world. I mean we were just referencing the Nexus sort of deal that we announced on the earnings call. So that is causing some uplift in that geography. And also North America, we've -- it's our biggest geography as a percentage of revenue. There's also a lot of momentum there as well.
Got it. So I want to spend some time just talking about the AI initiatives within Endava. Obviously, key and central part of your investment focus and where you're putting resources, becoming more AI native. What are the objective KPIs you guys will use to prove those investments are translating into higher win rates, faster sales cycles, better unit economics, et cetera? Like what are the things that you're tracking and that maybe you can share with us at least from time to time?
I think you just covered a few of them. But yes, I mean, obviously, seeing that come through in revenue growth actually driven by those capabilities. And we're tracking which projects we're using the Dava.Flow on, et cetera, so that we can actually track the impact that it's having. I think margin improvement, so top line growth. Margin improvement, we'll be able to see that on those projects, many of which will be outcome-based that we're actually able to track a margin improvement coming through. So on average, actually lifting the overall margin of the business as we shift to more outcome-based and Dava.Flow-enabled solutions that we're putting in place for the clients.
So -- and those were good financial metrics. What about operational metrics? Is there some sort of productivity metrics or output-related metrics, et cetera, that you're seeing and can talk about?
Yes. Operationally, we've sort of drunk the Kool-Aid ourselves and brought a lot of efficiency to our legal department, to our finance department, to our platforms, to our sales process. So we've reduced the number of salespeople we have substantially and replaced them with higher-quality C-suite engagement salespeople.
I think that one of the key KPIs that I would be looking out for is longevity of partnerships. Because I think if you look at Paysafe and Nexus, these are 5- to 7-year partnerships and none of us know where the world is going to be. But if we're still in that dialogue contractually and we're finding efficiencies through Dava.Flow, our ability to create that operational leverage and the unit economics that we're searching for is far greater than getting back into a bidding war every year against competitors who are also desperate to win those accounts.
So my job here is to make sure that people that want to come on the journey with us are prepared to put some skin in the game. And back in the day when I was building companies, that was really sort of joint-venture model. So like, are we really going to partner here? We're not setting up loads of joint ventures, but the culture and the cadence of the relationships is much similar to a joint venture.
And how -- like -- and it seems to me from the outside that, that would be conducive to some of this outcome-based pricing and projects, et cetera. Is that right? And like how do you -- and so on the flip side of it, if you're trying to put together outcome-based agreements and as you're saying, Al, your putting -- and that's resulting in some JV, et cetera. But how does that survive? Or how is that reevaluated, particularly if it is a longer duration contract and beyond the horizon of what you could really see?
Look, I think you have to be -- particularly, in a hype cycle, you've got to have some good self-awareness. The history shows us that the projected change is never as quick as people expect, but it's more profound in the long term. And I don't think this is going to be any different. So we've designed the new business structure in a way to say those that are doing more traditional Endava services, which, there's tons of appetite, right? You have got to make sure there's no decline because it's the cash flow from that, that's helping us fund the new.
So if a relationship with a strategic partner starts in year 1 with 90% traditional Endava, 10% Dava.Flow, can we get to 50-50 by year 3? So they're the levers that we have to pull to get the blended margin back up to the 20% pluses, into the 30s where we've been before, but it's a blend. And it's -- people keep talking about flicking a switch. It just -- it never happens like that.
Right. So borrowing from some of that consulting developed adoption curves and emotion that goes with that. How do you -- what do you need to do then to -- if we're in the hype cycle, to limit the depths of the valley of despair and as people kind of come to grips with what the realities are versus impressions and then ultimately make that profound change.?
I joined -- just quickly, sorry, and then I'll pass it. I joined because I believe that John pivoted earlier than anyone else. So I think we've been through our trough. I think our trough is done. I actually think the trough of disillusionment, we're now coming back into the plateau and starting to scale. And I think a lot of other people are about to enter it.
Go on then.
Go on then.
That's exactly what I was going to say. The -- and if you look at the sweet spot for us, is that combination of we're talking to the CEO, very senior in the C-suite. We're understanding what they're trying to do to their business, what their aspiration is, what the game-changing thing is they're trying to do. We're bringing an output-based outcome-based contract to bear on that so that the client sees we've got skin in the game, we were all pulling in the same direction, but also is giving us opportunity to make wider margins.
And then when you're putting the Dava.Flow capability, which is a method, by the way. It's not some platform, we've been using in AI, and I'll come back to that in a moment, if you want. When you get that sweet spot of putting those 3 things together, you actually are giving yourself the opportunity to drive much more significant growth with the client, much higher margins and strong execution. And we have very, very high NPS score as a company. That is because of our execution. And that's why clients trust us and actually go, "Do you know what? I'm going to believe in you guys to actually drive this change for me."
So John, talk about Dava.Flow from your perspective, like what is it? And how does it differentiate what you can deliver to the customer?
So, let me wind back a moment. If you look at the digital wave that we wrote for 20 years, that was largely an Agile-based method, right? And Agile is all about coordinating human beings in the creation of software and doing it in an iterative way. That is completely inappropriate to an agentic AI delivery model.
Dava.Flow is the creation of that delivery model that you need for an agentic solution. So upfront, you use agents to help envision what new products or capabilities or strategies a client should be searching around, coming up with options, helping them choose. The next phase is around creating the backlogs, doing the specs, getting the regulations, the governance, the coding standards, everything together that then becomes the ability to do the prompt engineering and the context engineering and all the rest of it that goes into the next phase where the agents actually build the code, governed by people. And then the final phase is the -- you're getting into the support mode of systems that have already been taken live and the improvement of them and so on.
Now that is a very different approach to an Agile approach. It's completely different. Culturally, it's different. Agile teams, when they start, they get together. Within 2 weeks, they're kicking code out. The -- in an agentic model, you're not doing that. You're creating an understanding of what you're trying to build and you put weeks into that, and then you have a very fast build and refinement process. So it's culturally different. It's a different conversation with clients, different expectations to manage and so on. And needs codifying it in a lot of detail so that an engineer who is picking something up actually understands the role they're playing in a large program and the phase that they're in and what they need to do. We have captured all of that. And we found our people on very fast learning curves, using the capabilities that we put in place, to actually make it work. We're not seeing other people do that yet.
Right. So can I ask you, like it's a potentially incredibly important point that you're making there. So it seems like most of the metrics I hear thrown around about effective use of agentic AI or that kind of thing, basically just comes down to speed of code production, right? But it sounds like what you're saying is like if that's your focus and your metric, that may be a key risk of pushing you into this trough of disillusionment because you think it's just about speed of production, whereas like it's really the outcome and getting that right from the get-go instead of trying to iterate your way there. Is that fair? Or is that a lacking upfront?
It's absolutely fair. And it's particularly true in an enterprise environment, right? I think people can look at what is happening at a consumer level or an individual who can use these tools to create a lot of code very quickly, the vibe-coding type thing. That does not translate into an enterprise environment easily where you've got regulators, you've got governance, you've got security issues, you've got legacy systems, you've got data problems. All of those things have to be integrated into an architecture and a design that can be fed into the agents so that they code something that works. And it's capturing all of that, that Dava.Flow is all about.
One of my favorite books is Pillars of the Earth by Ken Follett, which goes back to the original cathedral builders. And they used to start laying slabs really quickly, and they kept on collapsing because they didn't design them properly. The job of a modern day an Endava engineer is to do the architectural thinking, think inception, and establish in their mind with the client what is the building going to look like when it's done and not then hand that over to a load of coders, you hand it to the agents to each do their little bit of the LEGO building. So it's a very different approach.
It's an interesting construct that you're building. At least to me, it's somewhat resonant because if I think about the way that things were built for a long time as you just kind of started. If I start with the log cabin, I start -- I see which -- what my trees are, what fits, what fits together and kind of architect as I go. Then to your point, is that, once you start building big things and you've got a lot of labor that can move quickly, you got to figure it out beforehand. And so...
Which AI can help you do, by the way.
Yes, Yes, yes, which is kind of interesting, right? But then if I go back to kind of what people -- like, if I go back to some of the big failures in software initiatives back in -- at the dawn of the Internet ages, people felt like, "Oh, like we fell short of capability and had a lot of cost overruns because we tried to overengineer upfront without really knowing what the potential was." And so that's kind of, in my mind, maybe overly simplistically gave rise to this Agile coding approach, et cetera, where once again, you're kind of back to building as you can, especially in a cloud-based environment, your costs were low if you made a mistake, et cetera. But maybe as you're suggesting is that with agentic development, it seems like the architects start to become a lot more important again. And it seems like what you're saying.
It's not just the architects but I...
Yes. But like the architecture that comes together.
Yes, you have to put the work into what exactly are we building and then you tell the agents to do it. Right. But by the time we're equipped with all of that information, the prompts, the ask but also all the contextual information around this is the environment you're going into, this is the regulator requirements, et cetera, you can get -- and our experience is you get higher quality code than with very good engineers, if you do it right. If you don't do it right, if you're substandard in the way you do it, you have a rubbish in, rubbish out problem.
Got it.
And just to add to that, if you think of our strategy to engage with the C-suite and ideate on what their modern building might look like, what their skyscraper is going to look like, their Salesforce Tower, is if they've already done that work internally and they've got it wrong and it's got to IT procurement and they're just doing an RFP and you're in a race to the bottom against the Indian outsourcers or against one of our peer group, the chances are it's not going to be a great project, and you're going to build a reputation for that. By being in the ideation stage, you can really work through the flow so you get success.
Got it. Any questions from the audience here? Just -- a question here.
How much efficiency will this method bring clients in terms of the job. So if you think about -- there's a lot of software companies talking about engineers doing 20x the amount of work as they used to do per head. If you had a job that was 6 months or 9 months, how much -- and obviously, you guys want to participate in the benefits here, but how much quicker can you -- do you think you can do it?
So we're in multiples rather than percentages, right? We're definitely in that space, i.e. are we talking 3x, 4x, 10x? It's that sort of -- and it depends on the specific job. I think that's actually essential because in order to deliver successful solutions, you've got to do things like address the legacy system problem. That means you've got to lower the cost of fixing those issues to a level where it becomes viable which it hasn't been historically. AI actually enables that, and it's the productivity that enables it. But it unlocks a huge amount of work that's been locked away because no one could afford to do it.
Yes. So it's the obvious follow-up. So if your multiple is more efficient, is there multiples more work there to replace what you were doing before? Just not that in terms of the market size, obviously, you could grow share or whatever, but just in your client base?
I think for an organization like us, there is, right? Because we're shaped right for an AI world with enough senior people and not too many junior people. I don't think you can apply it to the whole market and go everyone, including all these armies of junior people are going to be kept busy by this new method, right? I think that's where you get the winners and losers. But I think for an organization like Endava, with the structure and shape that we've got, there is plenty of opportunity to eat up the productivity and do more with our clients, i.e., they'll still spend the money.
Yes, go ahead.
And can you talk to any pilot or test projects where this has been successful already, maybe on the metrics of what it would have looked like versus what it looks like now?
So yes, we're not actually disclosing any of that at the moment, right? Some of these are 12-, 18-month programs, and we're seeing the benefit, but we're not actually able to reach the point where we have completed and actually able to demonstrate that the outcomes that we got were what we expected or better. So we're seeing it, but we haven't reached the point where we can really produce definitive things on it.
Let me just add. Because, obviously, under NDA with particular customers, we can demonstrate how the methodology has been viewed, because we had to show examples. So the Nexus bid that we won against pretty much every big IT services company in the world. So it's us and AWS that won the rebuilding of SWIFT, if you want to think of it like that, starting with 6 countries in Asia.
It's an enormous project. I mean it's a huge project. But it's under some time pressure, which has now been compounded by the geopolitical environment because it's all about sovereignty of data and do we want 2 big American companies managing these systems around the world. And so we're on an aggressive time line to get that delivered. They would never -- if you look at who Nexus is, set up by the Bank of International Settlements as a joint venture between some pretty big players, they would never have picked us if they didn't have the confidence that our methodology would get it there in time for a modern platform.
So a lot of the deals we'll be announcing and the deals that we've announced are based on us exposing the methodology to people. We do get asked the obvious question, which is, 'Does that mean we get it for less money?" No. But it's a much more guaranteed outcome, and it will be more efficient when we do it.
So there is an element of alchemy. We're not a company that builds IP per se. We don't build our own platforms. We're not committing to platforms. But we do think the methodology, just like the Agile Manifesto did, will become something that people gather around. That's our ambition.
And just you reminded me there, the thing about Dava.Flow is it's tool agnostic. So clients are no longer worrying about, "I have to decide whether I'm going to choose Anthropic or ChatGPT," and "Someone else will come up with something better and my whole choice has been thrown out," and "I don't want to start a project because something keeps coming over the horizon." Dava.Flow takes that away because you can plug whatever tool you want into it and then execute against that.
So last question here in the last 1.5 minutes, and I want to take this back a little bit to the P&L. How much of recent margin pressure is intentional, that is investment in this and other transformative initiatives versus structural pricing utilization, going back to kind of this question here? And help us understand the impact -- relative impact of margins and when we should expect to turn.
I'll let Mark give some definitive numbers. But essentially, we've been investing significantly in the pivot, by investing in the AI capability. We've invested in staff with AI capability that are not fully billable yet. And so that's had a depression impact. And our billability has come down because we're not driving the growth rates that gives the healthiest level of billability right now.
I don't know whether you want to put number on it.
Took the words out of my mouth. I mean, quantification, it's about 3% that we've been investing. It will abate as we go through into our next fiscal '27, but we will continue investing but not at that level because the groundwork has been done basically.
Great. Well, we're out of time here. John, Al, Mark, thank you very much for joining us here at the Morgan Stanley TMT Conference, fascinating conversation and best of luck.
Thank you, and a great conference. Cheers.
Thank you.
Endava ADR — Q2 2026 Earnings Call
1. Management Discussion
Good day, and welcome to the Endava Second Quarter 2026 Results. [Operator Instructions] Please note this event is being recorded.
I would now like to turn the conference over to Laurence Madsen, Head of Investor Relations and ESG. Please go ahead.
Thank you. Good afternoon, everyone, and welcome to Endava's second quarter of our fiscal year 2026 conference call. As a reminder, this conference call is being recorded.
Joining me today are John Cotterell, Endava's Chief Executive Officer; and Mark Thurston, Endava's Chief Financial Officer.
Before we begin, a quick reminder to our listeners. Our presentation and our accompanying remarks today include forward-looking statements, including, but not limited to, statements regarding our guidance for Q3 fiscal year 2026 and for the full fiscal year 2026, the impact of headwinds facing our industry and business, trends in our industry, including with respect to development with AI, enhancement to our technology and offerings, the benefits of our partnerships, demand from clients for our technology services, our ability to create long-term value for our clients, our people and our shareholders and our business strategies, plans, operations and growth opportunities.
These statements are subject to risks and uncertainties that could cause actual results to differ materially from those contained in the forward-looking statements. Actual results and the timing of certain events may differ materially from the results or timing predicted or implied by such forward-looking statements, and reported results should not be considered as an indication of future performance.
Please note that these forward-looking statements made during this conference call speak only as of today's date, and we undertake no obligation to update them to reflect subsequent events or circumstances other than to the extent required by law. For more information, please refer to the Risk Factors section of our annual report filed with the Securities and Exchange Commission on September 4, 2025, and in other filings that Endava makes from time to time with the SEC.
Also, during the call, we'll present both IFRS and non-IFRS financial measures. While we believe the non-IFRS financial measures provide useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with IFRS.
Reconciliations of such non-IFRS measures to the most directly comparable IFRS measures are included in today's earnings press release as well as the investor presentation, both of which you can find on our Investor Relations site or on the SEC website. A link to the replay of this call will also be available on our website.
With that, I'll turn the call over to John.
Thank you, Laurence, and welcome, everyone. We appreciate you joining us for our second quarter fiscal year 2026 earnings call. Earlier this month, Endava passed 26 years since its founding. During these years, we've been through significant technology shifts, each time with a founder mindset intent on driving transformation as fast as possible in order to emerge as a leader.
Today, my mindset is no different as the AI shift is underway. Over the past several quarters, we've been investing heavily in our pivot towards AI to establish Endava as an AI leader. These investments have encompassed recruitment and training of next-gen talent, introducing a shift towards becoming AI-native, building our partner ecosystem and evolving our engagement strategy.
I'd like to flag some highlights of the quarter. Revenue totaled GBP 184.1 million, representing a 5.9% decrease year-on-year and up 3.3% from Q1 FY '26. We are seeing strong initial interest with clients on Dava.Flow, our AI-native engagement life cycle. We continue to expand our network of strategic partners and broaden several existing relationships, further extending our reach.
A PayNet-NETS joint venture recently appointed as Nexus Technical Operator by Nexus Global Payments has selected Endava to design and build its cloud-native cross-border payment switch on AWS, underscoring our depth in the Payment vertical. We believe we are building the operational agility required to achieve sustainable long-term growth.
Over the quarter, we advanced several enterprise-scale AI projects that illustrate both the breadth of client demand and the speed at which AI-native delivery models can create measurable impact. We're helping a leading global payments network modernize a critical driver of revenue, the chargeback dispute system that currently needs more than 1,000 people to run.
The challenge is a rule book that amounts to thousands of pages and is hard for anyone to follow. Our system uses AI to read those rules, turn them into clear checkable logic and link each one to the right data so cases can be routed and analyzed automatically. Halfway through the 6-month projects, early results are promising. The new system is easy to use, fully auditable and will sharply cut manual effort while making decisions more consistent when it goes live.
Over several years, we've helped a leading global specialty insurer use AI and data science to streamline pricing, insight generation and automated data ingestion. Traditional operating models limited impact, so facing increasing competitive pressure and new entrants, the insurer committed to a faster AI-native approach.
Working with the client, we set up a ring-fenced incubator inside the organization that can build an end-to-end AI-native insurer while keeping clear governance and visibility for leadership and underwriting teams. The program has 3 linked work streams: digitization, the automation of submission, data enrichment, pricing and quoting, hypothesis-driven change, which tests value-add ideas such as new data sources and new revenue models and tactical value creation, which feeds proven ideas back into business as usual in partnership with stakeholders.
To date, the digitization work stream has been rolled out across 2 business lines. Using agent-based delivery, we stood up a fully operational AI-native workflow in roughly 3 weeks and built a backlog of more than 50 improvement hypotheses. Although still early, the results underline how rapidly AI-native capabilities can scale when governance and execution are explicitly tuned for speed. These milestones show that the initiative has moved beyond experimentation is now entering a more mature scaled phase of AI implementation across the organization.
Let me now turn to Dava.Flow. Client interest continues to build. Clients report faster delivery, tighter control and full traceability versus legacy models. In a recent project, we opened with a signal session, the first step in an engagement where agents and teams capture, enrich and interrogate market, client and operational signals to test assumptions and define a clear value hypothesis.
In just 90 minutes, the session gathered live inputs, ran synthetic workshops and produced an opportunity assessment, market and strategic insights, product requirement documents and an agent-ready backlog, work that would normally take several weeks. [ Two ] live Dava.Flow engagements now sit at different delivery stages.
Early results show higher productivity, better quality and strict policy adherence. Autonomous agents manage routine tasks under policy as code governance, freeing engineers for orchestration and critical decisions. Over the coming quarter, we expect to broaden the delivery portfolio, convert growing interest into larger outcome-driven programs and further refine the model using feedback from live engagements.
I will now turn to recent developments in our strategic partnerships. January marked the completion of our first year as an official services partner of OpenAI, and we are seeing growth in demand as clients scale proofs of concepts into enterprise-wide deployment of enterprise ChatGPT. Our partnership with OpenAI's go-to-market team is resulting in a pipeline of potential opportunities across industries such as insurance, health care and life sciences and public sector.
In collaboration with OpenAI, we've been engaged by Evoke, one of the world's leading betting and gaming operators to roll out enterprise-wide ChatGPT enablement and role-specific AI training that supports responsible generative AI adoption and measurable productivity gains. Additionally, last quarter, we broadened our expertise across OpenAI's product suite, continuing to graduate additional sales and technical specialists from our intensive training programs across APAC and EMEA.
Demand for our services across all 3 of our major hyperscaler partners, AWS, Google Cloud and Microsoft Azure is accelerating, primarily fueled by clients' core modernization initiatives to retire costly legacy systems and by their accelerating adoption of AI solutions. With AWS, in particular, we secured several notable wins and renewals, particularly in the financial services sector in the U.K., U.S.A. and Asia Pacific.
Clients are asking for repeatable proven solutions that derisk technology change. In response, we released 2 new AWS marketplace offerings, cloud application engineering and an AWS Landing Zone Accelerator. Our multiyear strategic partnership with Paysafe, a leading payments platform aims at enhancing innovation in payments and digital community engagement, notably fan engagement.
As part of accelerating Dava.Flow, we have forged 2 complementary partnerships. First, with Miro by embedding their AI innovation workspace across our global delivery network. Through this process, we increased the speed of decision-making, improved team alignment and enabled scalable AI-driven workflows that provide clients with greater speed and confidence in their AI transformation journey.
Second, our partnership with Cognition broadens the reach of our agentic coding, giving thousands of AI-native engineers access to Windsurf and Devin and strengthening our joint go-to-market for enterprise-grade outcomes. Together, these partnerships deepen the capabilities of Dava.Flow, from collaborative ideation through automated code delivery, creating an end-to-end AI-powered change delivery engine.
We believe our partner ecosystem, ranging from global hyperscalers and sector leaders to emerging scale-ups is essential to both client outcomes and our profitable growth. To support this initiative, in November, we launched Dava.Rise, a venture acceleration program that converts start-up innovation into solutions deployable at enterprise scale. By connecting high potential ventures with Endava's AI-native global delivery capabilities and established client relationships, Dava.Rise accelerates the path from concept to enterprise-ready solutions.
This collaborative model gives clients access to emerging technologies that address specific business challenges and deliver measurable impact across industries. We launched the inaugural Dava.Rise cohort in partnership with Octopus Ventures, selecting ventures in their portfolio whose offerings align with identified client needs.
I'd like to highlight several client wins that demonstrate the tangible value we are delivering. As mentioned earlier, a PayNet-NETS joint venture recently appointed as Nexus Technical Operator by Nexus Global Payments has selected Endava to design and build its cloud-native cross-border payment switch on AWS. The platform is intended to interconnect national instant payment systems into a single real-time network advancing global interoperability.
The appointment of the PayNet-NETS joint venture follows a competitive multi-vendor tender and underscores Endava's expertise in real-time payments architecture and delivery. We extended our strategic delivery commitments with 2 of our largest payments customers, reinforcing the strength and retained trust and delivery assurance we continue to enjoy with these major industry names.
We worked with Accor Plus, a leading lifestyle loyalty subscription program in the hospitality sector to successfully overhaul their payments infrastructure and loyalty program across Asia Pacific. In the first phase of the project, we replaced their legacy processor with a scalable plug-and-play solution, simplifying the loyalty architecture to support rapid membership growth and deploying the solution across 10 markets.
In the first 30 days following launch, product page conversion increased by 39%, providing Accor Plus with a more reliable, scalable foundation for future expansion. At the end of December, we expanded a strategic partnership with a manufacturer of electric vehicles, replacing a leading global technology services competitor in this arena. The new work stream adds an AI-enabled digital CRM to raise delivery efficiency and elevate customer and digital experience.
Endava has entered into a 3-year strategic partnership with Boex, a banking-grade software company that simplifies the B2B trade of goods and enables the secure compliant digitization of international trade processes. Our partnership supports the development and expansion of Boex's product portfolio, giving organizations the confidence to operate at a scale that was previously too complex and costly for most.
Additionally, through Endava's Dava.Rise program, Endava is working closely with Boex to accelerate product build-out and take advantage of mutual partnership opportunities. Endava is partnering with a global life sciences company to turn its agentic AI prototypes into governed platform-supported products that can be measured and replicated across the business.
The program accelerates delivery of safe, repeatable AI at scale while defining and helping implement the organizational changes needed across talent, operating model and culture for the company to become an AI-first enterprise. To drive adoption and demonstrable results, Endava has also introduced dynamic solution squads that co-create with domain owners through a structured outcomes-focused approach.
We ended the quarter with 11,385 Endavans, representing a 2.4% decrease from the same period last year. We continue to streamline roles in areas of softer demand, while broadening and upskilling our AI talent base, embedding new capabilities across the business to help clients integrate new technologies into their workflows.
Before we close, I want to thank every Endavan. Your dedication and professionalism continue to steer us through a fast-moving technology landscape and convert change into tangible results for our clients.
I'll now hand over to Mark for a closer look at our quarterly financial results and guidance for the upcoming quarter and the remainder of the fiscal year.
Thanks, John. Our revenue exceeded the upper end of the guidance issued for the quarter ended December 31, 2025. Revenue totaled GBP 184.1 million for the quarter as compared to GBP 195.6 million in the same period in the prior year, representing a 5.9% decrease. In constant currency, our revenue decreased 5.1% from the same period in the prior year. On a sequential basis, revenue increased by 3.3% compared to Q1.
Loss before tax for the 3 months ended December 31, 2025, was GBP 7.2 million compared to a profit of GBP 2.5 million in the same period in the prior year. Our adjusted PBT for the 3 months ended December 31, 2025, was GBP 10.7 million compared to GBP 21.8 million for the same period in the prior year.
Our adjusted PBT margin was 5.8% for the 3 months ended December 31, 2025, compared to 11.2% for the same period in the prior year. Our investment in our AI-native delivery model and in next-gen talent has impacted our adjusted PBT margin and will continue to do so as we continue our shift towards becoming AI-native. We estimate it has reduced the adjusted PBT margin by approximately 3% through Q2 FY '26.
Our adjusted diluted earnings per share, which fell within our guided range, was 16p for the 3 months ended December 31, 2025, calculated on 52.9 million diluted shares as compared to 30p for the same period in the prior year calculated on 59.6 million diluted shares. Revenue from our 10 largest clients accounted for 35% of revenue for the 3 months ended December 31, 2025, compared to 36% in the same period last fiscal year.
The average spend per client from our 10 largest clients decreased from GBP 7.1 million to GBP 6.5 million for the 3 months ended December 31, 2025, as compared to the 3 months ended December 31, 2024, representing a 7.9% year-over-year decrease. Of this, FX movements contributed to a 2% year-over-year decrease.
In the 3 months ended December 31, 2025, North America accounted for 40% of revenue, Europe for 23%, the U.K. for 31%, while the Rest of the World accounted for 6%. Revenue from North America decreased by 5.1% for the 3 months ended December 31, 2025, over the same period last fiscal year. The decrease was driven mainly by an FX headwind of 3.3% and the lack of contribution in the current quarter from the significant media client whose loss we reported last fiscal year.
Comparing the same periods, revenue from Europe declined 8.5% due mainly to weakness in Payments and Mobility. The U.K. decreased 9.1% due mainly to the reclassification of a large Payments clients from the U.K. to North America as the relationship with that client is now based there, which was mentioned last quarter. We also experienced weakness in TMT in the U.K. this quarter. The Rest of World increased 21.8%, driven mainly by the Payments and TMT verticals.
Our adjusted free cash flow was GBP 20.1 million for the 3 months ended December 31, 2025, down from GBP 31.6 million during the same period last fiscal year. Our cash and cash equivalents at the end of the period totaled GBP 68.5 million at December 31, 2025, compared to GBP 59.3 million at June 30, 2025, and GBP 60.1 million at December 31, 2024.
Our borrowings increased to GBP 202.7 million at December 31, 2025, from GBP 180.9 million at June 30, 2025, and GBP 123.7 million as at December 31, 2024, [ and will ] support the funding requirements of our share repurchase program.
Capital expenditure for the 3 months ended December 31, 2025, as a percentage of revenue were at 4.4% compared to 0.2% in the same period last fiscal year. The increase is mainly related to a onetime spend on Payments Accelerator, our internally developed payments gateway accelerator, which broadens our ability to secure a wider range of commercial engagements with Payments operators.
The development of this solution leverages our Dava.Flow ways of working. As of January 31, 2026, we purchased approximately 8 million ADSs for $121.9 million under the share repurchase program, and we had $28.1 million remaining for the repurchase under our Board's share repurchase authorization.
Before moving on to the guide, I'd like to provide some context. The U.S. dollar's ongoing weakening against our reporting currency, GBP, continues to create revenue headwinds. Revenue guide is being largely maintained in absolute terms, but the growth is stronger in constant currency terms by 1% for the full year. In addition, as I mentioned previously, we continue our investment in AI-native delivery and next-gen talent, which also continues to impact the adjusted PBT margin in the guide.
Now moving on to the guide. Our guidance for Q3 fiscal year 2026 is as follows. We expect revenue to be in the range of GBP 182 million to GBP 185 million, representing constant currency revenue decrease of between 4% and 2.5% on a year-over-year basis. We expect adjusted diluted EPS to be in the range of 18p to 21p per share.
Our guidance for full year fiscal 2026 is as follows. We expect revenue to be in the range of GBP 736 million to GBP 750 million, representing constant currency revenue decrease of between 3.5% and 1.5% on a year-over-year basis. We expect adjusted diluted EPS to be in the range of 80p to 86p per share. This above guidance for Q3 fiscal year 2026 and the full fiscal year 2026 assumes the exchange rates on January 31, 2025, when the exchange rate was GBP 1 to USD 1.37 and EUR 1.15.
This concludes our prepared comments. Operator, we are now ready to open the line for Q&A.
[Operator Instructions] Our first question comes from Puneet Jain with JPMorgan.
2. Question Answer
So I wanted to ask about like the fiscal year guidance, like, which implies like nice sequential growth in Q4 after flattish third quarter on FX-neutral basis. So can you talk about like what drives that growth in fourth quarter? Is it like the large deal ramps, billing days? If you can double-click on drivers for growth in fourth quarter?
Thanks for the question, Puneet. I think stepping back to Q3, it looks flattish when you look at it. But as I said in the opening comments on the guide, due to the weakness of the U.S. dollar, there is FX headwind quarter-on-quarter about 1.5%. I think the other thing that needs recognition in our Q3, which is the quarter to March, is we have lower working days than we had in the previous quarter, which is a further headwind of minus 3%.
So the underlying growth in Q3 quarter-on-quarter is about 4% at the midpoint of the guide. Now going to Q4, we actually have an increase in working days when compared to the quarter to March, which had about sort of 2% growth. So at the midpoint, it looks like a sequential growth of about 8%. It's actually about 6% and that compares against an underlying growth that we saw in Q3 of about 4%.
Now in terms of what underpins that Q4 pickup is basically some of the deals that we've highlighted that we have won that have been secured that provide that underpinning for growth.
Got it. Got it. And then I think you also mentioned extending commitments with 2 largest Payment clients. Can you share more details like around the scope, type of work? And if we should expect continued sequential growth beyond this year, given like the pipeline and overall opportunities you see?
Yes. So that was extensions of work with a couple of our larger Payments clients, in fact, the 2 largest. There's been quite a stream of that coming through as we went through the new calendar year coming into play. And most of it is extensions.
There is a little bit of incremental in it, but most of it is extensions on the run rate level that we had in Q1 and Q2. The relationships remain good. The sort of work is in the switch gateway type space and continuing to help our clients to rationalize the costs of those estates, but then also enhance the value propositions for customers coming out of their capabilities in that space.
And the next question comes from Gates Schwarzmann with TD Cowen.
I wanted to follow up on some of the guidance assumptions here. I wanted to ask particularly on the margin front. You guys talked a little bit about like the increased investments here that are going to drive some of that adjusted PBT to be a little bit lower. Is that -- are those investments coming in higher than expected now in the second half? Because the EPS guide is a little bit lower.
Just trying to sync the better revenue view with the lighter EPS view. Is that largely investments coming in higher than expected? Or is there any sort of FX impact there? And if possible, can you break out the FX impact on the margin front in terms of the guidance?
Thanks for the question. I'd say that it is slightly heavier investment in the second half. I mean, John referenced partnerships with Miro and Cognition, which are sort of key components for Dava.Flow. So we've entered into licensing the software with those providers.
And it is a wider sort of partnership than just a supplier vendor relationship. So they weigh a little bit more on margin. So that sort of 3%, let's call it continuing investment, I see being about that level as we go forward into the second half. In terms of FX, I think it does weigh on us in terms of the gross margin sort of certainly.
The weakness of the dollar, certainly at $1.37 and even a quarter ago when we were guiding for this quarter, it was $1.32 impacts gross margin. It's a little bit at the edges. It's something like about 0.5% or so as we have a sort of balanced global sort of workforce, but it is a headwind, and it does mainly impact the sort of revenue growth rather than margin for us.
Got you. And I know you guys have been a strategic partner for OpenAI, one of the early actual deployment partners there. So curious if you could touch up a little bit on the OpenEye -- like the OpenAI GPT enterprise adoption trends that you guys are seeing in the market. And then additionally, we've heard some comments in the past few weeks. There's been a little bit of a narrative around services and software displacement as a result from some of the offerings coming from these foundational model providers. Do you guys have a view there? I'm just curious if there's any sort of way to dispel some of those fears.
Yes, sure. I mean, OpenAI, our relationship with them is very strong. We've adopted enterprise ChatGPT across the business. And so it underpins a lot of our AI approaches. We're also in the market jointly selling with them. And that is leading to some success. I covered 1 or 2 of those in my opening remarks.
I mean with OpenAI, the opportunity is opening up the enterprise market for them. They've had a lot of success from a consumer market point of view. And we're one of the people who are going down the learning curve with them on how to really make their platforms work in an enterprise context.
And that -- those approaches and what we're doing with them there is what's leading to success in the market and some of the opportunities that are coming through. So we remain very excited about that relationship with them. You'll have picked up, we also have relationships with the other hyperscalers and large language model providers in the market, and we're seeing equally exciting opportunities with those guys.
On the services and software displacement question, I think a lot of the reaction is looking at some of these things at a very simplistic level, i.e., almost a consumer market level, or you can create code much more quickly using Agentic AI solutions and so on. But actually, when you project that into the enterprise market, the adoption challenge is different.
It's much higher. It requires a different delivery model that's going to handle the governance, the regulatory framework and the value realization, the access to data, the modernization of legacy systems all come into play. And the sort of out-of-the-box consumer level, small project level solutions don't address all of those things.
It's one of the reasons why we've created Dava.Flow as a replacement to Agile as a delivery method because Dava.Flow addresses the governance and the regulatory, the consistency, the enterprise environments that you're plugging into in a way that Agile doesn't. Agile was a methodology that was set up to enable interactions between people in the creation of software.
When you start moving into an agentic type situation, the people interactions person to person are less important than the interactions people to machine. And that requires a different development methodology, which is what we've built to work in these complex enterprise environments.
So we actually see a lot of opportunity as enterprises start to address all of these complex issues around the implementation of AI and a growth in demand because there are many things that enterprises have not been able to do in the last 20 or 30 years like address their legacy systems.
The AI actually enables a cost-effective route to addressing as well as then delivering business benefits that weren't possible without AI. So actually, we see the uplift in the market opportunity certainly for the next 5 to 10 years, outweighing as enterprise started to adopt at scale, outweighing the productivity headwinds that people are concerned about.
[Operator Instructions] Our next question comes from Antonio Jaramillo with Morgan Stanley.
I wanted to go back to your guys' top line guidance here and kind of go back to the assumptions baked in there. Could you walk through how your spend around your top customers are baked into that? And then also, could you remind us what your pipeline and your booking assumptions are as well? That would be helpful.
I'm not quite sure what you mean by the top spend clients. Do you mean the sort of profile of our top 10 clients and the profile quarter-on-quarter.
Yes.
Okay. So I think broadly, we see a lot of stability in that top 10. It is dominated by our Payments clients. We expect a little bit of a slowdown in our large Healthcare client in Q3, but then for that to resume as we go into Q4. But that is the only sort of change in the sort of profile. So we do expect sequential growth quarter-on-quarter.
In terms of sort of pipeline assumptions, we usually quote a split of contracted and committed to pipeline. So certainly for Q3, which we're guiding at, it's around 95% and slightly lower at the top of the guide. And then as we look into Q4, we're at 70%, 75% contracted and committed, which is typically what we have seen in recent sort of history.
I think there's a high degree of confidence around pipeline conversion. So -- and that's based on deals that we have secured throughout the course of the year and also the strength of the order book, including the ones secured in January. So we -- it may look as though there, as I said to the first caller that we had this step-up from Q3 to Q4, but actually, it may look like that, but it's actually an underlying 6% compared to a 4% sequential growth in Q3. So it is a relatively modest underlying Q-on-Q growth expectation from Q3 to Q4.
I think the only thing that I would add to that is the market continues to have a level of uncertainty to it that we didn't see 3 or 4 years ago. And that's reflected in the breadth of the guide that we've put forward. The top to bottom is very wide given -- for Q4, given it's only 6 weeks away. And I think that's how we've tried to capture the market dynamics in the way in which we've guided. And Mark covered all the details that have gone into that.
Great. That's helpful. And then just on the broader pricing environment, could you maybe walk through how GenAI engagement pricing is and -- versus core work? And are you seeing transitions from proof-of-concept into production for those GenAI projects? And does that vary by industry segment, by customer? Any trends there would be helpful to call out.
So I think -- and this will take a while to get through into the overall stats. But if you look at the new business that is coming through, it is shifting quite strongly to outcome-based solutions with our AI approach supporting how we're going to drive the outcomes.
And the Dava.Flow model that we have really helps to early on get a grip on what the benefits are that are going to be delivered, the appropriate levels of functionality and so on. So the new business stream that is coming in is much more outcome-based. That does offer a wider range of margin outcomes depending on how we perform and the benefits that we deliver to the clients, which at the top end are strong. And at the bottom end, they're reasonably well protected, I think, would be a good way of describing it.
And the next question comes from Jonathan Lee with Guggenheim Securities.
I wanted to dig into Dava.Flow a little bit more. It's good to hear about traction with clients there. But can you provide more detail on adoption, approximate number of clients or percentage of revenue touched by Dava.Flow today and whether there's any impact on pricing or margin versus your traditional engagements because of that shift to more outcomes-based pricing or fixed price?
So the focus that we've got for Dava.Flow is not to roll it right across our estate, but to focus it on the outcome-based deals that we're signing. Because our expectation is that with Dava.Flow, and actually, we're seeing this in the places where we're using it, that we can get a much, much higher level of velocity.
And so applying it in the space where we're writing outcome-based deals with clients gives us a lot more opportunity to participate in the upside as we deliver using the Dava.Flow method. And so that is where we're applying it. So it is in larger outcome-based projects. We're seeing a good pickup and enough to actually see the metrics across a number of clients as to how it performs.
But we're not going to be -- start giving actual numbers of clients because I think that would be misleading as in the numbers will be low, but the scale of the projects that it's applied to would be higher.
Appreciate that color there. And just as a follow-up, could you help us understand trends in signings, including trends across large and small deals and whether there have been any surprises or just delays or cancellations that you've seen across the quarter into this quarter?
No, I think the velocity has been the normal level for what is now this environment they're in. So we've had no surprises from that sort of score. Obviously, we'd like things to progress more quickly than they do. But increasingly the larger deals, one of the differences is there's a lot more due diligence that goes into it because of the scale of the engagement which is multiyear on both sides, the client and us.
But I think the velocity of opportunities has sort of stabilized, albeit at this sort of lower level. Are we seeing any uptick in it? I wouldn't say so. I think we're seeing particular sort of strength maybe in the payments and banking capital market space, so financial services more broadly.
This concludes our question-and-answer session. I would like to turn the conference back over to John Cotterell, CEO, for any closing remarks.
Thank you, and thank you all for joining us today. To close, we continue with our sustained investment in AI, spanning talent development, the rollout of Dava.Flow, deeper partner alliances and an evolved engagement model. And this quarter's momentum underscores that clients view Endava as a trusted partner for AI-enabled change. I look forward to seeing you in our next quarterly earnings in May.
The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.
Endava ADR — Q2 2026 Earnings Call
Endava ADR — J.P. Morgan 2025 Ultimate Services Investor Conference
1. Question Answer
Good afternoon. My name is Puneet. I'm from JPMorgan's payment processing and IT services team. Glad to have here with us Endava. We have Mark, who obviously, you all know, CFO of the company; and Al, who's Chief Engagement Officer. If you have any questions on Fintech, feel free to ask him. He's the Fintech guru here. So the format of this presentation is going to be fireside chat. I'll start with a few questions, and then we'll open for questions from audience. Welcome. Thank you, both of you. Appreciate it.
Thank you.
So let's start with like the third quarter results. You reported recently results came in slightly below expectations. So talk to us like what are the trends, high-level trends you are seeing? What were the drivers for the weakness or for the shortfall? And what do you expect going forward?
Yes. So it was mainly a top line hit or miss. We suffered an unexpected credit with a significant client. It wasn't driven by poor performance or delivery issues. It was basically to secure future sort of pipeline of work with them. So it was unexpected, and it was issued after -- or the discussion was entered into after the guide. Now taking the revenue off, it impacted our EPS. It went straight through to the bottom line. So we were just short on the revenue and we would have been in the middle of the EPS for the quarter, if not for that item.
Now we did see also some weakness on our non big deal pipeline. So if you recall back in May, we said we were offering guidance but stripping out big deals. So it was just run rate Endava. There was some slight weakness. So we did convert pipeline but not as much as anticipated. And as a consequence, we looked at the rest of year outlook and trim some of that pipeline.
It wasn't all bad news. We secured three large deals. So Paysafe, which I can now name since the call, 5-year $100 million deal, which Al is quite instrumental in securing, and an insurance client and Toyota Racing Development as well. And those really add the momentum to the second half of our revenue outlook as they produce step change in revenue.
So we -- as a result of that, we have, I'd call it, a flattish quarter ahead, Q2, minus this credit issue. And then the momentum picks up in the second half, basically from those contributions from big deals. And with the sort of operational leverage that Endava has, I'd expect it to be relatively flat from an EPS perspective for the next couple of quarters, but Q4, we start to sort of pick it up.
So let's talk about the credit issue that you experienced like -- first, like I'm assuming like it is nonrecurring, like this is like a onetime thing this client, it should not repeat with any other clients or some -- is it tied to vendor consolidation that many clients are doing? Like, how is it different from that vendor consolidation?
So we don't believe so. So it wasn't do this, and you remain part of the pack going forward. Basically, the client sought similar arrangements, if I can call it that, from the rest of their source suppliers. And made it pretty clear that if we didn't participate, then it would diminish our opportunity of further work or size of work with them going forward. The client we've had experienced previously, but not of this sort of scale and also the sort of downside that they're implying from the discussions. So we think it is one-off in nature. You can never say something won't repeat, but it's pretty unusual. We got notice of it very late, maybe after the quarter was sort of close, but obviously reflected what was going on in the quarter. So we booked it accordingly.
Got it. And then let's talk about -- like on the other side, like the large deals that you're winning. Obviously, we know that you've been trying to pursue those deals for a while. So there is lot of focused effort that has gone in winning those deals. So talk to us like how is like the profile of those deals different from the deals that larger diversified companies like Accenture, Cognizant talk about. And then the size you mentioned [ $100 million ], is that...
They are significant from Endava's perspective, probably not from an Accenture perspective. They don't tend to be managed service structure. We tend to be -- we're known for innovation and driving businesses for transformational. These engagements that we are securing, and there's a lot of appetite, so it's a very strong pipeline that we have, but it's not in the guide as we may sort of clear. They are quite heavy in financial services, and that has been picking up. Paysafe been a sort of example of that. They tend to be also multiyear. So we want to lock in a transformational journey and partnership with large clients for at least 3 to sort of 5 years. Now these arrangements are -- can take time to negotiate and agree. Most of them have the nature of actually starting almost like immediately.
So we announced deal with Reed Exhibitions, I think, back in sort of September. Now there's a lead time whilst there's a discovery phase and then the services sort of start from the 1st of January. Most of these deals do start in the new sort of calendar year. So there isn't the profile of a gradual ramp typically. There are service that starts and we start to deliver that service.
And maybe, Al, you'd like to talk about Paysafe in particular because it's typical of the arrangements that we're trying to put in place with these big deal structures.
Yes, happily. I always get confused because I'm a simple rugby player, which is -- you talked Q3, which obviously are...
Q1.
Q1. Yes. And interestingly, in this industry, you get the sort of end of year, start of year thing, and we fall between 2 stores. So it's quite an important thing to remember when we talk about ramp-ups as well and people spending budget sometimes a year. But I think there's 3 elements to a deal that is going to really matter to investors in companies like Endava, which is, a, are we starting to see AI creep into the delivery? So Endava has built an incredible track record of an amazing Net Promoter Score over the years of being a great delivery engine. All the customers are very satisfied. That was in the agile period, and now we're talking about an AI period. So we haven't lost that muscle memory. The 12,000 Endavans are all still completely committed to deliver it.
The second thing is how meaningful is the commitment? So rather than the sort of SOW, I've got a project, it's a race to the bottom, you're competing against other outsourcers. Those aren't really the deals that interested -- well, we're much more interested in -- you make a commitment, we'll make a commitment, build a joint team and go and get stuff done. So that's important.
And then the third piece is time. And I mean it's interesting today to be here when certainly back in my home country in the U.K., the headline news is the Alphabet CEO talking about maybe a correction, maybe a bubble in AI. It's fascinating to me. There's this sort of gap between the practitioners in AI, the developers of AI, the people invest in trillions of dollars in AI, and then your average company that is trying to deploy AI. And there's no one really bridging that gap and being acting as a bridge between the AI technology and the business outcome.
And if you think of the amount of data that certain companies hold, if you can apply AI to that, you're going to transform that business. So the third piece to these strategic deals is longevity. Because if you go back a year, ChatGPT 3, 4, now 5, the world is evolving very quickly. But if you've locked in a partnership, and I don't say locked in, in a negative way, I mean, in a commitment way, then you're really well placed to learn. And I think most of the C-suite that I talk to are getting quite fatigued about the silver bullet pitch. AI is going to transform your business.
It probably will, just like mainframe to blade frame, did machine learning, did -- but there's not one silver bullet, so they're looking for partners. So I think you'll see Endava, as we've done with Paysafe, do far more long-term committed partnerships with the leading companies.
So 2 questions on that. So some of these deals like the multiyear deals, like -- so the AI can have the 2 types of applications. It can help improve an operation, right?
Correct.
Business operation, you don't need making up an example, tellers and replace them with AI or augment them with AI or AI can make coding more efficient. You can create an application much more faster efficiently using AI. So what's the bigger driver using AI to transform your operations or AI to improve your coding...
I think, well, let's go back to a couple of the transactions that are like Reed Exhibitions and others where you get a step change. So basically, I think as Al was point out, there's a lot of disruption caused by AI. The technology future is uncertain. If you've got to navigate that as a corporate, that is quite challenging. I know a lot of corporates are engaging with AI, but I think the key issue is then how do you roll it out on an enterprise level. You have it into the core systems. You are not exactly future proofing, but how do you navigate your way through a big sort of change?
And I think how -- certainly in some of the engagements that the clients are approaching it, is they want to give us the problem in some respects. So you take elements of my IT function. A lot of it will be development and innovation, and I want you to navigate that path for me. And what I as a client get out of is a certainty in terms of cost, I want quality and innovation as part of that. But Endava, it's up to you.
Now that is reliant on us interpreting what AI can do. We need to drive efficiencies and improvement. And that's where we talked about methodology, Dava Flow comes into that. So it's outsourcing in some respects the issue for us to manage. Now that's how some of these engagements are starting to be sort of formulated. And I think that's the early stage. So it's effectively, I think, cost efficiency. But I think it will develop more widely than that, to what Al's point about sort of partnership.
Yes, I'm using American term because I'm here in New York, but like a great American football team, it's defense and offense. So I think a lot of clients are saying, I'm hearing, I have -- no one's proven it to me yet, but I'm hearing that AI is going to create efficiency in my cost base, in my management of data, in my clarity of data. So I'd like to do that because that always helps my numbers. But also, are there new propositions? And are there new mousetraps? And are there new things that I can do. I mean, I think we live in a fascinating era of colliding industries. If you look at payments, an industry that I've been close to for many years, as a horizontal, payments is touching everything. Government transformation, global movement of money, right down to efficiency in your local government, in your towns and your cities. So I think that Endava's track record of being able to, as Mark put it, take over pieces of work for our clients, prove that you can get efficiency, but then add into that a bit of sizzle and say, here's a new proposition. Here is something you could do with that data that you couldn't have done before. That's where we've got to be positioned. And in many ways, our size is very helpful as a company. I think you mentioned -- I think if you're a company of hundreds and hundreds of thousands of people, that's a long journey. That's a long transformation. We've spent the last 2.5 years making sure every Endavan is fully compliant with the ability to make AI useful. So I think we're in pretty good shape.
Yes. And I think certainly, John was here. We're not a product company, but we have a methodology about how we build and deliver. And the agile world, it was teams and teams. It was the distributed agile way that we delivered. Now it's Dava Flow, that is essentially what our thought product or our unique positioning is going to be in this AI-driven...
And talk to us like governance issues. Like the clients we often hear the reason, many of those AI pilot projects are stuck in that phase is because clients are not comfortable with data security, change management because AI -- future AI is going to interact with their employees, customers. So talk to us like how can Dava handhold your clients in overcoming some of those challenges?
I think as we've had to overcome those issues ourselves around security compliance. I mean we operate in financial services, which is heavily sort of compliant. So we know the benchmark that is required and taking clients on that journey. And they does start off small, Puneet. It's not going to be a big step into Endava Flow. You have to show what it can do, a glimpse of what it can do. You do need a pilot or proof of concept to onboard a client with -- and that's how you build the trust around. And the governance guard rails need to be in place. But if you can demonstrate that knowledge upfront that you know where the pitfalls and bare traps are, it gives confidence in clients to make those bigger sorts step forward.
So that becomes like a way for you to win share by helping clients get there?
Yes. And I think our approach, we think, is differentiated with Dava Flow because it's basically building on the legacy of, let's call it, ideation to production that you've heard us sort of talk about. But it's in an AI world. So it's -- I think we call it signals the start of this whole process. So there's -- the stages that you should see as you go through the life cycle using Endava Flow. And it has a componentized structure to it. So it's not like we've invented Endava Flow, we push everything through the sausage machine. You can take elements of it out and use it in the T&M world. And I think that's the sort of beauty of it. It's sort of flexible like agile is. And I think it's quite differentiated from what I understand others have been talking about.
Yes. So core modernization, like helping clients modernize their data move to cloud and whatnot to be ready for AI. That has to be even of your core competencies. So talk to us like the traction that you are seeing whether through Dava Flow or otherwise from clients in those services? And why are we not seeing like -- and it's not just for Dava, it's for everyone else to not improve growth rates as clients are spending on core modernization to be ready for AI.
And I think it's one of the big prizes certainly for Endava. It's a big increase of share of wallet. We've typically historically worked outside core legacy sort of systems and plugged into them. I think with Dava Flow, the transformation of the core to make AI enabled into the cloud is the big prize for us. Because I think using the accelerators, is the term we use, but the automations, the tools to do it, the speed at which it can be done, the reduced cost that can be done, the visibility about the progress that make those big monolithic changes feasible.
Now it hasn't moved at the rate that we thought it would do based on the comments we were making 12 months ago. And I think there's this -- I think the whole AI journey is sort of settling down. I know the technology is moving very quickly. But I think enterprises understand where they are at the moment. I think they understand that they're going to need help from firms like Endava to make those enterprise-wide step change, they need to. And part of that enterprise-wide step change is helping them out with the core. So I don't think anybody has moved on it, but that is the big prize for us. And I think using Endava Flow and our accelerators will give certainty and they give clients the confidence to do it so that they can meet at the end of the day, their requirements in terms of return on capital. They're going to have to invest to do this.
I think just to add in there. So we're absolutely clear. The question is the right one, which is why aren't -- why is our industry not seeing the numbers come through. But we have to represent at these events also the conversations that we're in. And a year ago, everyone, it was almost impossible to get through the internal person that have been promoted to the head of AI. Who were saying, I'm making a religious bet. I'm the expert. I used to be a risk manager now wear jeans and a T-shirt, and I'm now an AI person. I think the C-suite is starting to get pretty frustrated with that. And we've seen that in every single cycle.
So yesterday, at the London Stock Exchange, we launched a new initiative called Dava.Rise, which is basically a platform, an accelerator, a lab, if you like, where we can bring in some of the most exciting scale-ups in the world, and present them to the Fortune 500, and then utilize our AI tools to demonstrate how we can accelerate their growth because a lot of big companies are saying, "show me, don't tell me, and I don't want to go and fight the budget internally until I've seen it work. So I think that was quite a clever move, but someone who was talking the yesterday, very successful U.K. entrepreneur, which is like hen's teeth, obviously. But this person was talking about, every time you set up a company and you exit it, you start at the beginning again. What's so nice about Endava to your previous question is the ticket to the game already exists. Are you compliant? Do you understand governance? Can I trust you to look after regulated data in the Middle East where we have a strong practice now in financial services? Do you want to understand hybrid cloud, sovereignty of data? They are things that are just muscle memory to this company. So the stuff that comes after that. Now I'm not sure that many people in our space can say that. They're talking about AI as the solution to everything. We're saying, no, you get into partnership with Endava, the cheques already written, like the mortgages covered. It's now what you do next to the business. So I think that's quite important.
That's interesting. So let's talk about like the AI use cases. There's so much focus on efficiency, whether it's -- it can read documents faster, it can automate customer care. Everything is about efficiency. You talked about earlier about adding some small sizzle. Like, is that extra sizzle? Is that related to at all about consumer-facing applications of AI, things can help your clients grow revenue?
Just look at Agentic AI, Agentic Commerce. So if you're a MasterCard at the moment, and they've made -- this is all public, they've made these announcements recently. We're moving now to instant tokenization of consumer data anonymization and the ability to make payments within ChatGPT or within app or whatever it might be, without ever having to go through that whole. Mother's maiden name in a [ thorough ] measurement process. That is a vision, a glimpse, if you like, of what's coming next. That's true in every industry. So Toyota, who, Mark mentioned earlier, Toyota have just had the -- Toyota Racing in North America have just had their most successful season for years. Now we were heavily involved in building some of their AI capability and predictability of race circuits and all -- these are the things that are going to come above the surface. We weren't hired for those. Endava is hired to bring efficiency into the back office. We were hired to try and help them take out costs. It's then when we start to build these longer relationships, we can come up with ideas and ideation. So with one of our med tech clients at the moment, we've taken out a huge amount of time in that Phase I process of data assimilation. Now that won't make the drug any quicker to bills, but it will get you to the start line quicker. So I think all these are examples within the business of where we can now build throughout the sizzle.
And that's what Endava has always done. We sort of landed and then people have seen what we have done and taken us into new areas. So it's building on what we've always done.
Yes. And I'll open the floor for questions from audience after this. I'm sure there'll be many questions on Agentic Commerce. But can something like that drive the step change in your AI adoption as well as in your growth rate?
I think we've been in Endava, I'm only 9 months in, but I've been a client of Endava for 16 years, a very happy client. I think we've purposefully not made very big public bet on AI per se. We've talked about learning it because any student should go and learn what the latest doctrine is. I think we've talked about business outcomes. I think Endava has been very good at saying we listen to our clients. We're agnostic of technology. We don't make big religious bets. But when our clients are ready, we'll then take them on the journey they need to go on.
Some of that might be taken over an inefficient technology department and making it more efficient. We're not ashamed of that. That's a great business for us. But we'll only do that nowadays, if that also involves them getting glimpses of our new capability. But we are definitely not out here, and I'm very proud of that out here saying, 1 day, we're going to flick a switch and everything is going to be AI [ F8 ]. We're here saying we serve our clients, they serve their clients, and that's why they keep hiring us. And so Mark and I were talking about this actually earlier today. I believe when we're here next time, we'll be demonstrating a huge acceleration in these conversions and all rest of it. But most of the deals that I'm seeing in the market today still start with -- I've got this year's budget. I need to get this efficiency. I'm excited about the future, but can you guys do what we've always known you can do. And our job is to blend into that some of this.
Right. Any questions from audience?
I did indeed want to ask about Agentic Commerce. You touched on it a little bit, but maybe just within the payments vertical overall, could you talk about how important that is from a use case standpoint and maybe even broader than that within the payments vertical, kind of what are you seeing? Any trends beyond Agentic Commerce that you can call out?
Yes, of course. I mean and you'll be all over this anyway, but it's taken a Dodd-Frank and other -- it's taken a while for the regulatory shift interchange to really come into force, but it's really arrived now. And we're seeing that in loyalty schemes, how do you fund them. Lots of banks saying, well I used to use interchange to fund those sorts of things. So what's the new model for that? You've then because of the global volatility in the payment space and certainly the geopolitical space, we were moving to this sort of 1 size fits all payments model.
Now we're looking at much more innovation islands. Lots of national governments looking to put real-time payments in place. Lots of leaders of nations saying solvency of data is incredibly important. I think a lot of people speculating that the fact both Visa and Mastercard are U.S. -- perceived as U.S. companies, does that create challenges for them? I think those are brilliant businesses. The 4-party model is a pretty hard thing to pull down.
But a huge percentage of the work that Endava has done, hence the reason I was a big client over the years has been to enable this shift in payments or payment gateway accelerators, what we're doing to help people modernize their platforms. And I only see that getting faster and faster at the moment. The thing is if you look at most industries, and you say, here's a new incumbent like a Revolut or a Stripe or an Adyen, as soon as these companies have got through the governance or the firewall of regulation because their platforms are so much more fit for purpose, they've just accelerated to enormous scale very, very quickly. And so the incumbent, whether that's a bank with the merchant acquiring business or whether that's a Fiserv or whether that's an FIS or a global or a Worldpay, having to react. And the difference is these aren't start-ups, these are $100 billion companies. And so we are in that space, particularly super well placed, I believe, it's 30-plus percent of our revenue. And we've got teams that have built real-time payment systems for many, many companies. So I think for us, it's good.
And then to answer your question more on the themes I'm seeing, I'm certainly seeing people look at sovereignty of data in payments as a way to create local jobs and help local companies, particularly in Asia, particularly in South America, some in Europe, but probably more so in those first 2 markets.
Yes. Premise is about 15%, just to correct.
Well, banking and capital markets...
As a follow-up to the payments question, the other kind of big buzzword and payments aside from Agentic Commerce is Stablecoins. Can you talk about what your clients are or if they're trying to incorporate stable coins into their kind of payments workflow and what applications you see as being kind of most relevant for these companies over the next 3 to 5 years?
Yes. I mean I think, candidly, we don't profess to be an expert in that particular area, but we have enough people in our payments practice that understand it well enough [indiscernible]. So we are talking to lots of our banking clients, lots of our government clients about what -- in fact, I have posted a very VIP delegation from Vietnam a couple of weeks ago, it's public, so it's not new news, who came to the U.K. who are doubling down on crypto as a nation. And we were advising them on applying right touch regulation and rules of law to that environment. That for us is an in for Endava. That's a way of demonstrating that we understand what it means to run a regulated payments environment. I think on the individual technologies itself, the U.K. has been a bit behind the curve on this for me, which is why I spent most of my time. I think the U.S. is opening up to it more now. But yes, I can ask one of my team if it's helpful. Andy Davis probably is the right guy to help you with that.
Can I circle back to the Dava Flow platform and ask you to just explore the potential economic impact of clients shifting more towards Dava Flow for their engagements with Endava?
It's not a platform. I'll call it a methodology all way of working. It's basically using agents to deliver work of what would have been humans, one of a better word. And maybe just to simplify it, we sort of envisage where a scrum team to deliver what would have been 8 people. The new scrum team would be like 4 people and 4 agents. But it's the whole sort of methodology about how that work is delivered to governance because it can move very quickly through each of the phases. There's no equivalent in an Agentic AI world of daily stand-ups, feedback loops, the testing scenarios. It flows very, very, very sort of quickly. So thinking through the whole process from initiation right through to the production phase and not getting in the way of it, but having the right governance and checks around at the human in the loop. So it's a methodology. It's a proprietorial methodology using agents. And these are our tools and accelerators as well. So it's how do you orchestrate them and put the right balances and checks them.
And I think it's -- I agree, it's a movement. And because John and Mark logged before I arrived, took the right decision, no question to invest heavily in this area by going AI native ourselves. We -- across Endava, if you come to the locations, everybody is using AI. And so when we talk to clients, there's a real authenticity about it because we're saying this is the -- and you've seen some of the costs that we've been able to take out of the business, some of the efficiency that we're getting by using it. And I think that makes the job much easier for me, engaging with clients and saying, now here are the examples that have worked for us. So do you want to go on that journey. But it's -- as Mark says, it's called Dava Flow because it is a movement, it's a behavior, it's not a platform, and it's not a product. And I think that's resonating quite well because everyone's been asked to pick -- make a religious bet at the moment.
Just one more question, [ Friedman ].
So you're in an organization that's dominated by technology people, engineers, et cetera, et cetera. And so generally, the natural reaction to seeking growth is to come out with a thing. It's say here, we have a better thing now. And sometimes there's opportunities in commercial execution. We just get better at the soft side of the business in some respects, who we're targeting, getting higher up in the organizations. There's probably 50 things under that stack of things. Are you working on that as well, too? Because I know we haven't asked any questions in that area. So I was just curious about the execution side.
Are you asking about the go-to-market or...
And also how that affects the culture?
Yes. So we've always been industry-led. So it's about what are the -- how is technology going to impact the industries that we serve. What we're focusing on now is to take it up a level to the C-suite in terms of what are the big issues that need resolving at that level with our propositions. So it's always proposition led. It's the outcomes in terms of what is led. The technology is almost all secondary in that respect. Where the technology is important because it's driving some of these themes of disruption and change in the industries and AI is causing big disruption, and we are feeling it ourselves, but it's causing issues with clients. So it's how do we create solutions for clients to do that well. So we advise them, but we can go beyond that and also sort of build. So it's solution-driven, market-driven, but you have to have technical competence, engineering capability. We have a very strong engineering sort of heritage, which is very sort of valuable. But it's how do you hone it and build the solutions that the client wants and the outcomes the client wants is the key.
And let me add to that. So -- and this isn't perhaps always understood about Endava. The culture in Endava, is a superb question. 11,000, 10,500 of the Endavans are in what we call our locations, 62 locations from Eastern Europe to Vietnam to South America, okay? Vietnam [ is paying now ]. These are people who, when you go and visit these locations, the mayor of the town turns up because we're the biggest employer. The embassy will turn up because it's very important. We're giving these people incredible lives. In many cases, in Romania and Moldova, 100 clicks from a war zone. So this is really material to your question because these are hungry-driven people. They're not fascinated by the technology per se. They're excited about working on projects that are exciting.
So when Toyota -- so we have an internal channel called Dava Studios. So when we can show that Toyota have just had their best season on the racetrack and show the Toyota car winning because we built the AI dashboard, that's what motivates them. So they're motivated by working on cool stuff. And what I say to the engagement team, the growth team, is if we're not explaining why we got the CEO's attention in that organization and why they chose Endava, then we're letting our teams down because they're working on game-changing stuff. And so I think that's the other thing. Endava, and I will say this because John is a good friend of mine. John, by his very nature, he's a very humble guy, and Endava had many, many great years as a very humble organization, delivered well in agile. But we have to get above the parapet and point out to people some of the stuff that we're working on. The numbers are a consequence. They will come through. It's actually about working on brilliant stuff that other people want to replicate.
All right. Thank you so much.
Thank you.
Very good. Thanks, guys. Thank you.
Endava ADR — Q1 2026 Earnings Call
1. Management Discussion
Good day and welcome to the Endava's First Quarter Fiscal Year 2026 Conference Call. [Operator Instructions] Please note this event is being recorded.
I would now like to turn the conference over to Ms. Laurence Madsen, Head of Investor Relations and ESG at Endava. Please go ahead.
Thank you. Good afternoon, everyone, and welcome to Endava's First Quarter of our Fiscal Year 2026 Conference Call. As a reminder, this conference call is being recorded. Joining me today are John Cotterell, Endava's Chief Executive Officer; and Mark Thurston, Endava's Chief Financial Officer. Before we begin, a quick reminder to our listeners.
Our presentation and our accompanying remarks today include forward-looking statements, including, but not limited to, statements regarding our guidance for Q2 fiscal year 2026 and for the full fiscal year 2026; the impacts of headwinds facing our industry and business, trends in our industry including with respect to developments with AI, enhancements to our technology and offerings, our pipeline of client opportunity and our ability to convert such opportunities into contracted orders; the benefits of our partnerships; our pricing models; demand from clients for our technology services; our ability to create long-term value for our clients, our people and our shareholders; and our business strategies, plans, operations and growth opportunities.
These statements are subject to risks and uncertainties that could cause actual results to differ materially from those contained in the forward-looking statements. Actual results and the timing of certain events may differ materially from the results or timing predicted or implied by such forward-looking statements and reported results should not be considered as an indication of future performance. Please note that these forward-looking statements made during this conference call speak only as of today's date and we undertake no obligation to update them to reflect subsequent events or circumstances other than to the extent required by law.
For more information, please refer to the Risk Factors section of our annual report filed with the Securities and Exchange Commission on September 4, 2025 and in other filings that Endava makes from time to time with the SEC. Also, during the call, we'll present both IFRS and non-IFRS financial measures. While we believe the non-IFRS financial measures provide useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with IFRS.
Reconciliation of such non-IFRS measures to the most directly comparable IFRS measures are included in today's earnings press release as well as the investor presentation, both of which you can find on our Investor Relations site or on the SEC website. A link to the replay of this call will also be available on our website.
With that, I'll turn the call over to John.
Thank you, Laurence, and welcome, everyone. We appreciate you joining us for our first quarter fiscal year 2026 earnings call. Endava continues to be deeply engaged by and with major companies across the world as they look for support in navigating the journey towards AI whilst ensuring operational resilience in existing platforms and devices. We believe the partnerships with major technology giants and the decisions we took 3 years ago, which led to the development of our AI native change delivery lifecycle now branded DavaFlow, see us well placed for the coming years.
However, we continue to navigate the challenges associated with this transition in business models, delivery approach and acceleration of the new AI-driven digital wave. The first quarter results were lower than guided primarily due to an unexpected credit made to a client that arose subsequent to our last earnings call as well as certain non-large strategic pipeline opportunities that did not convert into revenue during the quarter as anticipated. While these factors weighed on our performance, our ability to secure a multiyear strategic relationship with a leading payments company of up to $100 million demonstrates the strength of our client relationships.
This partnership will utilize the best of Endava's global delivery capability as well as our AI and advanced engineering capabilities to streamline our clients' technology platforms and enhance existing capabilities. This represents a prime example of the type of deal and partnership we are targeting, utilizing our capability as an AI-native technology-agnostic transformation partner. Our broader partner ecosystem is already generating incremental potential pipeline opportunities and client interest in DavaFlow is accelerating. I will return to each of these topics later in the call.
Following the sales leadership realignment announced last quarter, we recently hired a Chief Growth Officer for Commercial Services for Europe and North America. These changes are already sharpening our customer engagement model, which is evident in the composition of our potential opportunity pipeline, which we are tracking closely. We remain committed to disciplined cost management to protect margins while continuing to focus on growth. Starting with an update on our AI-related engagements.
AI now anchors many clients' technology road maps and we are partnering across a spectrum of projects from early proof of concept to enterprise-wide rollouts and subsequent optimization efforts. Following the engagement for a leading U.S. health care services provider where we deployed AI to automate the intake and summarization of medical bills and supporting documentation, we have now advanced integration into the client's adjuster portal and enabled both near real-time and scheduled processing to support peak volumes.
The architecture is built for compliance and auditability with U.S. data residency and targets high accuracy to meet over 95% precision while holding unit costs below $0.05 per page. Early performance indicates faster, more consistent decisions and a clear path to materially lower per claim handling costs. Building on the Enterprise ChatGPT program, our collaboration with a leading financial compliance technology provider has progressed. We partnered with OpenAI to drive a company-wide deployment of ChatGPT Enterprise anchored in governance and enablement.
Within 3 months, more than 500 licenses were rolled out with a single sign-on, role-based access and audit logging. Key team members across finance, legal, IT, client services and support received train the trainer enablement to develop high value use cases and custom GPTs reinforced by structured communications, weekly show and tell sessions and continuous measurement. Adoption has scaled with growing catalogs of validated use cases and measurable productivity gains are emerging in document workflows and client service operations.
These first 2 client cases are examples we have previously discussed on earnings calls and I'm covering them to show how these engagements are progressing, to show how engagements are building and deepening once production solutions are in place. For a leading U.S. retail pharmacy chain, we are modernizing a core handheld application by upgrading its code base using AI-assisted analysis leveraging GitHub Copilot. We completed a comprehensive assessment and prepared a 2-phase execution plan that targets the highest impact fixes and derisks the upgrade.
The resulting playbook is designed to be repeatable across other applications; strengthens security, reduces technical debt and supports a faster release cadence. Initial results indicate AI-enabled reviews and automated testing are lowering manual effort by between 25% and 30% and shortening migration time by between 20% and 25%, implying a projected productivity uplift between 30% and 35% once both phases are completed. For a global energy and utilities provider that runs large-scale power grid simulations, we migrated a 400,000 line Fortran system.
We built AI-assisted passes and automation tools with agent coding tools to preserve program flow while refactoring syntax and improving memory management. We also identified code sections tied to domain concepts to speed future feature delivery. This approach reduced manual edit risk and enabled automated conversion at scale. Initial benchmarks indicate up to close to 30x faster code changes with improved reliability.
For an e-learning provider serving over 12,000 health care and human services organizations, we developed an AI-enabled content studio that streamlines the entire content lifecycle; drafting, review, quality assurance, export and accreditation; for a catalog of 7,000-plus courses. Built on Windsurf and integrated with the client's enterprise AI infrastructure, the platform generates course outlines and transcripts, runs policy-based QA agents, automates score imports and compares accreditation standards. Automation rules and validation tests further enhance compliance and operational consistency.
Results show end-to-end authoring efforts have fallen by approximately 30% and modeling shows projected time savings of 30% to 50% when scaling updates across the full course library. Turning to partnerships. Our investment in our partnership with OpenAI is expanding as we've enrolled a group of Endava engineers in OpenAI's newly launched partner exclusive certification program. Our team is pursuing multiple opportunities across the OpenAI product suite through training created by OpenAI that is only available to service partners. This is another step to deepen our knowledge and advance our AI native delivery capability.
On the commercial side, the joint go-to-market framework we created in partnership with OpenAI is producing measurable results with wins in the insurance sector. We continue to grow our dedicated Google Cloud business unit. In collaboration with Google Cloud, we continue to increase the number of Gemini enterprise projects that we are actively engaged in. Each engagement follows a production-grade reference architecture with explicit safety and audit controls ensuring that pilot outcomes can be migrated into compliant enterprise environments.
One of these projects involves a leading U.K. bank where we are rolling out AI-enabled digital assistance that give employees fast secure access to internal and market data. Early pilot results indicate shorter query resolution times and improved policy compliance laying a foundation for institution-wide adoption of agentic workflows. We also continue to strengthen our partnership with Salesforce by investing in agentic AI and innovation with a focus on applying agent force across Salesforce's core clouds to assist customer-facing teams, streamline operations and unlock new levels of engagement and productivity.
This reflects Endava's commitment to staying at the forefront of Salesforce innovation and helping clients turn emerging AI capabilities into real measurable impact. And now with an update on our large strategic deals defined as multiyear large-scale engagements. In addition to the multiyear payments deal I mentioned earlier, we deepened our engagement with Convex, an international specialty reinsurer, by signing a new agreement. This builds on the success we have achieved together in recent years as Convex continues to invest in innovative technology and deliver consistently high quality service.
This partnership enables us to deliver a range of capabilities enabling Convex to continue creating a business that has data at its heart and a strong emphasis on analytics to make better underwriting decisions. In mobility, we have extended and expanded our long-standing partnership with Toyota Racing Development as their official IT consulting partner in 2026 and beyond. As part of the partnership, Endava will leverage its AI-enabled accelerators and frameworks to modernize core Toyota Racing Development production systems and enable digital transformation for the business.
Next, let me outline how our delivery model is evolving and what that means for execution and client outcomes. The pace of AI innovation remains exceptionally fast and the nature of our client discussions has evolved just as quickly. Where a few quarters ago we were explaining foundational concepts such as intelligent agents, we are now examining how those agents can be deployed to deliver measurable efficiency across customer-facing and core operations. Clients are starting to move beyond the search for a single killer application and are instead seeking opportunities to embed AI throughout their technology stacks and operating models.
This marks the beginning of the transition from chasing incremental changes brought about by embracing AI to notable productivity changes. We're now spending time shaping larger scale projects that can only be delivered through the strategic adoption of AI. Purpose-built for an environment in which autonomous software agents participate in delivery, DavaFlow treats flow as the next progression beyond agile by embedding AI into every activity. The delivery lifecycle is organized into 4 sequential yet feedback linked phases: Signal, Explore, Govern and Evolve.
Throughout all phases, human oversight or human in the loop guides AI contributions and the system learns and improves with each cycle. In Signal, we deploy market and estate scanning agents to surface and qualify opportunities. The agent reacts to signals in the market or client environment and feeds qualified opportunities into the lifecycle with confidence scores. In Explore, we use human AI collaboration to convert these signals into evidence solution designs, producing prototypes, requirements and models at pace. The aim is to reduce uncertainty and finalize what needs to be built supported by evidence.
In Govern, we assemble and automate the build. Engineer oversight combines with agent-generated code to enforce best-in-class controls. Evolve is the post-deployment phase where the solution is in production with continuous improvement. Human-in-the-loop checkpoints span every phase so that each iteration strengthens the next. AI agents watch the system's telemetry, user behavior and performance data to detect anomalies or opportunities. Across the 4 phases, we take our lifetime experience of distributed agile at scale and optimize our approach to best organize agents at work with agentic checkpoints and humans in the loop at the core of the new approach.
We have equipped our teams with playbooks and training materials and all delivery teams are expected to complete the DavaFlow training and immersion before the close of this current financial year. We ended the quarter with 11,636 Endavans representing a 2% decrease from the same period last year. We are deepening our AI talent pool and embedding new capabilities across the business, positioning Endava to help clients turn emerging technology into near-term operational gains.
We're expanding and upskilling our AI talent while trimming roles where market demand has declined. Our inaugural Dava.X Academy created to train the next generation of AI skilled professionals through 2,900 applicants and resulted in 470 hires across 9 delivery locations. And our recent TechFest engineering event brought together those new hires working in 48 cross-functional teams to address 24 client-inspired challenges. Every team produced a working minimal viable product under mentor guidance.
Before we conclude, I want to recognize every Endavan for the perseverance and focus you continue to show as we steer through this period of rapid digital evolution and translate change into opportunity. Our priorities remain clear: sustain growth that endures, safeguard the distinctive culture that defines us and deliver technology solutions that equip our clients to set the pace confidently in an ever-shifting market.
I'll now hand over to Mark for a closer look at our quarterly financial results and guidance for the upcoming quarter and the remainder of the fiscal year.
Thanks, John. Endava's revenue totaled GBP 178.2 million for the 3 months ended September 30, 2025 compared to GBP 195.1 million in the same period in the prior year representing an 8.6% decrease. In constant currency, our revenue decreased 7.3% from the same period in the prior year. As John already mentioned, the first quarter results were lower than anticipated primarily due to a matter in the United States relating to an unexpected credit made to a client that arose subsequent to our last earnings call as well as failure to convert certain non-large strategic pipeline opportunities into revenue as previously anticipated.
Loss before tax for the 3 months ended September 30, 2025 was GBP 8.5 million compared to a profit of GBP 4.2 million in the same period in the prior year. Our adjusted PBT for the 3 months ended September 30, 2025 was GBP 9.9 million compared to GBP 19.2 million for the same period in the prior year. Our adjusted PBT margin was 5.5% for the 3 months ended September 30, 2025 compared to 9.9% for the same period in the prior year. Our adjusted diluted earnings per share was 15p for the 3 months ended September 30, 2025 calculated on 53.2 million diluted shares as compared to 25p for the same period in the prior year calculated on 59.4 million diluted shares.
Revenue from our 10 largest clients accounted for 36% of revenue for the 3 months ended September 30, 2025, in line with the same period last fiscal year. The average spend per client from our 10 largest clients decreased from GBP 7.1 million to GBP 6.4 million for the 3 months ended September 30, 2025 as compared to the 3 months ended September 30, 2024 representing a 9.9% year-over-year decrease. Of this, FX movements contributed to a 2% year-over-year decrease and the rest of the decline is in line with the rest of the business.
In the 3 months ended September 30, 2025; North America accounted for 42% of revenue, Europe for 24%, the U.K. for 28% while the Rest of World accounted for 6%. Revenue from North America decreased by 1% for 3 months ended September 30, 2025 over the same period last fiscal year. The decrease was driven by FX with underlying constant currency growth. The unexpected client credit mentioned in my opening comments was more than offset by the reclassification of a large payments client from the U.K. to North America as the relationship with the client is now based there.
Comparing the same periods, revenue from Europe declined 12.8% due mainly to weakness in the TMT and mobility verticals. The U.K. decreased 17.9% due mainly to the reclassification of the client referred to above to North America and the Rest of World increased 9%. Our adjusted free cash flow was GBP 9.2 million for the 3 months ended September 30, 2025, up from GBP 3.5 million during the same period last fiscal year. Our cash and cash equivalents at the end of the period totaled GBP 47.2 million at September 30, 2025 compared to GBP 59.3 million at June 30, 2025 and GBP 52.8 million at September 30, 2024.
Our borrowings totaled GBP 193.2 million at September 30, 2025 compared to GBP 180.9 million at June 30, 2025 and GBP 132.6 million at September 30, 2024. Capital expenditure for the 3 months ended September 30, 2025 as a percentage of revenue were 1.7% compared to 0.6% in the same period last fiscal year. We remain committed to our share repurchase program. As of October 31, 2025 Endava repurchased 7.1 million ADSs for $115.9 million under the program and we have $34.1 million remaining for repurchase under its share repurchase authorization. Before moving on to the guide, I would like to provide some context.
As a reminder, since May 2025, we are utilizing a guidance methodology under which revenue for any unsigned large strategic opportunity in the pipeline is excluded until the related statement of work is executed and delivery has begun. By contrast, for our non-large strategic deal pipeline, we make an assessment of likelihood and timing of conversion and likely timing of revenue. Turning to the guide for the remainder of the fiscal year. We have reassessed our non-large deal pipeline and lowered our conversion into revenue assumptions.
Additionally, the client-specific issue in the United States weighed on first quarter results and will continue to affect the remainder of the fiscal year while the 3 large signed engagements John highlighted are reflected in our guidance and partially underpin the expected revenue uplift in the second half. Now moving on to our outlook. Our guidance for Q2 fiscal 2026 is as follows. Endava expects revenue to be in a range of GBP 179 million to GBP 182 million representing constant currency revenue decrease of between 8% and 7% on a year-over-year basis. Endava expects adjusted diluted EPS to be in the range of 15p to 17p per share.
Our guidance for full fiscal year 2026 is as follows: Endava expects revenue to be in the range of GBP 735 million to GBP 752 million representing constant currency revenue decrease of between 4.5% and 2.5% on a year-over-year basis. Endava expects adjusted diluted EPS to be in the range of 80p to 88p per share. This above guidance for Q2 fiscal year 2026 and the full fiscal year 2026 assumes the exchange rates on October 31, 2025 when the exchange rate was GBP 1 to USD 1.32 and EUR 1.14.
This concludes our prepared comments. Operator, we are now ready to open the line for Q&A.
[Operator Instructions] The first question today comes from Bryan Bergin with TD Cowen.
2. Question Answer
I guess I'll start on the client credit. Can you share some more detail on this credit that was not foreseen and weighed on performance? Just any sizing of that in context? Curious if that was due to company execution or maybe a choice by the client made to pull back on something? Is it isolated or could this reoccur elsewhere?
So it was unexpected, Brian. It arrived after we guided last quarter. It isn't related to remediating work. I'll qualify it as being a more procedural matter. In terms of the impact, if it hadn't have happened, we would have been at around the bottom of the revenue guide and certainly in terms of EPS, we would have been right in the middle of the range that we set last quarter. I can't really go into any more detail than that at this stage.
Okay. And I guess on demand and the pipeline conversion then, is that a demand issue or would you say some friction in the changes in the commercial responsibilities? I'm just curious whether you would say that demand has or client sentiment has changed much at all here in the last quarter. Maybe if you could just talk about how demand trends progressed through the first quarter into the early part of 2Q now.
Yes. I mean in terms of the comment around pipeline conversion in the quarter, the significant impact on revenue was the credit that we just mentioned. Pipeline conversion, we did convert pipeline. So against the high end, it was about 50% and against the low end, we were about 80%. So not as high as we would have anticipated. But in the light of that sort of performance and the ongoing sort of review of pipeline quality, we've looked at our assumptions for the rest of the year and that's resulted in us actually downgrading from the top of the guide at GBP 765 million to GBP 752 million.
It is actually offset though by some of the big wins that John highlighted on his script. So they add step change revenue basically in the second half. So they do underpin part of the ramp as we see going through into mainly Q3, Q4. But we've taken a more prudent line on the pipeline conversion in the nonstrategic deal space.
The next question comes from Maggie Nolan with William Blair.
I understand the commentary on how you're considering pace of conversions from here for the non-large accounts. But can you comment on whether there's been any client churn at unusual levels in this quarter versus recent past?
Maggie, there hasn't been a growth in client churn. And just to be clear, the client that Mark was referring to where we had the credit is an ongoing relationship and not in decline. It's just a more conservative view based on the conversations that we've been having around that inflow of the non-large deal pipeline, which is what we guide against.
Okay. And then can you talk a little bit about how you're quantifying any productivity gains from DavaFlow and just the ability to kind of drive this at scale across your model?
Yes. So we're seeing the AI shift essentially going through 2 steps. There's the sort of Gen AI with a bit of agentic coming in where organizations are largely applying a bit of an accelerator from AI to an agile methodology and getting in that sort of 20% to 30% range productivity improvement that people are talking about. What we're seeing with DavaFlow is taking that next step into using agents to do a far, far bigger element of the design and coding all under human guidance and governance and through that getting significant step-ups in productivity in the 5x to 10x type range as I covered on the call last time.
Now for us, that gives us an opportunity alongside some of these bigger deals that we're working on to significantly accelerate transformation and change in client environment. And through doing that to actually deliver a lot of benefit to the client, but also look at pulling through wider margins through that huge added value that we're delivering. Now the big deal that I covered with the large payments client is very much based on those principles and taking that DavaFlow capability to accelerate transformation for them to help with new product development and some joint go-to-market together. And it's very illustrative of the type of larger deal that we're working on, but we're not putting it into our guidance as Mark has highlighted over the last couple of quarters.
The next question comes from Nate Svensson with Deutsche Bank.
John, I wanted to go back to something you said at the beginning of the prepared remarks. I think you mentioned that you're navigating challenges associated with the transition in business model delivery approach and the acceleration of the AI wave. I guess just from my perspective given the growth in the business, the lower guide; seems like there's been some struggles with everything that's going on. So I'm just hoping you can take a step back and maybe talk at a higher level on what your strategy is to successfully navigate these changes. I know there's macro considerations, but I guess beyond that, what do you think isn't going right and what's the plan internally to try to turn things around and ultimately capitalize on some of the opportunities that are ahead of you?
Yes. So for us, we are pushing very, very hard on this shift to being AI native. Our vision is that over the next 2 to 3 years, AI becomes a much, much more significant player in our industry in the way in which people deliver to clients; deliver code, deliver requirements and so on. And in pushing hard on that shift, we are moving much faster away from the old models than I believe many of our peers are. The result of which is that we are accelerating deliveries to clients in the current environment under the old T&M model largely. This quarter, we were 24% outcome-based, which is still rising, but it does mean that 76% of our revenue is coming in on a T&M basis.
And as we're delivering at a much higher productivity, that is having an erosion on the revenue that's coming through the business. That is being offset by the growth in demand for our new AI native approaches where every Endavan is using AI every day in the delivery of services to our clients. And that shift is very, very fast. Last quarter I reported that just over half of our services were AI related covering using AI to change and accelerate the SDLC, software development lifecycle, or identifying client workflows or indeed in deploying AI into the physical world. This quarter that greater than half has moved to over 70% of our services are AI related on the same measure.
So it is a strong shift and strong acceleration in productivity and that is having headwinds for us on revenue on the old model. The strategy and the focus is all around driving the fastest shift we possibly can to the new model where we are writing more outcome-based deals with clients, which locks in the opportunity to deliver greater benefit to the client using AI, but also to improve our margins. And we are seeing that come through in the rising proportion of outcome-based deals and in the margins attached to those deals. And so that's the strategic shift that we are going through. We are pushing through it very fast and we're probably carrying more pain in the short term because of that accelerated shift to the future state that we're pushing through.
Makes sense and I appreciate the detailed response there. I did want to follow up on this $100 million deal with a leading payments company. My guess is that would be a renewal with maybe one of your 2 large payments partners, but maybe you can correct me if that isn't the case and it was a new logo. But beyond that, maybe you could use that deal as kind of a launch point to expand more into general commentary on pricing and productivity commitments you're having to make in the current difficult macro sort of in order to get these larger deals across the finish line.
So the $100 million deal is not a renewal of one of our larger payments clients. It is an existing payment client, but really quite small and well over 85%, 90% of that deal is net new revenue to us. And it is around helping that client transform their business. They are as equally excited about us helping them do that as we are about helping them drive the transformation and bringing our engineering skills to bear on their estate. Mark, do you want to pick up on the pricing comment?
Yes. Pricing, I mean as John said in terms of the split of revenues, we are still mainly time and materials. So we still look at the average rate per workday and it is very much stable quarter-to-quarter. Our issue is volume more than anything else certainly in the T&M space.
Nice to hear about the payments one.
The next question comes from James Faucette with Morgan Stanley.
It's Antonio on for James. I wanted to ask about your fiscal year '26 guide. It looks like in the back half there's still a strong acceleration and I know that you mentioned those 3 large deals are contemplated in that. But what gives you confidence that those large 3 deals will sort of come through in the back half? Any color there would be appreciated.
So the 3 deals are signed so they are committed spend that involves ramp-up in the second half. I'll let Mark give you a little more color.
They are and it's not just those 3 deals that are additive. So we've signed deals going back when we were guiding for Q1 at the end of the year. So there is a further sort of layering on of, I'll call it, step change revenue because that's typically the nature of it. And that layering on of these larger deals on to the run rate, which we'll refer to the nonstrategic deal revenue stream, gives confidence in that back half. I mean there is still a pipeline to convert as we sort of highlighted when we were discussing the Q1 performance. So there is always sort of risk in the figure, but we have given a range of GBP 752 million, GBP 735 million, which we think accommodates that risk in terms of the pipeline conversion on the nonstrategic big deals.
Got it. That's helpful. And then as a follow-up, I wanted to ask on your capital allocation priorities. Like how are you balancing investment within AI and also share buybacks? Just trying to get a sense of that as well.
The share buyback continues. We still have $150 million approval from the Board. We continue to invest. I mean part of this year, we highlighted there was going to be margin impact through the investment in this shift mainly in terms of technology and onboarding people and that still remains the case. As John said, we are pushing very fast on this and sacrificing near-term profitability for the upswing in profitability that we think will come through in the outer years.
The next question comes from Jonathan Lee with Guggenheim Partners.
Can you help decompose what's contemplated in your outlook across the high and low end of the range as it relates to pipeline conversion required and the level of go get required and whether you've given any sort of allowance for macro uncertainty?
Well, in terms of the range for the full year, this is excluding obviously a strategic deal pipeline, which is growing strongly [indiscernible]. The range on the nonstrategic deal pipeline is for the full year I think it's about 79% to 81%. In the current quarter, it is very high, it's about 95% to 93%. So we think the quota for Q2 adequately is ranged. It does take into account that the quarter and in December, we have a lower number of working days, which is a headwind against the sort of revenue when you look at it sort of sequentially, but we have strong confidence in Q2. So Q3 and Q4 where we have the high levels of pipeline, we have done a sanitization of the pipelines being proposed in the business and we believe that those are achievable. And as I said, we have reduced the overall guide to take account of that.
And as you think about some of the margin challenges you're facing, how are you thinking about the potential for expansion levers and investments into the end of the calendar year and into the start of '26?
Well, I think as you've probably seen, Endava has high operational leverage, which is a sort of a negative and a positive. So we're very much driven by top line performance and reacting accordingly. Visibility has to be good for us to react in sort of times. So if we have slow revenue progress, we have to take out costs as we respond to that. But similarly with increasing revenue, we get a strong profitability recovery, which is what is implied basically in the full year guide that we get on that growth trajectory. And there is some strong sequential growth quarter-on-quarter implied by those larger deals starting to deliver revenue. But it does give us high operational leverage, which moves up our gross margin quite significantly and delivers strong EBITDA performance.
The only thing I'd add to that is if you look at that strategic pivot that we're talking about going through at the moment, that does have a margin impact. There's a friction element of that change, the change of skills, making sure that our people are moving to being AI native and having to take action where people are unable to make that shift or carrying skills that become less important in an AI native world going forward. So that friction element is also hitting the short-term margin picture.
The next question comes from Phani Kanumuri with HSBC.
My question is on your headcount. There seems to be a bit of increase quarter-on-quarter. Is this in anticipation for demand in the second half of the year? And then how do you see the headcount strategy in terms of the AI productivity that you're seeing and the macro headwinds that you're seeing for, let's say, the rest of the fiscal year?
Yes. So a lot of the increase in the headcount you've seen is the Dava.X Academy that I talked about on the call where we're specifically targeting bringing in strong AI native leaders across the organization as well as bringing in graduates who are from their university background more AI native, but perhaps less experienced from a coding and governance point of view so that you can create that mix of teams who've got that natural affinity with AI, with prompt engineering and so on alongside the experienced headcount.
And so enabling that shift is part of the friction element I was talking about for Jonathan where we're investing in the people who move into that space and then getting them placed into client environments. So that's part of that shift up in headcount. We still continue to see us training and bringing in AI native people and losing people who are not going to make that shift into the future. And so you're still seeing an attrition level that's running higher than it has been historically because of that churn that's going through the business. And we anticipate that that will carry on for another couple of quarters before we settle down into being much more completely in the new world.
[Operator Instructions] The next question comes from Puneet Jain with JPMorgan.
I wanted to follow up on the $100 million deal, the one that has 85%, 90% of new work. Can you share more details like the duration of that revenue or type of work you will do specifically around new development versus managed services? And then why that client and that deal led to a very different outcome than others? Are these type of deals replicable?
Yes. So it's a very exciting deal for us. It's a headline of a number of other deals that we're working on that would fall into the same category. The duration is over 5 years and it's a commitment on the part of the client to spend that level of money with us in return for us driving accelerated transformation for them. It is almost all in the new development space rather than in the managed services space. And there are a number of pillars of transformation, of new product development and of joint go-to-market exploration of capability that is built into how we will deliver value back to the client for that spend that they have committed. It's a very close partnership mindset where together we're going to help transform that part of the market. And obviously it's in the payment space so we bring a lot of payments experience as well as the AI capabilities and so on that I've been talking about.
Got it. And can you also talk about the timing given the second half guidance for revenue implies, give or take, GBP 10 million in incremental revenue a quarter in Q3 and Q4. So can ramp in this deal and the 2 other large deals alone drive that incremental revenue in second half of this year?
So incrementally, your math is right around the GBP 10 million a quarter. It's not quite phased that way, but your math is roughly right. The deals that we've landed are contributing roughly about sort of 50% of that ramp and the balance is coming from the pipeline conversion on the existing sort of run rate. And that is after us look -- and that is the nonstrategic deals revenue sort of stream, if I can put it that way. So it's coming half and half from the big deals that we have landed, but also some of the pipeline conversion in the existing run rate business if I can call it that.
This concludes our question-and-answer session. I would like to turn the conference back over to John Cotterell for any closing remarks.
Thank you all for joining us today. In closing, we anticipate a gradual recovery over the balance of the year with being assisted by those large strategic deals that we recently signed or indeed signed back in the summer, which kick in in our H2. Our broader partner ecosystem is already generating incremental potential pipeline opportunities and client interest in DavaFlow is accelerating. So I look forward to speaking with you all on our next earnings call in February. Thank you very much.
The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.
Endava ADR — Q1 2026 Earnings Call
Financial data from Endava ADR
Revenue
Revenue is the sum of all sales generated by a company, e.g. for its products or services.
Revenue (TTM) metric explainedDirect Costs
Direct costs are the costs incurred directly in connection with the manufacture of the product or service.
Gross Profit
Gross Profit indicates how much of the revenue remains in the company after deducting direct production costs. If the percentage share of sales is calculated, this is referred to as the gross margin.
Gross Profit metric explainedSelling and Administrative Expenses
Selling, general and administrative expenses (SG&A) include all expenses for marketing and sales as well as the general administration of the company.
Research and Development Expense
Research and development costs (R&D) provide information on how much the company invests in the research and development of its products. The costs are particularly interesting as a percentage of revenue and in comparison to direct competitors.
EBITDA
EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) is the company's earnings before interest, taxes, depreciation and amortization. The EBITDA margin is calculated as a percentage of sales.
Depreciation and Amortization
Depreciation represents reductions in the value of the company's assets (e.g. due to wear and tear on machinery).
EBIT (Operating Income)
EBIT (Earnings Before Interest and Taxes) is the company's profit before interest and taxes, also known as the operating income. The EBIT Margin is calculated as a percentage of sales at
.
Net Profit
Net Profit represents the profit or loss after deduction of all costs.
Net Profit metric explainedStocksGuide Premium
| Mar '26 |
+/-
%
|
||
| Revenue | 968 968 |
7%
7%
100%
|
|
| - Direct Costs | 762 762 |
3%
3%
79%
|
|
| Gross Profit | 206 206 |
19%
19%
21%
|
|
| - Selling and Administrative Expenses | 188 188 |
5%
5%
19%
|
|
| - Research and Development Expense | - - |
-
-
|
|
| EBITDA | 19 19 |
67%
67%
2%
|
|
| - Depreciation and Amortization | 23 23 |
8%
8%
2%
|
|
| EBIT (Operating Income) EBIT | -4.24 -4.24 |
113%
113%
0%
|
|
| Net Profit | -543 -543 |
2,345%
2,345%
-56%
|
|
In millions USD.
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Endava ADR Stock News
Company Profile
Endava Plc engages in the provision of technology services. It focuses on finance, insurance, telecommunications, media, and retail companies. The company was founded by John Edward Cotterell in 2000 and is headquartered in London, the United Kingdom.
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| Head office | United Kingdom |
| CEO | Mr. Cotterell |
| Employees | 11,225 |
| Founded | 2000 |
| Website | www.endava.com |
