Endava plc

Good day and welcome to the NDAAVA third quarter fiscal year 2026 conference call. All participants will be in listen only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on your telephone keypad and to withdraw your question, please press star then two. 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 accompanying 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, our people and 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 Security and Exchange Commission on September 4th, 2025 and in other filings that NDAAVA 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 RFIS. 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 relation 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. 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 guide 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, And finally, large complex outcome-based contracts taking longer to execute than planned. During the quarter, we took a goodwill impairment of £364.6 million, which is a non-cash 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're 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, a modular accelerator call for next generation payment platforms delivered through a data 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 data flow. We now have 12 clients where data flow is deployed as compared to three 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 FY25 to 15% of total revenue in Q3 FY26. or 27 million pounds. 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 this 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 Indava'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 healthcare, with additional attention on telco, mobility, and travel. On AI adoption, clients are moving beyond isolated productivity pilots. They now want 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 stages of maturity, we're seeing increasing numbers implemented into production. Adoption is becoming more operational, more governed, 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 solutions 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 Davaflow 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've 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. For 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-disrupted partners, recognized for expertise with 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 UK high street bank. The project is expected to deliver an enterprise grade agent gallery that lets the bank's developer community register, govern and discover custom built agents. fully integrated with Google data platforms, such as BigQuery 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 longstanding 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 three concurrent requirements. One, lowering the marginal cost of scaling. Two, tightening operational efficiency and control. And three, keeping run to innovate around embedded commerce, omni-channel acceptance, platform consolidation, and marketplace models. Our answer is PGX delivered through DavoFlow. BGX provides a reusable core, spanning digital acceptance, orchestration and routing, merchant portals, onboarding, settlement, fraud management, developer tooling, partner-slash-ISV enablement, and back-office services. So clients can modernize selectively and still differentiate at the product and experience level. Shared configurable components cut scaling costs. Standardized orchestration and back office services boosts efficiency and leaves headroom to innovate. Crucially, PGX supplies the data and workflow layer needed to introduce AI-enabled operations and agentic commerce across the front office, onboarding, servicing, and back office. Built with agentic AI and strict human-in-the-loop governance, PGX demonstrates that 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 three 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 TIL by NatWest, NatWest Group's merchant payments arm, to modernize and expand its payments acceptance platform. Under the partnership, Endava will deploy DavaFlow together with components of PGX to speed the rollout of new fully integrated products and services while improving flexibility, scalability, and end-to-end performance across the payments lifecycle. Working jointly, the two companies have mapped a business and technology roadmap that links 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 UK financial institution, reinforcing our credentials in payments transformation. Second, PGX continues to gain momentum with two 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. DataFlow supplies the delivery engine that converts these modernization programs into measurable commercial value and seamless connectivity to ecosystem partners such as payment schemes, acquirers, POS hardware, and compliance providers. Some other client wins. We have also recently renewed our longstanding partnership with Slovenia's Ministry of Finance and Financial Administration through to 2028. bringing the relationship to more than two decades. Under the new agreement, we will continue to operate and enhance eDAVKI, 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. eDAVKI 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 two years and expand into additional roles and delivery teams. Our collaboration with a global brand and vehicle manufacturer has progressed from standalone engineering projects to an embedded partnership that has designed, built, and operated cloud native data platforms for connected vehicle services, real-time performance monitoring, provided around-the-clock support services, and delivered logistic 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 lifecycle 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 Davaflow and AI projects. Over the quarter, Davaflow has shifted from exploratory use to enterprise adoption. We enhanced the framework through a combination of partnerships and by applying it in two large-scale live engagements. Firstly, a large-scale implementation engagement in a regulated high assurance environment. And secondly, the Nexus Technical Operator Programme, a previously announced engagement in the payments vertical. We have also continued to advance an AI-enabled human movement analysis platform for a leading high-performance sports organisation, 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, strengthened the core analytics pipeline, and expanded synthetic data sets to improve performance across real-world scenarios. We also introduced more structured measurement through accuracy dashboards, regular comparisons to previous versions, and standardized evaluation against labeled 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. Indaba delivered a Google Cloud agent space 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 coordination 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 discipline 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, Jonk. Revenue for the quarter ended March 31st, 2026 was £178.5 million. The revenue miss in the quarter was due to opportunities slipping 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 £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. The last before tax for the three months ended March 31, 2026 was £372 million, which includes a non-cash goodwill impairment of £364.6 million compared to a profit of £13.6 million in the same period in the prior year. Our adjusted PBT for the three months ended March 31, 2026 was £3.2 million, compared to 24.6 million pounds for the same period in the prior year. Our adjusted PBT margin was 1.8% for the three months ended March 31st, 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 UK tax losses in the UK. As a consequence, we have taken an exceptional charge of £364.6 million in relation to the impairment of Goodwill and £23.2 million regarding the derecognition of the deferred tax asset. Both charges are non-cash 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, leaving 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 five pence for the three months ended March 31st, 2026, calculated on 52.2 million diluted shares as compared to 34 pence 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 three months ended March 31st, 2026, compared to 39% in the same period last fiscal year. The average spend per client from our 10 largest clients decreased from 7.5 million pounds to 7.1 million pounds for the three months ended March 31st, 2026, as compared to the three months ended March 31st, 2025. representing a 5.6% year-over-year decrease. Of this movement, FX contributed to a 3.7% year-over-year decrease due to US dollar weakness in the quarter. In the three months ended March 31st, 2026, North America accounted for 38% of revenue, Europe for 23%, the UK for 33%, while the rest of the world accounted for 6%. Revenue from North America decreased by 5.5% for the three months ended March 31st, 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 UK decreased 15.4%, due mainly to the reclassification of a large payments client from the UK 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 3.1 million pounds for the three months ended March 31st, 2026, from a positive 17.5 million pounds 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 £48.4 million at March 31, 2026, compared to £59.3 million at June 30, 2025. and £68.3 million at March 31st, 2025. Our borrowings increased to £195.8 million at March 31st, 2026, from £180.9 million at June 30th, 2025, and £136.5 million at March 31st, 2025, primarily to support the funding requirements of our share repurchase programme. Capital expenditure for the three months ended March 31st, 2026 as a percentage of revenue was 1.6% compared to 0.6% in the same period last fiscal year. Going to the guide, 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 follows. We expect revenue to be in the range of £181 million to £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 9 to 13 pence per share. Our guidance for full fiscal year 2026 is as follows. We expect revenue to be in the range of £721.8 million to £725.8 million, representing constant currency revenue decrease of between 6.0% and 5.0% on a year-over-year basis. We expect adjusted diluted EPS to be in the range of 45 to 49 pence per share. The above guidance for Q4 fiscal year 2026 and the full fiscal year 2026 assumes the exchange rates on April 30th, 2026, when the exchange rate was one British pound to 1.35 US dollar and 1.16 euro. This concludes our prepared comments. Operator, we are now ready to open the line for Q&A.

Thank you. We'll now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If your question has already been addressed and you'd like to remove yourself from queue, please press star then two. Our first question today comes from James Fawcett at Morgan Stanley. Please go ahead.

Thank you very much. Wanted to dig in quickly into two 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 evaluation, 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 booking 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 deal levering is an increasing priority, et cetera. Thank you very much.

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 three times 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, you know, a substantive element of the business that we expect to grow from. We've seen that in respective deals that are coming through. They are more complex in nature, outcome-based, looking at serious transformation across the customer's 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 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 cash flow?

Yeah, 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 FY27. But, you know, looking at the wider funding of the business is something that we'll consider as part of that.

Thank you. Our next question today comes from Brian Bergen at TD Cowen. Please go ahead.

Hi, guys. Thanks for taking the questions. So maybe a bit of follow-up as it relates to the unplanned pressure here. So I understand the Mideast 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 clients ending 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 in not reinvesting it. But I think that is also part of the shift as they're looking to much more substantive AI-driven transformations. And that's very much part of the pivot that we're 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 now.

Okay. And my follow-ups as it relates to some of the actions by the foundational model providers. So, you know, obviously with news flow around OpenAI 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 avenues here, but what's your perspective there? Just considering your base of engineering talent 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, What are your thoughts on that?

Yeah, 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 code models that they're coming up with. We're 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'll 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.

All right, thank you. Thanks, Brian.

And our next question comes from Puneet Jain with J.P. Morgan. Please go ahead.

Hey, thanks for taking my question. I want to follow up on Brian'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 three years. So do you think you need to change anything in the planning process to get better handle of quarterly revenue or even the quarter as well as full year guidance?

Yeah, 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 one that we're paying a lot of attention to. We're very sensitive to it. If you look at our Q4 guide, we've got 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.

Got it, 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 about your employees, motivating them to embrace AI, to embrace like this new way of delivery, while also like the stock obviously has been down so much. And some of those employees might also be worried about their jobs given like the new flow around AI. So talk to us about like the change management within Endava, like how are you managing all those things? Thank you.

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 generative AI that was in play and how to create GPTs and how to drive usage across 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 chat GPT enterprise as our standard across the business. And, you know, over the following three to four months, we saw usage across our staff base move above 75% of people using it every day in their job, which was our objective out of 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 up with our own agentic solution ahead of the large vendors coming up with agentic models. And so we were using that to initially start shaping how DarvaFlow would work, DarvaFlow being our method around how you develop business solutions and ultimately software and agentic solutions in an agentic world where most of the work is done by agents rather than by people that shift from agile, if you like. So those pioneering groups actually defined DarvaFlow, created all the prompts, et cetera, that go into it, created the context warehousing, all of the pieces that go to make DarvaFlow 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 gateway we were building, but also the development of Darva Flow. And then over the last six months, we started to shift to spreading that step-by-step across the organization. I highlighted we've now got 12 clients using Darva Flow in anger, up from three last quarter. So that's the rollout speed. Within the organization, we've got over 1,000 engineers who are actually using and training on Darva Flow now, or over 10% of our direct staff. And that's in anticipation of the greater use of Darva 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.

Got it. Thank you.

Thank you. And our next question today comes from Nate Svensson with Deutsche Bank. Please go ahead.

hey guys um i wanted to ask about another one of the factors you called out is driving the the missing guy 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 um and then i guess more broadly you clearly talked a lot about this shift to outcome-based contracts um 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 the outcome-based models to try and realize benefits on pricing or efficiency or, you know, your traditional time and materials contracts?

Yeah, so we're not seeing that latter problem. It's just these are, by nature, very large, transformative projects engagements in the tens of millions type category and nailing down, you know, 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, you know, see a three or four 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 you know five six 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 you know, how to contract these deals that is becoming visible and is 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 are a little smaller. We are seeing them progressing. They're just taking longer than expected.

Okay, got it. Thank you. And then for a follow-up, I wanted to ask specifically on two of the verticals. So I guess first, what's happening in banking and capital markets? That vertical has been growing pretty nicely for you, and then growth – fell pretty dramatically in 3Q. I think you mentioned worse pipeline conversion, but more color would be helpful there. And then in healthcare specifically, I think on the call last quarter, you talked about a large healthcare client 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 healthcare side, yes, we expected one of our larger clients to slow, which they have continued to do. So they came in as expected. 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 client. And then we do have a ramp down from an existing client from Q2 through Q3, Q4. So, you know, 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.

anything on banking and capital markets?

Yeah, sorry. So in banking and capital markets, we were pretty sort of stable through Q1 and Q2. We did see a step down. This, as we went into Q3, I think a couple of million, one and a half million or so, partly one client coming off the 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're anticipating in the original guide that we set in February. And that sort of slowdown in banking capital markets is most pronounced in the US and the UK, although we are feeling it to a smaller extent in the other geographies, but it's more significantly in UK and North America.

Thank you. And our next question today comes from Jonathan Lee at Guggenheim Partners. Please go ahead.

Great. Thanks for taking my questions. 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 flipped contracts? And what's the coverage on the 4Q range today? And what gives you confidence in that sequential improvement into 4Q that's implied in the outlook?

So if we go back to Q3, we had a range of 185 to 182. We were saying the contractual coverage at the high end, I think it was about 90%, and it rose, I think, to about 92% for the low end of the guide. So the pipeline to convert in both high and low was about 19 and 16 million, and we converted about 13. So you've got a conversion which is below what we anticipated. The low end is about 80%. Now, for the high guide in Q4, we have contracted and committed of 95%. For the low end, the 181, we have 97%. So that leaves about 9 million at the high end to convert and 5 mil to convert at the low end. We have... three or four opportunities that are sort of sizable but we have taken a view that you know some of those are not going to convert as part of the high guide and then a severe downside that's you know one 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, you know, something like at the top end of the guide about, I think, three and a half percent. We do have, you know, some movement in terms of, you know, working days between the quarters that actually does help us somewhat. So the 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 business. our figures, it's the nature of the business model. The issue going back to sort of John's initial comments has been, you know, 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 that John was outlaying 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 flows. to capture more of that benefit and therefore sort of protect margins. I think the sort of key thing, I mean, these are, I'm 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, you know, 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 TNM.

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 of billability is running much lower as we're going through this pivot, as we're investing in skills retraining and so on. And actually, you know, we need to do that to prepare our workforce for the new that is coming through. It's not an optional extra. And, you know, 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

It's pretty stable when you look at it on an average workday measure. I think this is the sort of issue, the sort of transition, the usual metrics of billability and average rate per workday are sort of fraying a little bit as we go through this change.

Thanks for that.

Thank you. And our next question today comes from Matt Desort at William Blair. Please go ahead.

Hi, team. This is Matt on for Maggie Nolan. Thank you for taking our questions. 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?

Yeah, 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 two 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're classifying here.

Got it. Thank you. 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?

Yes. well the sort of managing sort of two dynamics which is we'll call it the traditional TNM business and the which we could call it you know 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 be 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, you know 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 And it's about the deployment of DARPA flow to capture that sort of benefit. So those are the two levers that you can, you know, you apply basically. It's managing that sort of dynamic. And I expect over the coming years, this sort of split between what is, you know, fixed price and what is, you know, T&M is going to start to, you know, shift. You know, we don't have any, you know, figures at the moment, but we definitely do know at the moment that, know our our tnm proportion of revenues is starting to come down so i think it's um you know last year it was about 77 on a four-year basis fy25 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 you know dava flow, but that is one way that you can protect, you know, margin going forward about growing the new, more profitable work.

Thanks for the call.

Thank you. And our next question today comes from Ahani Kenamuri with HSBC. Please go ahead.

Hello, thanks for taking my question. I just want to ask on the update regarding your go-to market with OpenAI. You have that partnership. Do you have any update on how it's going? Thank you.

Yeah, we continue to have a really strong relationship with OpenAI. It's global in nature, driven out of the US. conversations that we had with the new deploy co a part of that relationship and you know through that putting together thoughts and plans on how we're going to work together with the new deploy co 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 are in the large complex space.

Perfect. Thank you. Thank you. And that concludes our question and answer session. I'd like to turn the conference back over to John Cotterill for any closing remarks.

Yeah, 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, and we thank you all for attending today's presentation. You may now disconnect your lines and have a wonderful day.