Good morning. My name is Puneet Jain, and I'm from JP Morgan Payment Processing and IT Services team. I'm glad to have here with us Endava CEO John and CFO Mark. Welcome, both of you, and we also have Laurence sitting here in the audience. So we covered Endava for about a year. It's been great covering the story, knowing more about you. You reported your results yesterday, third.
Tuesday.
First quarter results. Tuesday.
Tuesday.
Time just flies.
It does fly.
So you reported your results on Tuesday, reported revenue at the top end of your guidance in the quarter, and maintained your annual guidance. So can you recap your results and the trends that you are seeing?
Do you want to? Yeah. So as you said, we were top end of the guide in terms of revenue. Profitability was stronger. So the EPS was ahead of the initial guide. So our gross margin was better than anticipated, largely because of utilization being higher than anticipated. It was a good quarter. We've held the full year guide, so the top end of GBP 810-800. And the EPS remains in place despite the stronger start to the year. We've got work to do through the sort of Galaxy integration. We completed that acquisition in April. So there's a lot of activity between now and the end of March. So that will be a bit of a headwind in terms of the costs, certainly at the adjusted PBT level. But we anticipate we will get into sequential growth to achieve that top end of the guide.
So it's a good start to the year.
So the guidance implies, like you mentioned, Mark, sequential growth in the second half of this fiscal year. What drives the confidence that it's more real this time, that it's doable compared to in the prior years, last couple of years, when things have been just slow and any signs of optimism proved to be too optimistic?
Yeah. I mean, the pipeline remains strong. The key issue is conversion of it. So in terms of the velocity at which opportunities convert into a sort of revenue, it's still an elongated sort of stage. But we go through our forecasting process. We look at things on a monthly basis. So we're applying a degree of caution around the conversion rates that we're seeing. So we are confident in the guide in terms of that sequential step up from Q2 to Q3 to Q4. It's modest. I think we're looking at sort of 3% consecutive growth from Q2 to Q3. And if you dedupe FX for the implied guide for Q2, we're at 1.5%. So it's a steady sort of acceleration from what we hope is a low point in terms of Q1. I think we were outlining the core modernization prop yesterday.
We are getting a lot of interest in that proposition. We anticipate we will get pickup with regard to that offering.
Many of your clients will potentially decide their budgets for next calendar year in January, February. Any early read into what the magnitude or priorities your clients might have as they decide their next year budgets?
It's always a difficult part of the year, actually, and John's closer to it than I am, but you see elements of either people trying to spend their budgets as they get towards December. Budgets firm up a little bit later, actually, so we do get a sense. We're not getting any indications that budget levels are going to be reduced or increased, so we're not getting any sort of market information from that perspective that things will improve from that perspective into the second half. John's closer to it than I am.
Yeah. I think, I mean, one of the not every part of the world does their budgets in January. So for instance, in Australia, they mainly run July to June. And it's been interesting there to see that as we've got into their budget year, that actually spend is starting to come through. And the programs they're pushing ahead with, where we've also got other customers where their budgets are being established in their new financial year is kicking off in September, October, November. Likewise, we're also seeing work coming through with those budgets. Now, the vast majority is in January. So those are small indicators.
I think the other aspect, which is what we were talking a little bit about yesterday, was that whilst budgets are likely to stay reasonably stable by the indications that we all have, that actually there's a bit more of a shift going on within that to try and push a little bit more into the discretionary space, particularly for us, the AI activities. Some of the proof concepts that we've been doing seem to be shaping up strongly to move into production budgets next year, and then the other aspect is the core modernization aspect, where that has traditionally been a keep the lights on part of the budget, and actually, our proposition is quite strongly around how you change that from being run the business to change the business by bringing productivity and the new approaches that we've been talking about to core modernization to that.
And so that's getting traction in terms of those budget discussions with clients as well. So you put those together, and that's what's underpinning the guide that we put together.
This change in client behavior, would you attribute it to macro factors like the interest rates are coming down, like the election uncertainty, whether it's in the U.K., U.S. is behind us, U.S., although it's just happened literally last week? Or is it because of AI has been around, or Gen AI has been around for a couple of years, like vendors like yourself? Yesterday, you talked about Dava X and with tools and accelerators that can help clients embrace AI better, faster, cheaper. What's driving this changing clients' behavior now?
It is a combination of two things. One is the, if you like, the position that clients have been in for the last couple of years or so has been a little bit constrained around the way they put their business cases together, if I can describe it that way. CFOs raised the bar after that post-COVID rush. They went, no, we can't just spend money on anything that looks like technology. We want better business cases. Interest rates have gone up. So the standard, the returns that they were looking for were pushed up. And alongside that, the technology uncertainty that came with the AI wave, making it harder for CIOs, CTOs to actually demonstrate the certainty of outcome that's coming from investment, has caused that slowdown in discretionary spend. They are starting to move through that because the businesses are recognizing that they need change.
They need the new products and capabilities to be pulled into the business. We, as Endava, but I think more widely as an industry as well, are starting to solve some of those engineering problems around AI, around core modernization, and so on, that actually are starting to improve that certainty of outcome. And so you put those together, and there's that shift starting to happen. It's early days, and it will take a while for these programs, which I believe are going to tend to be larger because of going into the core in order to drive change, AI-driven change into the business. But they will take longer to ramp up as they get sign-off. And so we see a slower, steadier period during the rest of this financial year, which is what you've captured in the guide.
Yeah. No, that's great. So let's talk about core modernization. That was the focus of yesterday's presentations as well. How large core modernization opportunity can be? Totally, I can imagine how many of enterprise customers have legacy data that you cannot use to train AI models. The technology is still legacy at many places.
Yeah.
Systems in silos, disparate systems that do not talk to each other. So how large this opportunity can be overall for you? And are clients really ready to overhaul everything that they have not done in the last 20, 30 years at all?
Why is core modernization necessary? AI needs to get at the data and the processes that sit within an organization in order to be fully effective. At the simplest level, if someone phones a call center with a problem with their bill, and you're trying to get an AI to solve that customer's problem, it has to be able to get how the bill got created, what's in it. And then having solved the problem, it has to be able to change the bill, reissue it, et cetera. And that requires systems that have a digital core where it's truly opened up to the AI to enable that to happen. It's very difficult in most cases to do it into a legacy system with old code bases and all of that. That is increasing the pressure on organizations to address the problem in the core.
That is different to the way digital transformation has largely operated over the last 25 years or so. The 25 years that's seen the establishment and building of Endava, most of what we did was built around the outside of the core. So you were creating products and capabilities, digital products and capabilities that sat outside of the core, perhaps got into it a little bit in terms of the data and the access, but wasn't really sorting out the underlying brittleness and structure that you had in the core system. So that's a big shift. That's what we're calling the digital shift. So in order to drive digital product into the next age, you've actually got to sort the core problem as well as create the new digital products, and AI enabled in particular.
Now, the core problem is actually much bigger than the market that we've been addressing in digital transformation for the last 25 years. We heard Jim Grech from TD Bank yesterday at our conference saying that they spend 80% of their budget on just keeping the legacy systems operating. So as we can start to tap into some of that budget to drive change through accelerators and so on, so actually being able to drive change in the core much more productively, much more cost-effectively, much faster, then you start to shift that budget from being a sort of frozen keep the lights on budget to actually being moved into the digital space. And that's the underlying thesis around the shift that's going on. And that is where we're getting traction with clients, showing them how our techniques, our accelerators, and so on can start to address the problem.
Now, the final part of your comment was about the scale of it and are they ready to change it all? That is not how it's going to happen. It will happen by being able to break pieces off that are related to the new digital products that you're trying to create and actually transform the core in that space and do it piecemeal. Now, part of the techniques and the accelerators that we bring is the enabling of being able to break things off. Because in being able to track what's going on in the core, you can actually understand what you're doing to it when you take something out and transform it.
That's been part of the historic problem with legacy systems, is that actually, because they don't have a very deep understanding of how those systems work, when they try and take a piece of it, they break the whole thing. Fixing that actually enables you to start to make progress without having to throw billions at trying to transform the whole thing at once.
AI can help them do that.
Absolutely. AI helps by getting into the code along with some of the proprietary accelerators we've got to actually understand what's going on, and that when you compartmentalize something to transform it, make sure that you recreate the links that you need to keep it plugged into the rest of the system.
And I'd imagine this not being just like a technology problem for clients, but also like the cultural and organizational problem for them to change everything.
Correct.
Are clients ready to take that leap? It seems like they are now.
Yeah. So we are underway on the early projects, on the early stage of the projects with a number of clients. Some of them have ramped. Some of them are in the 100 to 200 people actually progressing the transformation, of course. But most of them are at the "can you show me how your accelerators help me understand my systems?" And "let's do that first." And as my confidence grows, I'll start to move into the actual transformation programs themselves. And that was the reason for this "will take a while to ramp" comment that I was making earlier.
Yeah. Makes sense. And what's Endava's right to win in this core modernization opportunity? Maybe just recap some of the tools, some of the accelerators you talked about yesterday.
Yeah. So we talked a lot about the accelerators because we were trying to bring to life the technology itself and how impactful it is. But I would put it in the framework that at the end of the day, Endava is an ideation to production business. We have that full suite of capabilities in terms of architects who can actually interpret things, make plans, structure programs for success, as well as all the developers, testers, and so on. What the AI accelerators do is to make us more productive and speed up that process on the one hand. And we demoed some of that yesterday. And on the other hand, be able to do the analytics on the core and what the clients actually got today so that you can break things off, create proper plans for the modernization of that core.
And so the big ones that we talked about were what we call MAPS and DASH. MAPS is a proprietary patented capability where we can read the code. It came with the Galaxy deal. And that has been 20 years plus in the making. And when we engage with a new client, we normally find they have a few more variants of flavors of COBOL or flavors of other code in there. And it takes us two to three weeks to write another parser that can read that specific flavor of code and then pull it into the MAPS analysis. What that enables us to do is to track what's happening in the code and spot all of those strange links to other parts of the system and all the rest of it. We also have an accelerator that we call Chronos.
Now, Chronos looks at the data repository and the interaction that developers and so on are doing with the code through the repository. And so you can pick up patterns of behavior from that. You can see parts of the code that no one ever touches. You can see parts of the code that are being interacted with almost hourly and many other patterns. And that helps you understand where the issues are within the code. And then on the more modern code, if I can describe it that way, that sits in the core, AI itself can actually read some of that code and start to pull out some insights. And then over the top, we have an agentic AI solution.
It's based on our Morpheus solution that we announced about six months ago, which we call Compass, which actually pulls all of those sources of information together to enable you to map out what's actually happening in the code. And it creates that map from the perspective of all the different players. So you can have the requirements, the architecture, the developer perspective, the quality and testing dimensions, and actually use that to equip the different players who are going to modernize the code with the understanding from their perspective of what's actually going on within the core. And that's what creates the power. That's what enables you to suddenly move from a place where you have this difficult to understand legacy code to actually now we've created it in a structured fashion where the technicians and the players in the modernization can actually understand what's going on.
That takes care of hallucinations as well because.
The agentic dimension really takes care of hallucinations because essentially you've got the agentic AI is about different agents interacting with each other. So you can set an agent up who is doing development, another one who's doing testing, another one that's only requirements perhaps a regulator agent. And as they interact, they will call each other out on that looks like a hallucination to me, and resolve that. And so you end up with a much higher quality of AI output from it.
Yeah. I like to see various AI agents arguing with each other.
It's interesting because it's the same way that we've run our business for the last 25 years with people is multidisciplinary teams actually operating together that enable you to actually get to grips with a new product and get it from ideated and get it into production much faster because of that interaction between the different players around the table. And we've essentially taken that approach and applied it to AI, and you get the same benefit. With humans in the loop, by the way, it's not just about the AI going off and doing its thing. So you've still got the human agents, if you like, that are also part of that process.
Yeah. So I imagine if clients implement these AI tools to modernize core, it will save them significantly. It will be significantly cheaper, faster for them to modernize those core systems. And that is one of the top questions we get from investors who worry about the impact of AI on IT services model, that it is going to reduce opportunity for IT services companies. It will make them less relevant because there's going to be more AI tools, less people, right? So how would you respond to that? What would clients do with all that savings?
So what the tooling actually does is enable you to move, as I mentioned earlier, from keep the lights on to transform and create new products and capabilities. So that shift means that organizations that are out there who largely do keep the lights on work are either going to need to shift what they're doing or they're going to be hurt by it, which I think is your thesis, but that there's going to be less work in just keeping the lights on. But as we shift it over to more discretionary spend and make it available to actually transform the organization, that will be a tailwind for organizations like Endava that have really operated in that space. So that's our underlying digital shift and why we're setting ourselves up to drive that shift and that change to open up budgets that come our way.
I believe alongside that, that the backlog of work that clients would like to get to if they could just get their budget working more effectively for them is actually huge. So you could argue that in 10 years' time when they've got through that backlog of transforming their legacy systems, then it comes down. But that has always been the way in technology. And there's always on that sort of horizon been new technologies that have come along that drive a next wave of change. But I don't know what that is in 10 years' time.
And there'll be, like you said, something else in 10 years that will catch their attention and will drive spending. No, that's fair. You talked about Galaxy, like in the tools, some of the accelerators you got through Galaxy. You also got significant India delivery capabilities through that deal. So talk to us about the integration plan. It seems like you are already at a point that you can offer their India delivery to Heritage and our clients. Is that right? And what's the feedback been from those clients?
Yeah. So the India integration into our cross-selling, and let me describe it that way, has been very positive. In fact, it's uncovered something for us that we hadn't really picked up on, which is that for some clients, because India is such a core part of their technology delivery strategy, when we weren't there, they didn't consider us for some of the pieces of work. Not because they were going to do it all from India, but because they saw a capability in India as being part of the solution. And so the first pieces of work that we have won through having that capability have not been, we're going to do all of something for you from India, but they have been great. Tick the box, you're India, so we're going to sign you up.
But then actually 70% of the teams that we're deploying have been near shore, but that last 30% being available to clients has enabled us to win the whole thing as opposed to being excluded from that piece of work. So that has been the big opportunity that's opened up by having that footprint in India.
At this time, are there any questions from the audience? Just wait for Mike.
Hi, John. Great to catch up again, and again, we've been a big fan of the way you've handled culture and the business. I think one thing we wanted to understand was now that US is becoming a much larger portion of your business with Galaxy also coming in and obviously in general the trend, how are you thinking about getting ready to scale up in terms of your GTM approach and the team? I think some perspective on that would be very, very helpful.
Scale up within the U.S., did you say? Sorry?
Sorry?
Scale up where?
In U.S., yes. What would be your approach to scale up in U.S.? I think from a GTM perspective, from a team perspective, I think that would be very helpful.
So I mean, we've talked a lot about the horizontals and the technical capabilities and how that's adding value to our proposition to clients. But it's worth taking a step back and remembering that our primary go-to-market route is through our industries. And so global industries that are focused on specific client segments, understanding the industry challenges and how technology can have an impact on it, and then creating conversations with clients around those industry areas. So some of those industries are being led out of Europe. Some of them are much more strongly located in the U.S. The healthcare one that's come with Galaxy, in particular, the healthcare market here is so much stronger than it is in the rest of the world. We will be leading that out of the U.S. Some of the Galaxy teams are in a strong position to take that leadership.
But also we have the Endavans that we have in the healthcare space are also based actually in New York, New Jersey. So integrating that together will create a strong global leadership team out of the U.S. Automotive is another area, and that's sort of balanced between continental Europe, where you've got the European auto manufacturers, and then in the U.S. auto manufacturing space. And so the leadership teams there are across the U.S. and Europe. So continuing to attract top-level talent into the teams that we have in the U.S. is a key part of the strategy going forward. We've been doing that strongly over the last couple of years. And so the U.S. footprint is actually a lot stronger than it was three, four years ago. And that's driving alongside the inorganic a strong performance in the North American geographies.
Hey there. Thank you guys so much for all the time this week. If we could double-click quickly on the payments portion, you guys are obviously renowned sort of payments experts in the tech services space. So it gets a lot of maybe pressure or criticism because the numbers haven't been as good. But I think that's partially a factor of your own success over the last many years where you had these couple of accounts where you're hugely penetrated and getting so much revenue from just a couple of accounts. So could you share if you look through those biggest accounts, what do you think is going on in payments? I'm particularly thinking about payments companies. Obviously, you have the payments as a horizontal capability as well. But yeah, within payments, kind of ex these big companies.
So there's probably two trends that I'd really like to call out in payments. One is the core modernization dimension is also hitting the payment space. Now, some of the clients addressed that in some parts of their business over the last 10 years or so, and we did a lot of work around that, e-commerce platforms and so on. But there's still a lot of underlying switches and payment processes that are sitting on old mainframe systems. And actually, that is an issue for payments companies, right? The stickiness that you get and stickiness protects your margin comes from being able to add value-add services to the merchants that you're providing service to. And the added value services that people are hunting for are actually quite difficult to just plug in on top of some of the legacy systems.
And so that's driving a need to get into the core modernization space in the payments world as well. And some of the activity, the pickup, the stabilization you're seeing in payments is coming from some of that activity starting to ramp up again as we're moving through this year. So on payments, you've got that sort of global picture going on with margin pressure alongside it. So it's quite a difficult invest when you're under pressure on margins. And so some clients have been working out how they bite the bullet and get those programs underway. And that's by no means universal. The second trend that I'd just like to pull out on payments is that we portray payments as a vertical in terms of the payments processes because we did a lot of work with them. But actually, what we're seeing is payments going horizontally.
And so that doesn't get reported, right? But actually, we're doing more work for payments in the banking arena. There's quite a few of the banks who are going, "Do you know what? We should be back in processing ourselves." And actually helping them to build capabilities and so on is also driving revenue in our banking and capital markets, mainly banking arena. But then we're also seeing it getting pulled into automotive, into retail, orchestration layers, and so on that we're putting in place in the retail space as well. So it's probably not shrinking as much as you think it is because you're just looking at the vertical of the payment processes and the way we report our numbers. And it's still an underlying strength that's driving some growth across the business.
All right. I think we are out of time.
Oh, we are.
Great. Thank you so much. It was very helpful.
Thank you, and thank you all for coming and listening in.