All righty. Good afternoon. Thanks, everyone, for joining today. My name is Tyler Dupont. I'm on the Payments and IT Services team here at Bank of America, and I am excited to have Endava CEO John Cotterell and CFO Mark Thurston joining me for what I can only imagine will be a very productive and exciting discussion. I wanted to jump right in, given we're limited on time. John, you've been with Endava since the beginning, so you'd be the perfect person to give us a quick intro. For those less familiar with the story, what are the types of service offerings that Endava specializes in? Who do you serve on a day-to-day basis? How do you position yourself in the market?
As a second question to Mark, you know, you've been with the team for around 10 years now, pretty almost like a month ago, right? You have a take?
Oh, boy.
Maybe just your perspective on how Endava's evolved during that time as well.
Sure. So, yeah, I was the founder of Endava back in February 2000. So we've just hit our 25th birthday.
Congratulations.
I've seen quite a few changes go across the world, which, you know, if you look back to when I founded the business, the dot-com boom was in full flight, all driven by the internet and the revolution that was coming through from that. That then hit a pause as you went into the end of 2001, 2002, 2003, during which time, you know, we in Endava and others in the industry were working on, you know, what is the engineering around the internet and how does that get implemented into the enterprise. We came up with this approach, which was around this, you do not go into the core, you leave the legacy systems alone, and you build capability around the outside and API in what you need and so on.
and, you know, as that came through, we went into the digital transformation wave, which Endava, you know, as we grew, became a leading player in, around our whole approach, which was around ideation to production, multidisciplinary teams, how you integrated creatives who can come up with new product ideas, with engineers who can make sure those product ideas are viable in the real world, and then are gonna scale, as you put them into the market. and so, you know, that drove that digital transformation wave. It ran for about 20 years. We grew 20-30% a year or, mostly organically through all of that period. You had little kickers that came along the way, things like mobile, things like cloud, but it was all following the same, you know, basic shape.
Then, you know, if you look the last couple of years, we've had another major year, technology shift coming through in the form of AI, and that creating a whole shift, in what is needed, and what the opportunities are for businesses. And, you know, I think we're going through a similar lull right now as we went through in, in 2001 through 2002, 2003, around getting the engineering, getting the application, getting the, the use cases and so on, out of AI applied into the enterprise world. So that's, that's very much where Endava is focused. We're very much at the, change the business rather than keep the lights on and run the business end of the spectrum, a bit more exposure to discretionary spend.
Interestingly, the 20 years of the digital transformation wave, even when discretionary spend was pulled back, we still carried on with the sort of 20% plus organic growth. It did not impact us hard. This time it has impacted us. I think that is just because of the more fundamental nature of the shift that is going on with AI coming through.
Interesting. That's, that's.
Yeah. I joined John and the team, pre-IPO, to get us ready. It was basically about putting in robust forecasting processes, which already existed actually, but, you know, being able to report the numbers to SEC sort of standards. It's been a fantastic journey. Grew very, very quickly, executed, faultlessly, I'd say, you know, beat and raise cadence. We've built a very solid platform over that period of time, geographically, global delivery, you know, capability. A little bit more choppier more recently, which I know that we'll sort of touch on, but it's been, it's been a great experience, but we're into this, this difficult choppy period at the moment.
Yeah. I'm glad you brought that up because I think it'd be remiss if I don't lead with that. Macro environment that we're in right now is, I think volatile is a polite word for it, you know, and scratching it up meaningfully, the historical context is helpful as well. Maybe if you could just sort of double click on that, sort of where are we now? How is that compared to prior cycles? What are the types of projects that enterprise decision makers are partnering with Endava on? How does that change in this macro?
I think the thing that I would highlight that is going through the biggest change is getting the engineering around the implementation of AI into an enterprise environment, right? All sorts of things like, you know, these strong brands are not gonna put solutions in place that are gonna hallucinate in front of their customers. So how do you solve for that? Largely we're there, and agentic solutions are certainly gonna help make that even better. The resilience and scalability that comes, you know, they don't want solutions that are gonna work at a proof of concept level, but then are not gonna work when exposed to their customer base.
You know, there's a lot of the industries that we work with, there's been regulators to manage and go through the process of regulatory confidence around the use of AI in the environments that they regulate. Those are moving forward. There's still more work to be done, but they're no longer blockers to actually being able to progress with programs. You know, the two big ones, one has been business cases. If you go back, you know, a year or 18 months, a lot of the business cases weren't standing up. You could demonstrate that AI does the job. It does a good job, subject to the engineering items being right that I just took you through. The business case didn't stand up because the processing costs of driving the AI were so high.
Now you can design for that, so you can start to abstract out elements of activity that do not need to be processed in a GPU type environment and bring the cost down. It all takes more work, more design. That curve is now starting to come, that price curve coming down is now coming down to a level where actually those business cases are getting more robust and clients are getting more confidence that the curve carries on down and therefore they can progress with their program. We are starting to see that coming through. The last big one is the state of enterprise systems. A lot of them have legacy systems, and those legacy systems make it really hard for AI to be, you know, 100% effective.
If someone phones up and has a problem with their bill and you actually want an AI to be able to handle the call and sort it, it has to know how the bill got created, what its options are around, you know, I'll use the word negotiating with the client. Then it has to be able to action the result of that back into the systems to make a change to the bill, to do a credit or whatever. That's actually incredibly difficult to perform with the legacy systems that exist in a lot of client organizations. The good news is that leaving legacy systems alone, which was part of that digital transformation wave I was talking about because of the difficulty of transforming them, that can actually be helped by the use of AI.
We have established tools and then layered AI over the top of them that help you actually understand what's going on in the client's core straight legacy system. Then, knowing the start point, you can actually map out a transformation program that gives much greater assurance, much faster execution than they've previously been able to do. We are seeing those programs kicking off, and actually some of them are at large scale with clients now. We are working on a lot of transformation deals with clients that are around that end-to-end, you know, AI benefit into the business through to the core modernization process that sits underneath it.
Yeah, that's interesting and actually segues nicely to the larger deals that you're signing. That's been a topic that's come up recently, and I feel like there's been this, and I think it was mentioned on the call, some not necessarily pausing, but delayed spending. Particularly in the back half of calendar 2025. Are there any updates there you can provide? What are you seeing in the market converting bookings to revenue? The large deals seem encouraging on a go forward basis, but sitting where we are today, how should we be thinking about that?
The large deals, they're increasing in number and they're increasing in average size, as a result of the work we are doing with clients. I would like, you know, I'd like to add that these are deals that result out of the ideation phases that we are doing with clients, which are becoming extended in these cases. Nonetheless, these are periods of time where clients are paying us to do the consulting, the engineering, the design work, and so on on these solutions. It's not just a sales cycle. It is the conclusion of work that they're actually paying us to do. Those are increasing in size, and in number.
The challenge that we had, you know, over the last 12 months, which was prove that the engineering works so that we can press the button on these deals, is moving to, you know, clients raising budget to actually do those transformation programs. In the latter stages, they are finding with AI being so core to it that actually, you know, they're hitting unexpected issues like, you know, legal departments sticking their hand up and going, hang on, have we, have we made sure we're compliant with EU regulations or all sorts of things, across the organization? You know, our clients are essentially going down the learning curve of how to buy in this space.
and then having gone down that learning curve, we expect to see a more regular cadence come through as everyone knows how to get these things from idea into, let's start building this.
What are the, the duration of that, like ideation phase that we're in right now? I feel like historically, you know, it's been fairly quick to go from ideation to production. Now it feels like that's, you know, the project's not canceled or anything, but you're sort of in that stage for longer. Just sort of walk us through that.
I mean, during the digital transformation wave, we saw three to six months as being an average ideation production. The significance being during ideation, you are running, I don't know, a team of seven or eight maybe. When you go into production, that could 10X or even more. You see the big step up in revenue when you move to the production phase. This phase around the AI shift, we've seen that being over a year and some of them have actually hit two years where we're hitting that paid, design, ideation phase still going on. Obviously that's our number one focus as a business at the moment is to get these, a number of these deals over the line 'cause that's what's gonna enable us to turn the nose up on the revenue.
Great. Yeah. I'm glad again we brought up the deals because I, it might be helpful if you could help remind us this sort of the relative strength you're seeing from a deal size perspective of the larger deals, seeing more strength of the smaller deals. Just from the larger deals you have signed, I believe there were five that were signed in the quarter. How should we be thinking about the ramp timing of revenue as we look into the back half?
I mean, it ties back to sort of our guide survey pullback quite so strongly in Q4. We had an issue actually predicting when these deals were gonna sign. John sort of took you through some of the sort of reasons there. I think given we don't have the feel for the cadence of the progress, I think it will come over time. We're basically going to sort of take an approach going forward, looking at guiding, which we'll do in September, that we will look at the sort of run rate of the business. This is the non-big deal step change type of increments that we've found difficult to sort of date when they will happen. The approach will be that we will look at the run rate of the business as we exit Q4.
We'll make guidance around, you know, how we, when it's gonna be flat, it's gonna inflect slightly upward or inflect slightly downward, et cetera. We'll have to be careful about, you know, how we set that expectation. In terms of these larger deals, I think we will just include them in the guidance as we land them because they do produce this material step up. There'll be a, let's call it a bedrock of the business, an underlying sort of run rate. The big inflection is kind of come from these big deals basically. Like John was saying, it's also the cadence at which some of these big deals accelerate. Some of them will step change almost immediately. Others, it may be a build in terms of the revenue sort of profile as what that duration is.
Sure. Because of this uncertainty, it's a bit more prudent to leave those deals on the side for now. And then when they hit, they hit.
Yes.
Okay. That makes sense.
I think when we see that regular cadence of clients being able to push these through their process with a much more, higher level of certainty around that cadence, then we can start building it in. That is probably at least nine months away, if not longer.
Yeah. Sure. Sure. It sounds like based on this conversation and earlier today that not all of your end markets have been experiencing the macro environment evenly, you know, at a high level. It might be helpful if you can break out sort of what you're seeing in the demand environment across your universe of clients. I would assume, you know, the, I would just say maybe the mobile business is not quite as robust as like your insurance business or, or just any color commentary there.
The area where we've had real strength over the last 12 months has been the banking and capital markets arena. That's been followed by insurance, which has been steady, sort of low double-digit, high single-digit like growth over that period year on year. And, you know, different factors driving that. If you look at the BCM space, it has been some of the core modernization activities that I've been talking about, and those programs are actually starting and ramping. That's been a strong factor in the growth there. There's actually been a second factor, which is our payments capability. We have payments as a vertical where we report on the activity we have with the payment processes.
If we do payments work in another vertical, like retail or in this case, banking and capital markets, we report that within the banking and capital market vertical. We are actually seeing the payments capability being quite a strong tailwind in the banking and capital markets space. Essentially, banks looking at merchants and so on as being their customers and how can they use payment capability to make that relationship stickier, because of the information it gathers, either as a value add layer over what the payment processes do, which we are helping them build, or some of them are going deeper into, you know, the whole process, which results in large programs. That, you know, whilst payments as a vertical has had a lot of headwinds, actually, if you look at it as a vertical and as a horizontal, it has been much more stable, holistically.
The insurance space has been a lot about, data and AI driven. Actually, how do you help the underwriters? A lot of it's in the broking space, and that's where we've seen a lot of that momentum coming from. Essentially, not being constrained by a legacy system issue, you've been able to get on with delivering AI benefits more quickly.
What's the sustainability like of that, you know, revenue growth that you're seeing in those verticals? They're seeing pretty meaningful outperformance. It sounds like it's, you know, the core modernization work, it's the AI work, which tends to have a long run rate. Should we just assume that those are the growth rates for the foreseeable future or just what visibility you have in those verticals that you are allowed to talk about, if at all?
I think we will see going forward. I don't really wanna comment on FY 2026.
Of course.
You know, we're going through a budget process, et cetera. I think those sort of dynamics that we, you know, John's been through, you know, we see banking and capital markets remaining pretty strong. Quite a lot of the, you know, the pipeline, the larger deals tend to be in that sort of space. Do we see some payments, you know, payers, payers in that space? I think insurance will also continue to perform, you know, reasonably well. I think TMT for us is struggles a little bit. It's muted sort of performance that we expect. I think over time, sectors like mobility to come back. There's a little bit of hesitation around automotive at the moment, which you could understand given the talk of sort of tariffs at the moment, but there is a strong sort of disruptive wave going through that space.
We are getting quite a lot of traction in terms of big deals that we see in the pipeline.
Great. That's helpful. You mentioned payments a few times, but the payments vertical was facing some one-off headwinds related to a large client ramp down. Would you say that the demand trends you're seeing across that vertical outside of that one client are relatively stable, or is there any other underlying dynamics as you just try to peel away that one buying issue?
I mean, John can jump in here. I mean, we've seen a big reduction in payments from the peaks, we're like 50% to where we are now. It's dominated by two or three large clients who've pulled back on spend and not in all cases. Our biggest payments client has reduced spend with this, which is around a particular sort of product, if I can put it that way. On the other hand, our second largest, you know, payments client has actually sort of grown. I think generally we're seeing now, I think we're around the sort of bottom with payments. Do I see it improving in FY 2026? Probably, probably not, subject to, you know, these large deals basically that we've been talking about.
That's helpful. Switching gears just a little bit here. You know, the Galaxy acquisition has meant healthcare has become an increasingly large portion of your business. I'll touch on Galaxy itself in a few minutes, but maybe it'd be helpful to hear from a vertical perspective of any trends you're seeing within the healthcare space. You know, there's been a lot of volatility in the market, particularly on the payer and provider side. Are there any dynamics worth calling out in healthcare?
Healthcare is one of the spaces where we're getting real traction around the core modernization capability. Essentially, a lot of those underlying tools that I was talking about that enable you to read the code and see what it does came with the Galaxy acquisition, and so they have had those in place with a lot of their healthcare clients pre-deal. What getting together has enabled us to do is for Endava to add that sort of AI overlay. That means that you can do a lot more with the information that we're gleaning through those tools. Then secondly, client confidence around us taking on larger programs as a bigger business is higher. We're actually seeing some really good opportunities come through and progressing in the healthcare space.
Alongside the BCM space, that's where we're also seeing a lot of this core modernization work actually happening. Two very strong industries for us to be able to create those case studies and credentials to share with clients alongside the tools that we have.
Great. Your largest client as well is in the healthcare space as of now, right? That is where, where do they sit within the ecosystem and how has that relationship evolved over the past year now as an Endava client?
So, they sit in the PBM space mainly.
Okay.
They've also got some of the insurance, I think you call that payer here, capability. The relationship's been good. The business has, you know, largely grown if you look at it year on year, and, you know, there's good core modernization work going on there, and a good stream of opportunities that we're working through with them. It's generally in a good place.
Great.
no issues.
Yeah. I'd like to see that. And I said I would get back to Galaxy. So I'll mention it now. You know, from my understanding, the business has been officially integrated to Endava as of this past quarter. How has that integration progressed versus expectations?
I think it's gone smoothly. I mean, we took a bit of a risk in that we cut over onto our financial systems at the core, always a bit of a risk, but no issues. I think the team have embraced the change 'cause we, you know, we have a cadence that we have to, in terms of reporting, that they have to adhere to, forecasting that's a higher level of granularity than they've been used to. And the Galaxy team have, you know, responded to that very well. I think they're settling in now as we go towards the end of June. I think there's a further integration underneath the covers rather than a systems perspective that we'll see over the course of the next 12 months through FY 2026.
A lot of cross, you know, cross-team sort of working. We, we do it a little bit at the edges. It needs to be more integrated. But it's, it's gone very well actually. I think, I mean, Mark's picking up mainly on the backend there.
Yeah.
If you look at the go-to-market, I've already highlighted a few, you know, areas where we're seeing benefit in the banking and capital market space where together we've been winning business, likewise expanding in the healthcare space. The other area where we've seen opportunity emerge is around India. They had an India footprint. We've had some of our, you know, traditional Endava clients come and say, can you do near shore for us in India? 'Cause we have delivery operations there. That's led to some growth. I mean, not huge, about 200 people, but nonetheless, that's been a benefit that's come out of that.
I'm glad you brought that up 'cause the acquisition gave Endava a unique exposure to APAC that it didn't have prior. You know, how have clients really responded to this newer delivery capability set? Are you seeing clients source their work from just a wider range of geographies now, or, you know, is the delivery model any different or?
I mean, we've had a near shore delivery model. It gives us a far shore capability. We're tending to use that more in the core modernization scenario. If you think about near shore, it was very strong for new product ideation and creating teams that are in similar timezone for client for creating new products. That absolutely has a role going forward. If you look at the core modernization, you're essentially using tools to understand what the client's existing system does and then using the outputs of that to be able to create the future picture of that system and re-engineer it. You don't need to be near shore to an SME on the client side in the same way, and so we can deliver that from a location like India, which is what Galaxy had been doing.
It's not competing with the India pure plays because it's very technology enhanced in terms of what we're doing, in terms of using the accelerators that we have. So that's very much the positioning of the role that India plays. For places like Australia, Singapore, and so on, we're tending to use Malaysia and Vietnam, which are other locations in the region as that sort of nearshore service provider.
Great. I have a bunch more questions, but given we're limited on time, I want to just quickly poll, see if there's any questions in the audience that are worth just taking a second and seeing if there are any. I can keep going. Okay. I'll keep going. We, we've talked about AI quite a bit over the past 28 minutes now effectively. How are you, but that's from more of a go-to-market and a sales perspective, how is Endava using AI internally in the business? You know, are there a certain level of productivity gains that can be capitalized on by using AI? How many of your employees are AI enabled and you've,
Let me pick up on the general picture. We have set ourselves a challenge of being what we call AI native, meaning that everyone uses AI in their job every day. We have given everyone, we did a global enterprise agreement with OpenAI. We are a strong partner with OpenAI. That has enabled us to give everyone access to ChatGPT. Some people also have access to Copilot, depending on the nature of the actual work that they are doing. A big focus is on getting that into the way people work and maximizing the productivity benefits of that in development work, testing work, and so on. We are also doing it within the sort of GNA world.
Yep. Yep. Yep. You know, we use it basically for examples in finance where we go to read the contracts basically and get to a quicker, you know, accounting judgment, how we should, you know, re-rebrack rather than having a team doing it. I think that's only just the start of it basically. Interesting. Interesting. That, that's good to hear. I guess one concern that we get from investors on our side is that, you know, the increasing use of AI internally generates a lot of productivity gains, but it could also lead to a form of cannibalization as your TNM model gets, you know, the dynamic that is involved there. You know, have you seen any of that? Are you moving more towards an outcome-based model to adjust for that?
Are there any gains that you're sharing with the client? Just trying to figure out the mix dynamic.
I mean, we are expecting the, and seeing already big productivity gains, but expecting to see even bigger productivity gains. You know, the thing that I would say is productivity gains have been a feature of our industry since the year dot. Even if you look over the last 20 years through that digital transformation wave, there were huge productivity gains that came through the use of open source, for instance. You know, a sort of 2X, 3X type gain in productivity 'cause you're essentially reusing code and not writing it from scratch every time. There will be similar productivity gains that you can get through the use of AI. The history of our industry is that those productivity gains get converted into backlog because it gets cheaper for clients to write new systems.
As it gets cheaper, the business cases stand up better and clients want more systems. It creates more work. The productivity gain that we had over the last 20 years through open source was massive, but we still saw the industry grow enormously. I think we'll see the same effect with AI.
It sounds like it's a flywheel effect of demand begets demand.
Yeah. And we're already seeing that. We're already seeing, you know, we're delivering productivity benefits to clients through the use of AI. They're asking us to do more work. They're not saying, okay, stop.
Sure. That makes sense. I have a million more questions, but we're out of time. I want to thank everyone for joining us today. Thank you, John and Mark, and thanks everyone else.
Thank you all for coming.
Thank you.