ExlService Holdings, Inc. (NASDAQ:EXLS) Q3 2025 Earnings Call Transcript

ExlService Holdings, Inc. (NASDAQ:EXLS) Q3 2025 Earnings Call Transcript October 29, 2025

Operator: Hello, and welcome to the EXLService Holdings, Inc. Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Also, as a reminder, this conference is being recorded today. If you have any objections, please disconnect at this time. I will now turn the call over to Shirley Macbeth, Chief Marketing Officer.

Shirley Macbeth: Hello, and thank you all for joining EXL’s Third Quarter 2025 Financial Results Conference Call. On the call today with me are Rohit Kapoor, Chairman and Chief Executive Officer; and Maurizio Nicolelli, Chief Financial Officer. We hope you’ve had an opportunity to review the third quarter press release we issued yesterday afternoon. We’ve also posted a slide deck and investor fact sheet on our Investor Relations website. As a reminder, some of the matters we’ll be discussing this morning are forward looking. Please keep in mind that these forward-looking statements are subject to known and unknown risks and uncertainties that could cause actual results to differ materially from those expressed or implied by such statements.

Such risks and uncertainties include, but are not limited to, general economic conditions, those factors set forth in yesterday’s press release, discussed in the company’s periodic reports and other documents filed with the SEC from time to time. EXL assumes no obligation to update the information presented on this conference call today. During our call, we may reference certain non-GAAP financial measures, which we believe provide useful information for investors. Reconciliation of these measures to GAAP can be found in our press release, slide deck and investor fact sheet. With that, I’ll turn the call over to Rohit.

Rohit Kapoor: Thanks, Shirley. Good morning, everyone. Welcome to EXL’s Third Quarter 2025 Earnings Call. I’m pleased to report another strong quarter as we consistently executed on our data and AI growth strategy. In the third quarter, we generated revenue of $530 million, an increase of 12% year-over-year. And we grew adjusted EPS by 11% and to $0.48 per share. In the quarter, our data and AI led revenue grew 18% year-over-year, reaching 56% of total revenue. Our data and AI-led revenue comes from EXL’s AI-powered solutions and services, including those in which we embed data and AI into client workflows. This is the third consecutive quarter we have accelerated our data and AI-led revenue growth, underscoring both the rising demand for AI-driven solutions and demonstrating our leadership in embedding AI directly into client workflows.

At the same time, our Digital Operations revenue grew 6% year-over-year. This is significant when you consider but as we embed AI into workflows, we manage, the revenue moves from Digital Operations to the data and AI-led revenue category. Our third quarter results displayed sustained momentum across all operating segments. The Insurance segment grew 9% year-over-year, which represented 1/3 of our revenue in the quarter. This growth was driven by our Insurance clients evolving their operations to be more AI-powered. We believe the increased adoption of AI in the workflow in Insurance is a long-term trend from which EXL is well positioned to benefit. Healthcare and Life Sciences represented 1/4 of our revenue and was once again our fastest-growing segment at 22% growth.

This performance was fueled by our demand for data and AI solutions. This included growth in our payment services business as well as expansion of digital operations and analytics services with new and existing clients. banking, capital markets and diversified industries grew 12%, representing nearly 1/4 of our revenue. Looking ahead, we see significant opportunity to further increase value and improve business outcomes in this segment by leveraging our enhanced data and AI capabilities across the value chain. In Q3, we drove 8% year-over-year growth in our International Growth Markets segment as we continue to diversify our business geographically. This segment represented 18% of our total revenue in the quarter. International markets represent meaningful potential for us to accelerate our long-term growth trajectory and expand our global footprint.

We are encouraged by the overall demand environment, which remains positive. Our sales pipeline grew with the addition of several new data and AI-led opportunities. As enterprises navigate ongoing economic uncertainty, their priorities are expanding beyond the traditional focus on cost efficiency. They are also looking to change their business models, expand their total addressable market and grow revenue. As clients adopt AI to help achieve these goals they need trusted partners to help them navigate change and deliver tangible business outcomes. With our proven track record and comprehensive set of innovative AI-led solutions. We are a natural partner for our clients on this journey. For our existing contracts, we maintain exceptionally high renewal rates.

More than 75% of our revenue is recurring or annuity like. This provides revenue stability and predictability. Combined with a healthy new business pipeline, we have momentum to sustain double-digit top line growth into 2026. I’d like to highlight progress made in advancing our data and AI strategy to deliver differentiated value for our clients. I’ll cover 3 areas: number one, the launch of our new EXLdata.ai solution; two, client momentum with the adoption of embedding AI in the workflow; and three, industry recognition of our domain, data and AI leadership. Firstly, I’ll cover the launch of our latest innovation. Earlier this month, we unveiled EXLdata.ai the first its-kind agentic AI suite of data solutions that help clients make their enterprise data AI ready.

Data is the single biggest barrier to AI adoption. Our research shows only 30% of organizations can access their data enterprise-wide and most struggle with unifying data silos across legacy platforms. The challenge is especially acute with unstructured data, which now represents 85% of all enterprise data, especially in regulated industries. To make unstructured data AI-ready, it needs to be annotated, labeled and categorized within a structure. This is a manual, time-consuming and expensive process. We built EXLdata.ai to solve these challenges with EXLdata.ai, more than 65 AI agents autonomously managed data modernization, governance, quality, lineage and data accessibility across the entire data life cycle. This AI-first approach sharply reduces implementation time, which previously used to take months, down 2 weeks and even days, Built on a platform-agnostic architecture, EXLdata.ai integrates seamlessly with all leading data platforms, including our launch partner, Databricks, and Snowflake and Palantir and can be deployed across all the major cloud providers, including Microsoft Azure, Google Cloud Platform, Amazon Web Services, as well as with NVIDIA’s accelerated computing infrastructure.

We believe EXLdata.ai is a game changer, helping clients overcome the biggest hurdle to AI adoption. Next, I’d like to highlight our success with embedding AI in client workflows. I’ll share 3 examples that are illustrative of the scale of many projects underway and the client business value that we generate. The first use case is our multi-agent powered solution for a U.K. insurer designed to improve and accelerate risk assessment for underwriters. EXL embedded AI into a new business submission workflow that processes thousands of e-mails and attachments each month. The AI agents extract the right information and assess risk in real time. Processing time has been reduced from a week to a few hours and court conversion has increased by 7%. Real-time insights for brokers also help improve the customer experience during client interactions.

The second client example is a large U.S. health care organization. The collaboration began with the successful delivery of an enterprise-wide Gen AI platform for document processing which has become a foundational solution for managing unstructured data across the organization. Building on that momentum, we are designing a next-generation agentic ecosystem to power safe and secure solutions across their finance, pricing and supply chain functions. These AI-powered solutions are helping to reduce the cost of care accelerate speed to market for new solutions and improve end user experiences, work that used to take weeks can now be done in hours. My third example demonstrates how EXL is using AI to transform digital operations for existing clients.

EXL’s in-depth knowledge of the client processes that we already run is a huge advantage in accelerating infusion of AI and driving faster outcomes. For the past two decades, EXL has been a strategic partner to one of U.K.’s largest energy and home services companies. We’ve helped them reimagine their end-to-end operating processes, including onboarding, meter to cash, consume-to-pay and customer exit. By integrating data and AI throughout the front, middle and back office operations, over 35% of transactions that we run for this client are now AI-enabled. Our solutions have driven significant improvements in customer experience, including achieving 98% onboarding accuracy and a 10% upliftment in billing accuracy and timeliness. In addition, our initiatives leveraging intelligent automation and applied AI have improved productivity by over 30%.

Our revenue from this client has not declined as we were awarded additional work that grew the relationship. And we are positioned really well to begin implementing agentic AI for this client and grow value-added revenue streams. These 3 client examples are representative of numerous successful EXL client AI deployments. While many enterprises struggle to generate returns from AI investments, EXL’s unique strengths in domain, data and AI are delivering meaningful ROI and transforming how businesses operate. This has resulted in a success rate of over 90% and for EXL’s AI deployments. Finally, I’m proud to share that in Q3, EXL received several recognitions of our AI services and solutions leadership across our core industry verticals. Here are a few highlights.

In Insurance, we were named a market leader in the HFS Research, Horizon Insurance Services 2025 report, which emphasized EXL’s data-first approach, deep insurance expertise and AI-driven operational insights. For health care, EXL was recognized as a leader in Everest Group’s Healthcare Data, Analytics and AI Services PEAK Matrix 2025 for our domain expertise, analytics focus and strong partner ecosystem. In banking, EXL was recognized as a category winner in the 2025 IDC FinTech Real Results program. We were recognized for building a financing solution that allowed First National Bank of Omaha to introduce new financing options quickly, integrate seamlessly with merchants and scale with agility. These recognitions validate EXL’s innovative data and AI expertise as well as our unique approach to helping clients deliver significant business outcomes at scale.

In conclusion, we saw strong demand for our services and solutions across the markets we serve. We have bolstered EXL’s competitive position by investing in next-generation data and AI capabilities with the launch of EXLdata.ai. Our business portfolio is well balanced and stable and we have excellent visibility and confidence for the remainder of the year. As a result, we are raising our revenue and EPS guidance for the full year. With that, I’ll turn the call over to Maurizio to provide more details on our financial performance.

Maurizio Nicolelli: Thank you, Rohit, and thanks, everyone, for joining us this morning. I will provide insights into our financial performance for the third quarter and 9 months ended September 30, followed by our revised outlook for 2025. We delivered a strong third quarter with revenue of $529.6 million, up 12.2% year-over-year on a reported basis and 12.3% on a constant currency basis. Sequentially, we grew 3.1% on a constant currency basis. Adjusted EPS was $0.48 and a year-over-year increase of 10.8%. All revenue growth percentages mentioned hereafter are on a constant currency basis unless otherwise stated. Now turning to the third quarter revenue by segment. The Insurance segment grew 8.5% year-over-year with revenue of $180.5 million and 4.9% sequentially.

This growth was primarily driven by expansion in existing client relationships and new client wins. The Insurance vertical, including revenue from International Growth Markets grew 7.3% year-over-year with revenue of $211.1 million. The Healthcare and Life Sciences segment reported revenue of $135.3 million, representing growth of 21.6% year-over-year and 4.5% sequentially. The year-over-year growth was driven by higher volumes in our payment services business expansion in existing client relationships and new client wins. The Healthcare and Life Sciences vertical, including revenue from International Growth Markets grew 21.5% year-over-year with revenue of $135.5 million. In the Banking, Capital Markets and Diversified Industries segment, we reported revenue of $121 million representing growth of 11.8% year-over-year.

This growth was driven by the expansion of existing client relationships, primarily in Banking, Capital Markets and new client wins. The Banking, Capital Markets and Diversified Industries vertical, including revenue from International Growth Markets grew 12.1% year-over-year with revenue of $182.9 million. In the International Growth Markets segment, we generated revenue of $92.8 million, up 8.4% year-over-year and 1.7% sequentially. This growth was primarily driven by higher volumes with existing clients in Banking, Capital Markets and Diversified Industries and new client wins. SG&A expenses as a percentage of revenue increased by 120 basis points year-over-year to 21.3% driven by investments in front-end sales and marketing. Our adjusted operating margin for the quarter was 19.4%, down 50 basis points year-over-year, driven by investments in front-end sales and new solutions.

Our effective tax rate for the quarter was 22.1%, down 70 basis points year-over-year, driven by higher profitability and lower tax jurisdictions. Our adjusted EPS for the quarter was $0.48, up 10.8% year-over-year on a reported basis. Turning to our 9 months performance. Our revenue for the period was $1.55 billion, up 14% year-over-year on a constant currency basis. This increase was driven by double-digit growth across both our data and AI-led and Digital Operation Services. Our data and AI-led services grew 17.1% year-over-year on a constant currency basis. The adjusted operating margin for the period was 19.7%, up 10 basis points year-over-year. Our first 9 months adjusted EPS was $1.45, up 19% year-over-year. Our balance sheet remains strong.

Our cash, including short- and long-term investments as of September 30 was $393 million, and our revolver debt was $355 million, for net cash position of $38 million. We generated cash flow from operations of $233 million in the first 9 months of the year versus $163 million for the same period last year. This improvement was primarily driven by higher profitability and better working capital management. During the first 9 months, we spent $42 million on capital expenditures and repurchased approximately 4.2 million shares at an average cost of $44 per share for a total of $183 million. This includes 2.3 million shares received upfront as part of the settlement of our previously announced $125 million accelerated share repurchase plan. We expect to receive the remaining shares in the fourth quarter.

Now moving on to our outlook for 2025. Based on our strong year-to-date performance, continued momentum and current visibility for the remainder of the year, we are raising our revenue and adjusted EPS guidance. We now anticipate 2025 revenue to be in the range of $2.07 billion to $2.08 billion, representing year-over-year growth of 13%, both on a reported and constant currency basis. This is an increase of $15 million at the midpoint of our previous guidance. We expect a foreign exchange gain of approximately $2 million to $3 million, net interest income of approximately $1 million and our full year effective tax rate to be in the range of 22% to 23%. We expect capital expenditures to be in the range of $50 million to $55 million. We anticipate our adjusted EPS to be in the range of $1.88 to $1.92, representing year-over-year growth of 14% to 16%.

To conclude, we delivered a strong third quarter, demonstrating our formidable competitive position in embedding AI into the workflow. Our resilient business model and strong sales pipeline gives us confidence in our ability to maintain double-digit growth momentum in 2026. With that, Rohit and I would be happy to take your questions now.

Q&A Session

Operator: [Operator Instructions]. Our first question will come from Surinder Thind with Jefferies.

Surinder Thind: Rohit, can you maybe just talk a little bit about how you’re thinking about the change in the overall demand environment? Would you characterize it as relatively unchanged or are clients maybe getting a little bit more positive when it comes to kind of some of the innovation spend that obviously, you guys sit on a different end of the spectrum versus some of your peers, but I just wanted to understand what you’re seeing in your commentary on the sustainability of the double-digit organic revenue growth.

Rohit Kapoor: Sure, Surinder. So I think the way I would characterize it is that the overall demand continues to be very strong. And what we are seeing is that the TAM for our services and solutions has really expanded. But this is probably the first quarter in which the shift in demand is now visible in our financials. And you can see that our data and AI-led revenue has moved quite significantly up and become 56% of our total revenue. We can see the conversion of some traditional domain and F&A operations, businesses that we used to manage being converted to AI-led operations. We can see Gen AI and agentic AI move from POCs to production to actually going to enterprise scale. And there is a huge amount of demand that is building up around data enablement for AI.

So frankly, the market overall demand in terms of innovation spend and sustainability is moving exactly in the direction in which we thought we should be strategically playing and building out our capabilities. And some of this is now becoming quite visible in our financials. We are pleased with our ability to gain new clients. We are pleased with our ability to win market share from other providers. And we’re pleased to become the AI transformation partner for these clients and help them along these journeys. So when we think about sustained growth in double digits, we are very confident of our ability to be able to drive that because our data and AI-led business, which is 56% and it grew at 18% in the third quarter, that alone will be able to command a double-digit growth rate for the full company.

So frankly, all of these signs are very encouraging for us and the pivots that we have made seem to be playing out quite nicely.

Surinder Thind: That’s helpful. And then I guess as a follow-up in the shift in demand and the shift in the underlying business. I think you pointed out some interesting things where work that may be used to take months may now be done in weeks and in a few instances or some instances, maybe it can be done in the course of hours or a week. That sounds very deflationary, right, optically. Can you maybe help us understand how and where the makeup of this is that when you go to that client and you offer to do work that used to be 3 months, and now you’re telling him, hey, we can do it in 3 weeks. Where is that incremental revenue coming from? Are you now doing 3 or 4x times as much work with that client? Or what is going on here to help us understand the sustainability of the growth rate?

Rohit Kapoor: Yes, absolutely. And the best anecdotal example of that was what I shared in my prepared remarks about an existing client for which we have implemented AI-led operations. And now we have 35% of the transactions, which are AI-enabled, and that’s generated 30% productivity benefit for this client. And yet our revenue for this client has remained the same. And to your point, the reason the revenue has remained the same is, this client obviously has great confidence in our ability to be able to apply AI and deliver that productivity benefit to them. And therefore, they’re giving us more and more work which is being shifted over from what they were running themselves or what they might have been running with other providers and we are winning more business from them.

And therefore, this deflationary piece that you talk about, we don’t really see that because today — even today, I mean, the penetration of the work that we do with our clients is still relatively low. And the opportunity set for us is enormous. And then finally, there are new areas that this client would never have engaged with in the past with anybody, so things around agentic AI, things around bringing together their data together and bringing it in a manner that can be accessed, looking at data lineage, looking at data governance. These are things which were never necessary in the past because AI was not being used in these business operations. And now that it is these are areas that need to be kind of worked upon and we are the natural choice partner for them.

So frankly, what we are seeing is the more benefit we can provide to our clients and the quicker we can do it for them. the more they tend to rely on us and give us more work and we become an even more trusted partner in this journey.

Operator: Our next question will come from Bryan Bergin with TD Cowen.

Bryan Bergin: First question is on digital ops. So can you just unpack further your expectations for the fourth quarter for digital ops and really into fiscal ’26 as well, just given the first half comps. And Rohit, just based on that demand shift you noted here recently, where does the comfort lie in digital ops longer term? Is it still kind of high single digits? Is it mid-single to high single? And then my follow-up, I’ll ask both up front here. Just on the top client, what’s driving that top client strength and what’s the sustainability.

Rohit Kapoor: Sure. So Bryan, first of all, I just want to make sure that everybody understands that when we talk about Digital Operations, it includes 3 service lines below that. Number one is domain operations; Number two is finance and accounting operations; and number three is platform services. So those are the 3 elements that constitute our Digital Operations business. Now in terms of the growth rate of Digital Operations, clearly, as we embed AI into domain operations, F&A operations and platform services, some of that revenue is moving from the Digital Operations bucket to the data and AI-led bucket. So that’s very important to understand because we ourselves are AI-enabling a lot of digital operations and making it data and AI-led operations.

What you are seeing is the net growth of Digital Operations, which is at 6% for this quarter. What you are not seeing is that the overall growth rate of this business is much higher. And because the shift of Digital Operations to data and AI led is taking place, that’s not visible to you. So that’s something which I just want to preface the conversation in. Now in terms of how we are seeing domain operations grow, finance and accounting operations grow, platform services growth. We’re actually very pleased with how clients are engaging with us a lot more in this direction. And when they first engage with us, a lot of this is some of the traditional work that we have done with them. And then very quickly within the first 6 months to 1 year, we start to apply AI into this operation.

So frankly, this engagement with a new client, starting out with the Digital Operations and then converting it to an AI-led operations is a very good pathway and we feel very good about the kind of growth that we are seeing, the kind of engagement that we are experiencing. And this seems to be working really, really well. The top client question that you asked, for us, the top client grew very nicely year-on-year. And I will tell you this that our penetration rate with this top client still is extremely low. And we think there’s an opportunity set for us to really expand this volume of business with the top client far, far more meaningfully. In fact, it can be multiples of the amount of business that we do with this client today. So there is no real limit to how much we can grow.

I think if you also look at our second largest client, that also grew very nicely. So frankly, as we get more engaged with clients across multiple service lines, which includes domain operations, finance and accounting operations platform services, analytics, data management, AI services, our ability to expand work and revenue with large clients is actually — there’s a tremendous amount of potential out there.

Operator: Our next question will come from Maggie Nolan with William Blair.

Margaret Nolan: Maybe to build on an earlier question about your ability to win additional work in these clients, can you talk about how you’re changing your client relationship management, your go-to-market motions and those types of things. And just in general, your confidence in your ability to win additional market share as these shifts happen?

Rohit Kapoor: Sure, Maggie. I think that’s a really important attribute and you’re touching upon something which we’ve been working on very proactively because clearly, the nature of our conversation with our clients has changed. It’s no longer about just providing them with cost efficiency. It’s much more about innovation. It’s much more about transformation of their business model a lot more about applying AI correctly in a sustainable way. So what that means is 2 or 3 things. Number one, our account managers and our client executives and our sales hunters. They all need to be proficient in terms of being able to engage and talk to clients with the use of some of these highly complex and newer technologies. So they need to be conversant with data with AI.

They need to know how to apply that into the client workflow. They need to understand what it takes in order to pull this whole ecosystem together and deliver that business outcome to them. So that’s a big change, and we are training our front-end teams to learn, understand and be able to communicate this appropriately to our customers and our prospects. The second thing that’s happening is, we are no longer talking only to the Chief Operating Officer. We’re talking to the CIO. We’re talking to the CDO. We’re talking to the Business Head. We are talking to the CEO. And therefore, the buying centers are much more integrated and much more spread across the organization. What that also means is these are much larger deal sizes, and these are much more strategic decisions that the client needs to make.

And the third part of it is the entry point for us is it starts off with providing them the confidence on a single use case and then expand that use case at scale for the enterprise and then actually expand and proliferate across the organization across multiple businesses, multiple geographies and multiple functions. So the go-to-market piece has changed quite significantly. And then the third element of this is a large part of our go-to-market is now with partners. So the partners has got a number of the technology partners that we partner with. So we partner with Microsoft Azure, with GCP, we partner with AWS, we partner with the data platforms, Databricks, which is our launch partner for EXLdata.ai, with Snowflake, with Palantir and the go-to-market motion is jointly with these technology partners.

We’re also partnering with private equity firms, which are looking at applying this AI into their portfolio of clients a lot quicker. So again, the go-to-market motion has changed very, very significantly.

Margaret Nolan: That’s great detail. My follow-up would be about the growth in revenue per employee. Can you talk about the puts and takes there, just given that your growth was led by the data and AI? I would have expected that to track a little more closely with that growth rate? Any incremental color would be great.

Rohit Kapoor: Right. So we are seeing there to be changed an upward improvement in terms of the revenue per employee across the company. So that’s a trend we would expect to see going forward for the next several years as we apply AI and we get into more complex work for our clients. But keep in mind that we are also going to see this happen over a period of time. So there may be quarters in which this will move in different directions. It all depends upon what work we are winning, what the business composition of that work is and how that correlates. You can see actually quite visibly that the number of employees that we’ve added year-on-year is at a much slower pace as compared to our revenue growth rate. And that’s been trending for the last several quarters.

And that’s something which we would expect to see going forward. So we would expect to see our revenue grow double digit but we don’t expect to add employee head count at a double-digit growth rate. It’s going to be pretty much in a single digit, maybe a mid- to high single-digit kind of a growth rate.

Operator: Our next question will come from David Koning with RW Baird.

David Koning: Good quarter. I guess A couple of questions. My first question, Healthcare has dramatically grown the last couple of years. It’s about 50% bigger than 2 years ago. Maybe just talk a little bit about the outlook there. Can you keep growing this fast? What are you doing to kind of keep the pipeline going. But yes, the biggest question is just can it keep this growth rate up? It’s been so good.

Rohit Kapoor: So Dave, for us, the way we think about it is that our Healthcare business is really in its infancy because the health care market is so enormous and so huge. You also know that it’s very data rich. It’s got broken and fragmented processes. It is adopting AI and it’s applying analytics in a much more aggressive way. And therefore, the opportunity set in health care is enormous. We are pleased with how we’ve — we are building up our Healthcare business. If you talk to our clients in Healthcare, they can clearly see the kind of value that we bring to them. Our payment integrity business continues to grow very nicely. But what we are also very pleased with is that our domain operations business in health care this year grew very nicely.

So frankly, there are multiple areas where we can help our clients as such. One of the biggest opportunities for health care is going to be able to help them around their data. And that’s something which we can see again is growing nicely. So the headroom for us is enormous. These are enormous markets for us. And I think even if we’ve grown 50% it’s just a fraction of where our potential is within these industry segments.

David Koning: Yes. Okay. Great to hear that. And then a question for Maurizio. You’re doing a really nice job executing to the full year plan on margins. But it’s a little bit lumpy just the way Q1 was so good with margins. And then now as you’re kind of going through the year just as expected. But margins being down in Q3 and maybe flattish in Q4, it looks like is — you still expect growth next year, right, like growth in margin next year? I’m just wondering the cadence this year, is next year going to be more kind of stable growth through the year?

Maurizio Nicolelli: So Dave, you are correct, right? So the first half of the year, our adjusted margin was 19.9%. We just closed the quarter at 19.4%. So it’s a little bit lumpy this year, right? We started extremely high, just over 20% in Q1, and we’re trending more towards what I’ve been guiding to is 10 to 20 basis points higher on a year-over-year basis, which would put us right around 19.5% for the year. So going forward, when we look at Q1 and also 2026, we continue to see margin improvement of 10 to 20 basis points a year, but a little bit more flatlined than what you’ve seen this year, meaning Q1 should be a little bit more reflective of the annual margin going forward. And you should see that for the rest of next year. So a little bit more balanced next year. But right now, you’re seeing us spend a bit more on front-end sales and also on capability development and that’s where we’re really putting our investment dollars in the second half of the year.

Operator: Our next question will come from Vincent Colicchio with Barrington Research Associates.

Vincent Colicchio: Rohit, the EXLdata.ai, the product sounds very promising. Just curious, what does the landscape look like there? Are there similar products out there?

Rohit Kapoor: So yes, Vincent, I think on the data side, a number of companies which are trying to build solutions and help clients manage their data and get their data AI-ready, we all know that, that’s the #1 problem that clients face. But I think the way in which we have thought about being helpful to our clients is really to use AI to make data AI ready. And therefore, the large part of the effort and the heavy lifting is not manual, but actually it leverages AI itself for helping our clients have that data be AI ready. I would say that we differentiate ourselves in 2 ways. Number one is the use of AI for data being AI ready. And number two, is we built this platform and the solution set, which is fully comprehensive end-to-end.

And that means it can help in data lineage, data accessibility, data governance, master data management, having data being coordinated across different platforms and silos and really attacking unstructured data which is the heaviest piece of lifting that needs to happen and do that by leveraging AI itself. So as of today, we think this is really a first of its kind. When we talk to our launch partners and other partners, which have data platforms, they find this solution to be compelling. And we are seeing tremendous amount of excitement around this. So a lot of demos, a lot of use cases and a lot of activity associated with this at this point of time.

Vincent Colicchio: Thanks for that. The International segment looks should be a large opportunity for you given your penetration. What are you doing to accelerate that? Are you making investments in the marketing side, for example?

Rohit Kapoor: Yes, Vincent. You’re right. The International piece for us should overall be growing at a faster pace. And that’s something which we are consciously investing in and also making sure that we have senior executive talent closer to our customers out there. So we are bringing on additional talent out there. We are taking our solutions and capabilities that we’ve created and leveraged with some of our U.S.-based clients and applying that into these international geographies. We are building up some local partnerships in these geographies. And we really do need to mature the business as such, but the opportunity and the potential is very, very strong here.

Operator: Next question will come from David Grossman with Stifel Europe.

David Grossman: I wonder if we could talk a little bit more about the requirements to really deploy enterprise or AI, if you will. And I think Rohit, you’re talking quite a bit on this call about the amount of data preparation required to execute that and the new products that you have in the marketplace that automates a large part of that. So when you’re going to these clients, are you going to market offering this service, which is then converting into follow-on revenue? So in other words, is it being sold as a stand-alone business. And if it is, what is the typical multiplier effect that you’re getting once you get in with the client on that type of engagement in terms of the following work.

Rohit Kapoor: That’s a great question, David. You’re right. We’re doing this in two different motions. One is on a stand-alone motion. So we are taking EXLdata.ai as a stand-alone capability and whether or not our clients use us for embedding AI into the workflow, we’re just helping them get that data estate in order and make sure that their data is AI ready. And so these are stand-alone engagements. They typically start off with demonstrating our ability with one particular use case, but it very quickly expands to kind of working across the enterprise and working across a number of their legacy data platforms and converting that and moving that to the cloud and moving that into a much more modern data platform. So that’s one motion.

The second motion is where we engage with clients to help them embed AI into the workflow, and we have the responsibility of doing the end-to-end charter, which means we have to get the data estate in order. We have to apply AI to that data and we have to deliver a business outcome to the client. And there, it’s in a much more integrated format that we bring in our capabilities and services. We are finding actually both of these seem to be resonating. And clearly, the need for this across our clients is very, very strong.

David Grossman: So what do you think the multiplier is stand-alone versus kind of the integrated sell?

Rohit Kapoor: At this point of time, David, the data management piece in itself is a large part. So the AI enablement is a much smaller piece, but the heavy lifting is much more around the data enablement. So the multiplier at this point of time is not that strong. But I think as this kind of progresses, it will become larger and larger. And so we’ll see how that plays out.

David Grossman: And then just as you’re thinking I know you’ve guided to double-digit growth as your target model here. And as you kind of formulated that double-digit target, how much of that is kind of net revenue retention or same-store growth, same client growth versus new bookings?

Rohit Kapoor: Yes, that’s a very strong metric for us, David, because with existing clients, as we embed more AI as we deliver greater value to them, the renewal rates are north of 90%. We continue to win additional business from them and then we add on new clients. I think we’ve shared this metric before for us, adding new clients in any given year only contributes somewhere between less than 5% of the revenue for that year. So a large part of this is with existing clients that we are able to kind of build and grow.

David Grossman: Got it. And just if I could sneak one more in because I was a little confused by your response to an earlier question because I think you said that you were getting 30% productivity gains from a client, yet their client — their revenues were remaining flat. So I think the context of the question was the deflationary — or potential deflationary component of AI to the industry, not just for EXL. So did I hear that right that it’s flat? And if I did, again, I guess I would ask the same question again. How should we think about this if we’re just getting to flat off of a 30% productivity gain?

Rohit Kapoor: Yes. So think about it this way that if our revenue was $100, we were able to provide a productivity benefit of 30% and it dropped down to $70 we were given incremental revenue of another $30 that brought it back to $100. Now we came back to $100 with better margins, higher revenue per head count and an increased amount of value for the customer. So our penetration rate with that customer increased and the strategic relationship with that customer just got enhanced.

David Grossman: Got it. So then is that more of a I wouldn’t call it a onetime event, but is it really just more of an upfront event. So if you can keep it flat, that’s kind of a victory, and then you can grow off that base going forward? Is that the way to think about it at higher margin and higher value?

Rohit Kapoor: Yes. So that part of the business for us remained flat. But we then became a strategic partner for the same client on helping them use agentic AI. And agentic AI is a space that we would have never played with in the past and the client would never have kind of used us in the past. And therefore, it opened up newer revenue streams, which are much more higher value added and a much more strategic and much higher margin.

Operator: We have no further questions this time. This concludes our call. Thank you, and have a good day.