Good day, and thank you for standing by. Welcome to the Second Quarter 2024 EXL Service Holdings, Inc. earnings conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker for today, John Kristoff, Vice President of Investor Relations. John, please go ahead. Thanks, Felicia. Hello, and thank you for joining EXL's Second Quarter 2024 financial results conference call. On the call with me today are Rohit Kapoor, Chairman and Chief Executive Officer, and Maurizio Nicolelli, Chief Financial Officer. We hope you've had an opportunity to review the second quarter earnings release we issued this morning. We also have posted an earnings release slide deck and investor fact sheet in the investor relations section of our website. As a reminder, some of the matters we'll discuss 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 today'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. Thanks, John. Good morning, everyone. Welcome to EXL's Second Quarter 2024 earnings call. I'm pleased to be with you this morning, sharing our strong financial results. In the second quarter, we generated revenue of $448 million, an increase of 11% year-over-year. We also grew second quarter adjusted EPS by 11% to $0.40 per share. The execution of our data and AI-led strategy enabled us to accelerate our growth momentum across both our analytics and digital operations and solutions businesses during the quarter. In analytics, we delivered revenue of $194 million for the quarter, up 2% sequentially and 6% year-over-year, driven by strong double-digit growth in healthcare payment services and data management. I am pleased to share that this marks the second consecutive quarter of sequential growth for analytics, which positions us well to accelerate our growth rate in the second half of the year. Data management continues to be a major focus area for EXL and for our clients on their AI journey. The ability to generate insights and outcomes using AI hinges on accessible, quality data, both structured and unstructured. In line with our strategy, I'm thrilled to announce our acquisition of ITI Data, a leading information and data management company serving the world's largest banks, financial services, and healthcare firms. This acquisition not only bolsters our data management capabilities, but also greatly complements EXL's existing vertical markets, expanding our data and AI partner ecosystem, and grows our geographic and Global 1000 client footprint. This acquisition is an example of our commitment to further enhance our competitive differentiation by acquiring wider skill sets and deeper expertise in data management as we strengthen our position as a data and AI-led company. In our digital operations and solutions business during the second quarter, we once again delivered strong double-digit growth as we leverage our domain, data, and AI capabilities to win in the market. We grew revenue 4% sequentially and 14% year-over-year to $255 million. This acceleration of growth was driven by our insurance and emerging business segments, which grew 16% and 15%, respectively. Our clients continue to focus on cost efficiency and digital transformation, creating a favorable demand environment for us. Last month marked EXL's 25th anniversary, and we commemorated the milestone by ringing the opening bell on Nasdaq. As I reflect on our journey over the past two and a half decades, our transformation from a traditional outsourcing company to a recognized leader in data and AI has been truly remarkable and stands out. Our strategic decisions to make timely pivots and evolve into a data and AI-led company has contributed to our industry-leading growth rates. More importantly, we have positioned EXL for success in the rapidly evolving and expanding AI era. As we shared in our investor strategy update event in May, AI has changed the business transformation landscape from one that was historically technology-led, to one that is now increasingly domain and data-led. This plays to our core strengths in domain expertise, data mastery, and AI implementation capabilities. It has significantly expanded our total addressable market and accelerated our growth rates. Data and AI-led revenue now accounts for more than half of the company's total revenue, and we anticipate that percentage to grow over time. We recently announced a strategic collaboration with NVIDIA to create enterprise-wide data and AI applications for insurance, healthcare, banking, retail, and other industries. EXL's adoption of advanced AI technologies, powered by NVIDIA AI, helps our clients with fast and scalable AI in complex enterprise production environments. As a leader in helping clients redesign customer journeys and reinvent business models by integrating data, analytics, and AI directly into critical workflows, EXL will play a pivotal role in fine-tuning and applying the NVIDIA AI platform to highly specialized use cases. I am happy to share that our first insurance-specific LLM, which has been fine-tuned on 2 billion tokens, curated from insurance domain data, is now production-ready. Our fine-tune model outperforms several foundational models, such as GPT-4o, Claude Sonnet, and Llama 3 70 billion on insurance-specific tasks in the medical claims space. We leveraged a number of proprietary data preprocessing and fine-tuning techniques in close collaboration with NVIDIA's engineering teams to achieve this outcome. Given our success, we will continue to create additional domain-specific LLMs across our chosen industries. Our growing ability to tangibly improve our clients' businesses through domain data and AI is reflected in the continued strength of our sales pipeline. We are particularly encouraged by the year-over-year growth we have experienced in the data and AI portion of our pipeline. Let me share a couple of recent examples of how we are harnessing our differentiated capabilities to deliver meaningful value for our clients. We partnered with a global personal and commercial lines insurer to help them improve underwriter utilization and drive higher premium growth. As part of the engagement, we deployed our SaaS-based underwriting solution on our proprietary AI platform. This included our patented GenAI-based ExTractor.AI solution for structured and unstructured data processing, an advanced scoring engine to generate a risk score for all incoming leads, and automated decision-making algorithms. The whole underwriting process now just takes a few hours, where it used to take multiple days. This solution not only improves our client's quote-to-policy conversion, but it also helps them improve the broker experience and drives better underwriter productivity and higher premium growth. This is a great example of how EXL is combining our insurance domain expertise, along with our data and AI solutions, to help our clients transform their operating model. In another example, we have been working with a Fortune 50 consumer goods company to help them solve challenges in their rapidly growing e-commerce business. They were experiencing a surge in data volume, which had strained their internal resources, resulting in frequent data pipeline failures and unreliable data quality. Leveraging our data engineering experience and capabilities, we helped the client streamline data flow and improve data quality. This included combining data in various disparate formats across supply chain, marketing, and sales into a comprehensive data warehouse. We also optimized their data extraction algorithms and developed various actionable executive dashboards, empowering leaders to make informed decisions faster. This resulted in a reduction in pipeline failures of approximately 95%, with consistent data availability and smooth processing. In addition, we were able to reduce their computing costs related to extracting, transforming, and loading data for those pipelines by over a third. These impressive results demonstrate our ability to leverage our deep data management capabilities to become the data and AI partner of choice for some of the largest companies in the world. We continue to see growing opportunities in data management and engineering as more clients focus on complex foundational work necessary to prepare for broader AI deployment in the future. We continue to successfully attract new specialized talent to EXL, as well as train and develop our existing talent in data and AI. In summary, we delivered strong results in the second quarter, and we are encouraged by the acceleration of growth across our analytics and digital operations and solutions businesses. The consistent execution of our data and AI-led strategy, combined with our growing data and AI sales pipeline, puts us in a strong position for further growth in the second half of the year. With that, I'll turn the call over to Maurizio to cover our financial performance in detail. Thank you, Rohit, and thanks, everyone, for joining us this morning. I will provide insights into our financial performance for the second quarter and the first six months of 2024, followed by our revised outlook for the full year. We delivered a strong second quarter with revenue of $448.4 million, up 10.7% year-over-year on a reported basis. On a constant currency basis, we grew revenue 10.8% year-over-year and 2.8% sequentially. All revenue growth percentages mentioned hereafter are on a constant currency basis. Revenue from our digital operations and solutions businesses, as defined by three reportable segments, excluding analytics, was $254.6 million, which represents year-over-year growth of 14.3%. Sequentially, from the first quarter of 2024, we grew revenue 3.6%. In the insurance segment, we generated revenue of $149.3 million, an increase of 16.2% year-over-year and 2.8% sequentially. This growth was driven by the expansion of existing client relationships and new client wins. The insurance vertical, consisting of both our digital operations and solutions and analytics businesses, grew 12.9% year-over-year, with revenue of $185.7 million. In the emerging segment, we grew revenue 15.1% year-over-year and 4% sequentially to $77.2 million. This growth was primarily driven by the expansion of existing client relationships. The emerging vertical, consisting of both our digital operations and solutions and analytics businesses, grew 5% year-over-year, with revenue of $159.7 million. The healthcare segment reported revenue of $28.1 million, growing 3.5% year-over-year and 7% sequentially. This growth was driven by higher volumes in our clinical services business. The healthcare vertical, consisting of our digital operations and solutions and analytics businesses, grew 16.8% year-over-year, with revenue of $103 million. In the analytics segment, we generated revenue of $193.8 million, up 6.4% year-over-year and 1.7% sequentially. Growth in analytics was driven by higher volumes in payment services and growth in our data management business. SG&A expenses as a percentage of revenue increased by 230 basis points year-over-year to 20.5%, driven by investments in sales and marketing, generative AI and digital solutions, as well as restructuring and litigation settlement costs. In the second quarter, we incurred $6.2 million in restructuring and litigation settlement costs to realign a portion of our employee workforce to better meet the evolving needs of our clients. This was largely completed in the second quarter. We do not expect to incur any additional material costs in the third quarter. Our adjusted operating margin for the quarter was 19.8%, down 20 basis points year-over-year, primarily due to increased SG&A investments. Our effective tax rate for the quarter was 23.2%, down 70 basis points year-over-year. This was driven by higher profits in lower tax jurisdictions. Our adjusted EPS for the quarter was $0.40, a 10.8% increase year-over-year on a reported basis. Turning to our first half performance, our revenue for the period was $884.9 million, up 9.8% year-over-year on a reported and constant currency basis. This growth was driven by both our digital operations and solutions and analytics businesses.... Adjusted operating margin for the period was 19.4%, down 30 basis points year-over-year. Our first half adjusted EPS was $0.78, up 9.9% year-over-year on a reported basis. Our balance sheet remains strong. Our cash, including short- and long-term investments as of June 30th, was $285 million, and our revolver debt was $335 million, for a net debt position of $50 million. We generated cash flow from operations of $75 million in the second quarter, compared to $48 million for the same period in 2023, driven by improved working capital management. During the first six months, we spent $23 million on capital expenditures and repurchased approximately 4.3 million shares at an average cost of $30 per share, for a total of $128.3 million. This includes 3.35 million shares received upfront as part of our previously announced $125 million accelerated share repurchase plan. We received the remaining shares in July. Now, moving on to our outlook for 2024. Although the macroeconomic environment remains unpredictable, we are raising our guidance range for revenue based on our strong first six months results and the recent acquisition of ITI Data. We now anticipate revenue to be in the range of $1.805 billion-$1.83 billion, representing year-over-year growth of 11%-12% on both reported and constant currency basis. This represents an increase of $13 million at the midpoint from our previous guidance of $1.79 billion-$1.82 billion. The current revenue guidance includes $7 million-$9 million from ITI Data for the remaining five months of 2024. We expect a foreign exchange gain of approximately $1 million, net interest expense of approximately $5 million-$6 million, and our full year effective tax rate to be in the range of 23%-24%. Based on this, we anticipate our adjusted EPS to be in the range of $1.59-$1.62, representing year-over-year growth of 11%-13%, which is an increase from our prior adjusted EPS guidance of $1.58-$1.62. The ITI Data acquisition is expected to be neutral to adjusted EPS in 2024. We expect capital expenditures to be in the range of $50 million-$55 million. In summary, we are pleased with our second quarter results and encouraged by the acceleration of our growth momentum. By continuing to execute on our data and AI-led strategy, we are confident in our ability to maintain our double-digit growth trajectory. With that, Rohit and I would now be happy to take your questions. Thank you. At this time, we will now conduct the Q&A session. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. Please stand by while we compile the Q&A roster. The first call comes from the line of Maggie Nolan of William Blair. Maggie, please go ahead. Hi, thank you. I'm hoping you can break down your analytics segment in a little bit more detail for us, where you're seeing incremental tailwinds versus where you're seeing headwinds by kind of offering and vertical alignment within the analytics segment as well. Sure, Maggie. So, you know, as we mentioned, the places where we are seeing a tremendous amount of growth is around some of the work that we do on healthcare payment services, as well as data management. Both of these continue to drive, you know, the growth in our analytics business very nicely and, you know, double digits. We are also seeing, you know, some of the strength come back across some of the industry verticals, the work that we do in analytics, particularly in some of the other industry verticals like retail and banking, and that's encouraging for us. And then, as we mentioned previously, marketing analytics for us continues to be a tailwind, and that's something which has, you know, been a drag in terms of our growth rate for the second quarter. Thank you. Can you talk in a little bit more detail about the adjusted operating margin expansion expectations on a quarterly basis, and in particular, what we should expect in terms of SG&A investments over the remainder of the year? Sure, Maggie. So when you take a look at our adjusted operating margin, you know, in 2023, our margin expanded 100 basis points to 19.3%. And we had guided this year to be flat, fairly flat with 2023. If you look at the first half of the year, we ended the first half of the year at 19.4%. We had a lower first quarter because of a number of investments that we planned on making, and we made that brought that AOPM down to 18.9%. But now, now that we've made those investments in the first quarter, we get to much more of a normalized AOPM for the rest of the year. So you can anticipate or expect the second half of the year of AOPM to be right in line with our guidance to being flat with 2023, right around that 19.3%-19.4% range. You know, in terms of SG&A investments, we made a number of investments, both in AI and also in our front-end sales in the first half of the year. So our second-half investments in SG&A should be fairly reasonable, nothing significant in SG&A. Thank you. Solid quarter. One moment for your next question. The next question comes from the line of Bryan Bergin of TD Cowen. Brian, please go ahead. Thanks. Good morning. Maybe on ITI, can you give more detail on how that target complements your existing data management practice? I'm curious if it's about, more about scale or more so additive solutions and kind of the industry penetration. And then just on the financial side, has that, you know, can you comment on how growth has been performing there? Sure. So first of all, we are really excited to welcome the ITI team to become part of EXL. As we've kind of gotten to know them, we find that there's exceptional talent within ITI Data. I think what it does for us is, from a strategic lens, it further strengthens our capability in data management, and it allows us to be able to provide a wider array of services to our clients around data management. It also brings to us, you know, a much more global 1,000 customer base, and so a number of new large client relationships that we think we can leverage together and add to the capabilities out there. It also brings some IP as well as some partnerships, which we think would be additive and would be helpful. And then finally, it's got a very nice global mix of business that complements the capabilities that, you know, EXL has. So we are excited about, you know, this combination, and we think, um, with this combination, we should be able to grow the business, um, at a much faster pace, um, and be able to add to the service offerings that we currently have for our clients around data management. Okay. And then my follow-up, just on the GenAI front, the insurance-specific LLM you trained here is interesting. Can you comment on how you intend to contract engagements that may leverage that, as well as just any other details on the kind of productivity and delivery implications? Yeah. So that's exciting for us. It's our first, um, you know, domain-specific trained LLM, and we naturally chose to do that in our insurance, you know, vertical, where, which is where we've got the maximum amount of domain knowledge as well as access to data. Um, And I think, um, you know, there are a number of things that we are learning as we are experimenting with this and as we are building up these LLMs. Number one, what we are finding is foundational models are good, but when you have to deploy them into the workflow, these need to be specifically trained on the domain and data from that domain, and that's what allows them to be a lot more effective and be able to, um, be a lot more productive. So, one of the things which we have done is to create our own insurance LLM, um, which can now be a plug-and-play. So it actually allows us to be able to offer that service to multiple clients simultaneously, and it requires, um, you know, a one-time effort upfront, which is what we have done, and trained that LLM on 2 billion parameters. And we are finding that the efficacy of that LLM is far superior to the foundational models that we are kind of testing it out against. And so it allows us to be able to deploy the solution with speed, at much lower cost, and get great results. I think in terms of the commercial model, that's something which is gonna evolve as we go forward. It'll depend upon the kind of engagement that our clients want to kind of have with us. Um, if they want to have an engagement which is a total outsourcing engagement, we will embed this as part of the cost structure and be able to offer them, um, a benefit and an outcome, and it might be a commercial model that integrates in our operations management capabilities, our analytics capabilities, and the LLM. In other situations where clients may want to adopt this as a standalone capability, um, there would be perhaps a licensing agreement as well as, um, a payment for the use of this LLM. And And obviously, you know, this is just the beginning for us. Um, we hope to be able to continue to kind of, um, keep improving on this and also building out LLMs in other industry verticals. I think our viewpoint is that that's where the market is headed, and we are excited that we are able to kind of take the lead in terms of going forward with one of these LLMs and be able to demonstrate its performance and its efficacy. All right, very good. Thank you. One moment for your next question. The next question comes from the line of Surinder Thind of Jefferies. Surinder, please go ahead. Thank you. Rohit, just following up on the prior question about proprietary LLMs that are industry-specific, can you help me, help me understand how the training of the models work in the sense that where are you getting that data from? And then are you able to then go to the client, and does it have to be further trained with client data, or where does the IP for some of that exist? Sure, Surinder. So first off, as you know, um, for us, we go deep into industry verticals, and we work with multiple clients across each of our industry verticals. So take insurance as an example. We work with several leading, um, you know, carriers in that space, and we have a deep knowledge and understanding about the workflow, the processes, the data, and everything that needs to happen there. Second, we do have, um, contractual rights to be able to use the data across some of our client relationships. And those, um, situations where we have permissioning to be able to use the data, as well as to be able to use derivative, um, actionable data, um, we're basically using both of this. So we're using, um, the primary data as well as some of the derivative data to be able to train our models, um, on these insurance processes. Now, going forward, um, in terms of, um, you know, the work that we will do, certainly, um, in terms of, um, areas where, you know, we have invested in terms of creating that model, and we have trained that data, that IP will belong to us. But as we deploy it in client, um, workflows, that IP will, you know, jointly be owned by us and by our clients. So it's gonna be no different than other technology solutions that we create or we deploy across our client portfolio. But I think the exciting part out here is the efficacy that we are able to get. I mean, that is beating the foundational models, which are trained on much, much more larger parameters. I think that's, um, what is, you know, exciting for us and for our clients. That's helpful. Then just in terms of a bigger picture question here, I think you've noted that the current environment from a digital ops perspective has been highly supportive with, you know, considerations around cost and efficiency. But as we move towards maybe rates coming down, perhaps a bit more growth on the discretionary spend in part, how are you thinking about the potential impact on the digital ops business? So how much of that tailwind should go away, as we think over the next two, three years or whenever the demand normalizes? Sure. So, you know, fundamentally, when we think about our business and what we are helping our clients with at the highest level, there are two things that we are helping them with. Number one is helping them drive down cost, and number two, helping them transform their businesses. Um, that's what we focus in on the digital operations side. We've said always that, you know, for us, the demand environment continues to be strong as long as the penetration is low and the adoption of our capabilities can be used to leverage for clients being able to benefit from the cost reduction, as well as transformation of their operating processes. In an economic environment where the growth rates are slowing down, the interest rates are coming down, the propensity of clients to focus in on a lot more cost savings becomes even more significant. So frankly, at that point of time, we would expect more and more immediacy in terms of client actions, outsourcing their work and entrusting that work to us, so that we can actually lower and reduce their cost structure in a very significant way. In terms of transformation, the way in which clients are approaching this is, they want to be able to get the benefit of the transformation in the current period itself. And therefore, they want to work with those providers that have the necessary tools and the skill sets and the capabilities that can be deployed immediately, where the return on investment can be very, very high, very quickly. So I think, we end up being a very credible partner for our clients in terms of helping them engage on the transformation initiative as well. So that's why I think, um, for us, the digital operations and solutions business is strong, and we would expect it to continue to remain strong. Our expectation is that our growth rate has accelerated in the second quarter, both in analytics and in digital operations and we do expect that acceleration to continue in the second half of this year. Thank you. One moment for our next question. The next question comes from the line of Puneet Jain of JP Morgan. Puneet, please go ahead. Yeah, hi, thanks for taking my question. I have like a follow-up on digital ops. So it seems like in the industry, um, clients, in-house operations are ramping up on an overall basis. Are you seeing that trend in operations management as well? And, broadly, what do you expect for insourcing versus outsourcing decisions by your clients in digital ops? Hi, Puneet. Um, yes, I think clients, um, do use multiple avenues for being able to manage and run their operations efficiently, and certainly creating in-house operations or captive operations or global, you know, captive centers, that is certainly part of their portfolio. I think the place where we tend to have an advantage is where there is, um, leading and cutting-edge technology that needs to be applied, where data flows need to be integrated in the, um, you know, customer workflows, where AI needs to be deployed. Um, you know, that's where I think we have an advantage, because we tend to see this across multiple clients and across multiple, um, you know, um, use cases. And therefore, our understanding of being able to deploy this effectively in a shorter time period and quickly tends to be a little bit better. So it actually works quite well because we end up complementing, um, you know, some of the work that, the in-house captives are doing. And many times, um, you know, we might do the work, um, initially, and, um, subsequently, the captive might do that work, um, or vice versa, right? So it actually is a good ecosystem. I think the key is: can we continue to remain competitive and continue to innovate and continue to be, um, adding value to our client relationships, um, across the board? I think, by virtue of us going deep into the domain, by going deep into data, by going deep into AI, which is our strategy, we are able to maintain that differentiation and that competitive edge. Got it. No, that makes sense. And then you had, like, accelerated repurchase this year, just completed an acquisition. Um, from here on, how should we think about the use of cash? And also, like, how much you are paying for, um, the ITI acquisition? Sure, Puneet. So, um, to answer your latter question, the ITI acquisition was $26 million in cash that we purchased the, um, company for. So we, we used that from existing cash resources. You know, going forward, you know, we have been pretty aggressive on share repurchase, um, in the first seven months of the year. We closed the ASR in July, and we've repurchased right around $160 million worth of stock so far this year, right around $30 per share. So it's been very, it's been, w e've been fairly aggressive, and we've gotten a good price on our share repurchases for the year. We, um, we got approval of $500 million back in March by the board for the next two years for share repurchases. So at least for 2025, our minimum for share repurchases that we plan on is at least half that number, which would require us to do about another $90 million in share repurchases in the final five months of the year. So when we allocate capital this, for the remainder of 2024, you'll see a portion of that go towards share repurchases and then any other opportunities that come up on the M&A side, you know, going forward. Got you. Thank you. As a reminder, to ask a question, you will need to press star one one on your telephone. One moment for your next question. The next question comes from the line of Dave Koning of Baird. Dave, please go ahead. Yeah. Hey, guys, nice quarter. And I guess my first question, new wins were really strong, new client wins in the quarter, I think the best I think we've ever seen, certainly a lot higher than many of the recent quarters. I guess, is that an indication in part that macro is getting a lot better? And maybe what are the size of those? Is the size also bigger? And what's the lag again? Like, when you win this quarter a lot, is that kind of really a 2025, um, impact, more so than the next six months? Yeah. Thanks, um, Dave. Um, so we're very pleased with the number of new client wins that we had in the second quarter, and also, if you saw, um, our first quarter, new client wins was,um, pretty healthy. So I think in the first half of the year, we've signed up, um, 39 new clients, 23 of them coming in the second quarter. I think what this is showing us is that the adoption of our business model and working with clients seems to be resonating nicely, and therefore, we are being able to widen the number of client relationships that we work with. We are also very happy about, the quality of these new clients that we are signing up, because some of these are very significant client relationships. And we expect to be able to do a very significant and meaningful amount of revenue with them. But as you correctly noted, most of this is going to be a revenue growth that takes place in 2025 and beyond. We get very little growth from new clients in the current, um, period. Um, keep in mind that we've had a good track record of signing up new clients in all of 2023 and 2024 as well, and some of the clients that we signed up in 2023, we are still in the process of ramping those up, um, right now and into the second half of 2024. So that should be adding on to our volume of business going forward. Gotcha. Thanks for that. And maybe as my follow-up, um, you guys don't do, you guys have very, very limited, like, restructuring type actions over time. You have super, super clean financials for many years. Um, annd this was pretty small too, the $6 million or so. Um, but maybe describe a little more, was this part of why employee growth was a little slower sequentially than normal? And maybe what are the savings gonna be around it? Or just maybe a little more data around it. Sure, Dave. So in the second quarter, we did have a restructuring and legal settlement, um, charge of $6.2 million. The restructuring piece was $4.8 million. Um, it involved about 450 employees that, that were affected by the restructuring, so less than 1% of the overall workforce. And it was really just to realign a small portion of our workforce, um, during the quarter. And so it did contribute, um, to a slower headcount growth number during the second quarter. We grew just slightly north of 800 employees during the quarter. And so they did contribute to that. But it was really just a one-time exercise in the second quarter, and we don't see that recurring at all, um, for the rest of the year. Gotcha. Thanks, guys. Nice job. One moment for your next question. The next question comes from the line of David Grossman of Stifel. David, please go ahead. Um, good morning. Thank you. I just wanted to follow up on, on two of the questions that were already asked. The first one was just, you know, Rohit, going back to, um, the backlog and the pipeline. You talked about the pipeline, at least for, um, data analytics being fairly strong and AI. I'm just curious on the ops, you know, digital ops side, what does the backlog look like year-over-year, and as well as the pipeline? And, um, where are we in terms of rolling out the 2023 wins, um, in 2024? Do you think that's gonna extend into 2025, or do you think most of those contracts will ramp in 2024? Sure, David. Um, so the backlog and the pipeline for us across the board, um, you know, continues to be pretty healthy. Um, it continues to be strong. We're not really seeing any, um, material change in that. I think for us, um, in terms of the implementation of deals that we've already won, um, we've only partially implemented the backlog that we had at the beginning of the year. We've got a tremendous amount of backlog that we still need to implement on in the second half of this year, and there are a number of, um, large client wins that we will be implementing in the second half of the year. The pipeline for us, um, you know, is basically strong across verticals, but, um, what I would say is, while the large deal pipeline within our overall pipeline, that ratio is about the same as what it's been previously. The place where we've seen obviously a tremendous amount of growth in the pipeline is the pipeline attributable to Gen AI, and that's increased in a pretty material way over the last 12 months. So we are encouraged by the quality of that pipeline and the, um, areas in which, um, clients want to partner with us. How should we think about the revenue conversion of a GenAI, GenAI deal? Is that fairly small and quick turn, or are those gonna be longer duration type, um, relationships? Yeah. So, I would say that what we are seeing is a, um, bipolar effect on the Gen AI part. In some cases, we are seeing Gen AI being embedded into the operations and into the workflow, and the client outsourcing the entire operation to us, along with the Gen AI implementation, and those tend to be the large size deals. And on the other side of the spectrum, they want us to implement Gen AI solutions into existing operations, which they might be running or some of our competitors might be running, and those tend to be, um, typically much smaller implementations as such. So, you know, we are seeing, um, you know deals at both ends of the spectrum that are there. Some which are bundled in with the operations, which tend to be large, and some which are, um, pure GenAI implementations, which tend to be much smaller in size. Just as a follow-up on your comments about your domain-specific model, um, you know, I think you mentioned that how that you're gonna monetize that is still a little bit up in the air. However, as you look beyond the near term, Rohit, how do you think a domain-specific model impacts your business longer term. You know, over time, the market has a tendency, at least, you know, the BPO market has a tendency to price in a lot of this, um, and they wanna recapture a lot of the benefit. The client wants to recapture a lot of the benefits. So is there something different here that would suggest that EXL can retain a larger piece of the economics as it relates to these models? Or do you think it follows a more traditional pattern? Yeah. So I think you're right. I think there'll always be a tussle between clients and service providers in terms of retaining economic value. But I think where we stand out is our focus and our expertise and our domain knowledge in select industry verticals. I think, um, in those areas where we have deep knowledge and we have deep access to data our ability to train these models and to be able to leverage these models will perhaps be a little bit better. And the networking effect of being able to see workflows across, um, you know multiple clients, I think that is very powerful when the use of GenAI is involved. So, I think that's what gives us, um, a little bit of an advantage and a little bit of a pricing power that can leverage the value that we can create out there. I see. Thanks. If I could just squeeze one more in. Maurizio, can you give us what, post all the share repurchases today, what the fully diluted share count should look like? So, David, so far, we have purchased right around 4.5-5 million shares overall. So if you deduct that from our overall share count going forward in 2025, you're gonna find that it's right around, you know, y ou can calculate what that reduction in the share count will be, but that's what we've done so far. You're talking about 4.5 versus where you were at the beginning of the year, then? No, you'd have to average that out for the year. You know, you're gonna get a much. It's when you do the diluted average shares for the year and you do your calculation, you're gonna have to weight that over the year. But, we've done that, you know, in the first seven months of the year. So you have to break that. You have to average that out over the first seven months and calculate, and recalculate that. So you're not gonna get that whole benefit this year. You'll get that next year. Right. Right. Okay, great, guys. Thanks very much. One moment for your last question. The last question comes from the line of Vincent Colicchio of Barrington Research. Vincent, please go ahead. Yes, Rohit. The ITI deal looks, um, quite like a value add. You haven't been very acquisitive for some time. Will we see more ITI-type deals, um, as a way to accelerate your positioning? Yes, Vincent. I think, um, we've been very clear that for us, we'd love to be able to grow our business organically and inorganically. And frankly, the amount of cash flow that we generate and the strength of our balance sheet allows us to be in a fortunate position of being able to acquire, assets. But we're gonna be very selective in terms of the strategic fit, the financial discipline, and the cultural fit of the assets, that we acquire. And, therefore, um, you know, we do think that there is, um, there's a lot of opportunity for us to be able to deploy capital, and integrate in assets. And, as things continue to evolve, um, and, um, you know, progress, I think we, you should be expecting to see us continue to be active in this area. How should we think about this NVIDIA partnership in terms of, um, you know, how long it will take to meaningfully benefit the company? I think it's a very strategic partnership, which, um, where we are gonna be making a tremendous amount of investment of, um, talent and resources, time and commitment, and building up capabilities, on the NVIDIA AI stack. We think, um, you know, their, um, software and their platform is actually highly differentiated and provides for much better, um, business outcomes. So as we deploy it and jointly go to market, I think, um, you're gonna see, um, us being able to kind of benefit from that and our clients being able to benefit from that. Traditionally, NVIDIA has been seen as a hardware company and as a gaming company, and their, um, you know, use of, um, their advanced computing capabilities into the workflow is something that we think we can be very, very additive on. And so, for us and for them, I think it's gonna be a very meaningful partnership. Thank you for answering my questions. Thank you. This concludes the question and answer session. I would now like to turn it back to John Kristoff. Okay, thank you, everyone, for joining our call today. As always, um, feel free to reach out directly to me with follow-up questions. I hope everyone has a great day. Thanks, and bye-bye.