Ladies and gentlemen, good day and welcome to HCLTech's Q1 FY 2027 Earnings Conference Call. As a reminder, all participant lines will be in the listen-only mode, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during this conference, please signal an operator by pressing star then zero on your touchtone phone. Please note that this conference is being recorded. I now hand the conference over to Mr. Nitin Mohta, Head, Investor Relations. Thank you. Over to you, sir. Thank you, Darwin. Good morning and good evening, everyone. A very warm welcome to HCLTech's quarter one FY 2027 Earnings Conference Call. We have with us Mr. C. Vijayakumar, CEO and Managing Director, HCLTech, Mr. Shiv Walia, Chief Financial Officer, along with the broader leadership team to discuss the performance of the company during the quarter, followed by a Q&A. In the course of this call, certain statements that will be made are forward-looking, which involve a number of risks, uncertainties, assumptions and other factors that could cause actual results to differ materially from those in such forward-looking statements. All forward-looking statements made herein are based upon information presently available to the management. The company does not undertake to update any forward-looking statements that may be made in the course of this call. In this regard, please do review the safe harbor statements in the formal investor release document and all the factors that can cause a difference. Over to you, CVK. Good evening, good afternoon and good morning, everyone. Thank you for joining our FY 2027 Q1 earnings call. We began FY 2027 with a focus to grow our advanced AI-led offerings, increase our relevance with clients, capitalize on the full range of AI-related market opportunities in our pursuit of becoming the world's best AI solutions provider. As mentioned previously, our intent is very clear. Benefit disproportionately from the AI native and AI amplified opportunities, which together represent the fastest growing pool of enterprise spend. While in AI disrupted services, we intend to innovate faster than the market to stay ahead of the deflationary curve rather than be defined by it. The fruition of this is reflected in our growing advanced AI revenue. Advanced AI revenue for the quarter stood at $172 million, marking 10.3% quarter-over-quarter and 62.1% year-on-year growth. Let me delve into the business performance for the quarter. AMJ is typically a weaker quarter for us due to planned revenue declines driven by productivity commitments in large managed services contracts. Despite this seasonality, we delivered a good all-round performance. Our revenue declined by 0.5% sequentially and increased by 2.6% on a year-on-year basis in constant currency. Our operating margin stood at 16.9%, an improvement of 39 basis points quarter-over-quarter and an increase of 56 basis points year-on-year. All growth rates referred to are in constant currency. Our services business grew 3.5% year-on-year and declined by 0.7% sequentially in constant currency. Our IT and business services grew 4.2% year-on-year and remained flat sequentially. Engineering and R&D services grew 0.3% year-on-year and declined 3.7% sequentially. HCLSoftware annual recurring revenue is now at $1.063 billion, a 2% increase year-on-year in constant currency. Revenue grew 2.2% sequentially, while declining 5.3% year-on-year. We have completed the acquisition of Jaspersoft. This adds the visualization layer to our data management portfolio. Just to recap, our data software product portfolio already covers the majority of the data value chains, like Data Connect for data integration and quality, Ingres, HCL Informix, Zen and Vector AI DB for storage, and data intelligence and observability for governance and AI analysts to engage and activate data. What was missing was the visualize layer. The capability that takes governed trusted data and delivers it as actionable insights to the business users who need it. From a bookings perspective, the quarter was good and the bookings was well balanced across vertical service lines and geographies. Our net new PCV booking for the quarter was $2.4 billion. Highest ever Q1 bookings. This excludes the recent mega deal that we announced, which was signed in early July and not in Q1. Let me give a brief overview of this landmark win. We've been selected by a Europe-headquartered Fortune Global 50 firm as a technology partner to accelerate AI-led transformation and management of their digital workplace and enterprise networks. We will leverage our AI Force platform, software-defined solutions and digital employee experience framework to implement an AI-first workplace and intelligent connectivity fabric, thus elevating employee experience and productivity for the company at a global scale. While there are several deals that added to this $2.4 billion, I want to talk about a marquee deal that showcases the depth of value we deliver to our clients. A Fortune 250 semiconductor equipment OEM selected HCLTech to accelerate AI-driven transformation across its semiconductor engineering and manufacturing value stream. HCLTech will deploy SAP-enabled design to manufacturing capabilities and integrate SAP with core PLM and MES systems, establishing an enterprise backbone for a future-ready, scalable, AI-led digital supply chain. On the people front, we have 223,889 people as of 30th June 2026, a decrease of 3,292 compared to the previous quarter. Our attrition stands at 12.7% on an LTM basis. Our AI strategy shows evident returns, as seen in a 3.3% year-over-year increase in revenue per employee, which has gone up every quarter for the last five quarters. Coming to our AI updates. As you know, our AI strategy is anchored on five strategic pillars designed to drive client impact, accelerate innovation, and strengthen our leadership position in the AI market. I'm pleased to share the progress we made across each of them this quarter. Our first pillar of the strategy is proactive transformation of our services. We continue to embed AI deeply in our service delivery model, helping clients unlock measurable efficiencies and accelerate business outcomes. AI Force is now deployed across 92 distinct client accounts, enabling organizations to realize the benefits of AI within existing engagements at scale. A good example to the progress we are making in this area, a Europe-based global automotive manufacturer selected HCLTech for a large-scale AI-led site reliability engineering transformation program across engineering, production, commercial, and corporate application landscapes. Powered by AI Force, the program brings together SRE, AIOps, agentic AI, observability, automation, and application lifecycle transformation within a unified operating model. Coming to the second strategic pillar of building differentiated IP. Differentiated IP remains a cornerstone of our AI strategy, enabling clients to move from experimentation to enterprise-scale value realization. AI Force continued its evolution with 2.2 release, introducing capabilities such as VS Code IDE plugin support, multimodal AI, long-term memory, configurable governance guardrails, AWS native integration, and enhanced observability. We also rolled out an agent store, an organization-wide validated set of AI assets, including agents, AI Force use cases, workflows, tools, and connectors. The Next Ways enables reuse of AI assets across the organization to innovate faster and better to develop more AI IP. We also launched AI Force for Oracle, combining Oracle Fusion Agent Studio with HCLTech's domain-aligned agents, accelerators, and governance framework to accelerate enterprise adoption. In industry AI solutions, our intelligent regulatory platform solution achieved general availability, while VisionX was named as the finalist at the AI Awards U.K. in both the best AI product and AI-powered quality assurance categories. We also launched three new industry AI solutions, namely AI for store operations, order-to-cash platform, and intelligent validation and quality platform. We now have 23 industry AI solutions. Our industry AI solution, VoiceOps AI, designed for media platforms and entertainment vertical and telecom scale environments, received the Product of the Year award at NAB Show 2026 in the Intelligent Technology category, recognizing its ability to transform voice-led service operations and customer engagement. Coming to the third pillar, expanding AI-led services. We continue to broaden our portfolio of AI-led services, helping clients address emerging opportunities. In AI Labs, we hit a major milestone in Q1, crossing 1,000-plus AI engagements delivered. Within AI Factory, we announced a strategic collaboration with Red Hat to accelerate the deployment of enterprise-grade AI infrastructure through the AI Factory ecosystem. A global technology major expanded its partnership with HCLTech for an AI Factory program with an incremental scope of over INR 180 million for AI data center build-out. HCLTech solutions will fast-track the deployment of a large-scale infrastructure environment that leverages the latest GPU technologies to train large language models and advance AI-driven products. In Physical AI, a Europe-based manufacturer selected HCLTech to engineer the navigation stack for its next-generation autonomous robot. HCLTech will apply its Physical AI and intelligent product engineering capabilities to deliver core navigation logic, motion planning, and system integration for the product. In another deal, our AI engineering capabilities will translate chip specifications into implementable silicon, supporting the delivery of a secure hardware module that meets the stringent security standards for an Indian research organization. They selected HCLTech to support the development of a secure chip aligned to trusted computing requirements. This quarter, we also made a significant progress in building our sovereign AI-as-a-service capabilities. Sovereign is not just governments. It is for enterprises as well. Enterprises are realizing that their data, their know-how that gives them their competitive edge are their most valuable assets. They don't want the value disappearing into someone else's models. The evolving enterprise AI architecture is based on two broad principles. One is zero trust. That is, the default posture is that no data, no prompt or context ever leaves the enterprise boundary. The second principle is a tiered approach, where Tier 1 is private, on-prem, or VPC-hosted SLMs, fine-tuned on the enterprise data. Tier 2 is frontier models accessed through a policy enforcing, inferencing gateway that handles reduction, logging, and cost economics. The gateway becomes the primary policy enforcement point, which sits within the enterprise. The demand is moving towards solutions that can enable clients to have complete sovereign assurance with custom models and controls, rather than just renting the models from the big providers. Coming to the fourth leg of our strategy, scaling AI partnerships across the technology stack. Our partner ecosystem remains a powerful force multiplier, accelerating innovation and helping us deliver best-in-class AI solutions. Most notable is our recent strategic investment of $150 million in Sarvam, India's full-stack sovereign AI company. This reinforces HCLTech's position as an AI innovator, not just an adapter, underscoring our commitment to building, co-innovating, and shaping the next wave of AI. By combining Sarvam's research depth in multilingual India-focused AI models with HCLTech's global enterprise relationships, engineering expertise, and software IP, we are creating a differentiated full-stack AI platform for governments and enterprises, spanning models, platforms, applications, and managed services. This meaningfully opens up the Indian sovereign AI market for us across industries and the government sector. This is clearly an early-stage market opportunity to build industry and client-specific SLMs. While the world's attention has been captured by ever larger general-purpose models, the real value for enterprise often lies in smaller, specialized models trained deeply on the language, data, and workflow of a single industry or a client. These models are faster, more cost-efficient, and more accurate where it matters. The window to establish leadership here is open now. This quarter, we made significant progress with other partners. Mentioning a few, we expanded our strategic relationship with Google Cloud through the creation of a dedicated Gemini Enterprise Business Unit and launch of an autonomous finance platform that transforms core finance and accounting operations using Gemini Enterprise. We inaugurated AI innovation zones with Google Cloud and Intel at Santa Clara and Chennai, respectively, providing clients with immersive environments to explore, build, and scale AI solutions. HCLTech was added to OpenAI's Trusted Access for Cyber program, providing authorized teams access to advanced cyber-focused AI capabilities. In AWS, we achieved AI services competency, marking a significant milestone in our AI journey with AWS ecosystem. We also strengthened our modernization proposition by integrating HCLTech composable agents into AWS Transform agentic AI service, accelerating the transformation for mainframe modernization and VMware migration. Our ecosystem momentum was further recognized through prestigious industry awards, including Dell Technologies 2026, Global Alliance Americas Partner of the Year, HPE Storage Partner of the Year 2026, and more. We expanded our partnership with MetLife Stadium, the venue for FIFA 2026 World Cup Final, the New York Jets, and New York Giants as their official AI partner. We will leverage our AI capabilities to create intelligent, scalable solutions that enhance customer experiences and support smarter, safer, and more connected environments for the clients. On the fifth pillar of developing AI talent at scale, AI talent foundation remains critical to sustaining long-term growth and client success. In Q1, around 24,000 unique employees across the organization participated in AI and GenAI learning journeys tailored to different proficiency levels and roles. These roles are primarily categorized as users, super users, and AI builders. In parallel, focused capability building initiatives are being pursued in areas such as physical AI, SLM builder role, partner platforms, and hyperscaler technologies. Additionally, 200-plus employees were Black Belt certified during the quarter and are actively contributing to solutioning, ideation into and realization of AI use cases. The examples include transformation of global IT operations for a client's global IT through an AI-led hyperautomation ecosystem by pioneering agentic AI, AIOps, and intelligent incident management capabilities across a complex global infrastructure landscape. In another case, we enabled a client to move from fragmented GenAI pilots to an enterprise-scale automation strategy, delivering 40% productivity improvement while embedding AI into the core service delivery and commercial operating mode. Our AI strategy continues to be recognized well by leading analysts, industry bodies, and technology partners. While we have several recognitions this quarter, as detailed in our investor release, the one that stands out is HCLTech was named as a market shaper in Gartner's inaugural Physical AI Services assessment, becoming the only India heritage services company positioned in the top quadrant. Taken together, these demonstrate our continued strength of our AI strategy, the momentum of our innovation engine, and the trust clients place in us as they transform their businesses for an AI-first future. I would also like to share an important strategic initiative for HCLTech, where we are entering the AI data center business. Global data center demand is set to triple by 2030, with AI driving roughly 70% of that growth. In India, that growth is expected to happen at an even faster pace. India, given its scale, is one of the most supply-constrained data center markets globally, and sovereign data requirements are increasingly mandating that workloads for government enterprises and even global consumer platforms be delivered in-country. The convergence of AI-led demand, supply constraints, and sovereignty needs represent a very compelling opportunity. This is a business which is shifting from physical infrastructure to higher value AI-ready solutions. One we believe will be a new growth vector for HCLTech. We will create full-stack offerings by combining our capabilities across AI data center design, DevOps, and cloud operations, as well as a software portfolio with our new data center business. The biggest opportunity is not to rent AI, but to own the full stack. The data centers that compute the models built to address client-specific needs. As demand grows and supply catches up, the players who win will be the ones who will offer full-stack offerings. In this regard, we will make a strategic investment of up to INR 3,500 crores and with the potential to scale to 50 MW of capacity. This would also position us as a key enabler of India's sovereign AI ecosystem, expanding our presence in the fastest-growing market among largest economies with differentiated offerings around sovereign cloud, secure AI, and managed AI infrastructure. We are in advanced discussions with clients to ensure we start with certain level of committed consumption from day one. We would also like to highlight that we will consume some of the capacity internally as we build them into our managed services and outcome-based contracts for our global clients. Before I talk about the pipeline and market trends, I would like to take a moment to highlight our execution track record on mega deals. Over the last several years, you would notice there are areas where we are undisputed leaders and where we command execution premium, especially in mega deals. We also have a strong track record of executing mega deals with excellent client satisfaction and to the planned business case. This is also reflected in our renewals of our highest client categories. This is an important angle where we see large deals as a growth vector and our risk management framework and execution rigor ensures we don't compromise on margins. Our strategy continues to be to deliver superior growth at stable margins. As you would see, our margins have been stable over the years, including FY 2026, with the exclusion of restructuring costs. Coming to pipeline and market trends, our pipeline remains healthy. Looking at the broader market trends, we are seeing a clear divergence across different segments of the AI landscape. On one side, we are seeing strong, sustained growth both in AI native and AI amplified services. On the other side, AI disrupted services. The more traditional commoditized work continues to be optimized further as AI-enabled automation takes hold. Overall, we believe strong executors would gain a lot, but by changing their business mix more as AI-native and AI-amplified services. Looking ahead, we are retaining our guidance of 1%-4% and margin guidance of 17.5%-18.5% for FY 2027. The guidance is organic growth guidance and does not include acquisitions, including Jaspersoft. I would request Shiv to share more details on the numbers. Thank you, CVK. Good morning, good afternoon, and good evening to all of you. Thank you for joining our Q1 financial year 2027 earnings call. Let me walk you through our financial performance for the quarter. Starting with the revenue performance. Please note that all the growth numbers quoted are in constant currency, unless noted otherwise. Total revenue for the quarter is $3,650 million, a decline of 0.5% quarter-on-quarter and growth of 2.6% year-on-year. Services revenue for the quarter came in at $3,351 million, a decline of 0.7% quarter-on-quarter and growth of 3.5% year-on-year. Our ITBS services is flat quarter-on-quarter and grew 4.2% year-on-year. The ERS segment declined 3.7% quarter-on-quarter and grew 0.3% year-on-year. HCLSoftware revenue for the quarter is $330 million, representing growth of 2.2% quarter-on-quarter and decline of 5.3% year-on-year. In terms of geographies, during the quarter, the U.S.A. grew 2.9% year-on-year, Europe grew 0.1%, rest of the world grew 10.8%, and India grew 16.9%. Moving on to vertical. Our Q1 growth was broad-based, with six out of seven verticals registering year-on-year growth. Growth was led by public services and retail and CPG, which grew 12% and 10.1% year-on-year respectively. In terms of clients, our continued focus on deepening customer relationship has helped us expand the number of large client relationships. On a year-on-year basis, we added one client in the $100 million plus category, six clients in the $50 million plus category, 11 clients in the $20 million plus category, and 31 clients in the $10 million plus category. In terms of profitability, our EBIT is at $616 million, representing 16.9% of revenue. Adjusting for restructuring expenses of 62 basis points during the quarter, our Q1 EBIT margins are 17.5% compared with 17.7% in the previous quarter. Net income for the quarter is $488 million, representing 13.4% of revenue. In terms of EBIT margin walk, the margin bridge explaining the sequential margin movement is as follows. The reported EBIT margin increased by 39 basis points quarter-on-quarter from 16.5% in JFM 2026 to 16.9% in AMJ 2026. Lower restructuring expenses gave us 70 basis points and benefit on P&D gave us 20 basis points. This tailwind was offset by 110 basis points headwind from the seasonality due to annual productivity benefit and decline in ERS revenue. Forex gave us benefit of 60 basis points in the quarter. Now moving on to the return on invested capital, ROIC. Our ROIC continues to remain strong, supported by our ongoing focus on profitability and efficient capital management. The last 12 months ROIC is at 40.7% for the company, up 257 basis points year-on-year. Services ROIC is at 47.8%, up 260 basis points year-on-year. HCLSoftware is at 21.6%, which is up 75 basis points year-on-year. In terms of cash generation, over the last 12 months, free cash flow is at $1.98 billion, while operating cash flow is at $2.14 billion. Free cash flow to net income is 99%, and operating cash flow to net income is at 107%. Our balance sheet remains strong with gross cash of $2.86 billion and net cash of $2.84 billion as on 30th June 2026. In terms of DSO, our total DSO, including unbilled receivables, is at 86 days, representing an increase of two days quarter-on-quarter. In terms of EPS and dividend for our shareholders, normalized diluted EPS for the last 12 months came in at INR 66.9, representing a growth of 4.5% quarter-on-quarter and 6.9% year-on-year. Including the one-time impact of the New Labour Codes, diluted EPS was INR 64.25. The board has declared an interim dividend of INR 12 per share for the quarter. The record date is 17th of July 2026, and the payment date shall be 27th of July 2026. This brings our last 12 months payout to INR 60 per share, effectively distributing 93.2% of our net income. That is all from my side for now, and I would like to hand over the session to our moderator for the Q&A session. Thank you. Thank you very much. We will now begin the question- and- answer session. Anyone who wishes to ask a question may press star and one on their touchtone telephone. If you wish to withdraw yourself from the question queue, you may press star and two. Participants are requested to please use handsets while asking a question. Ladies and gentlemen, we will now wait for a moment while the question queue assembles. Our first question comes from the line of Abhishek Bhandari with Nomura. Please go ahead. Yeah. Thank you for the opportunity. CVK, congrats on the good deal wins. I have two questions. First is on your guidance. This quarter we had $2.4 billion deal wins, which in the press conference you said is highest ever for any Q1. Along with that, we also had a mega deal announced in the first week of July. What are the various moving parts which is restricting you from increasing the guidance from here? I'll come back with the second question after this. Yeah. Yes, we are happy to report a very strong booking. As you know, our guidance band is a little broader, and this is only the first quarter, we would like to see how things pan out in the next quarter. On the mega deal win, the transition is expected to start in a couple of months, and the steady state is expected to be reached only in April of 2027. Which is coming in the next financial year. It will have negligible impact to our revenue in this financial year. That's really what it is, Abhishek. Got it. Thanks, CVK. My second and last question is on the investment in the data center. If you can share more details around it, what are the upper limits or the periods of investment in this particular avenue? If I look at it works out to almost $7 million per megawatt, which is kind of the cost for a colo data center, not an AI data center. I'm a little confused, what makes you say it's a AI data center? Are there any increasing commitments on the investments once you get past the INR 3,500 crores? Our 50 MW is a long-term plan. The INR 3,500 crores is actually representing only a fraction of that capacity, and that is the initial investment that should get us started. We will have a very disciplined approach to increasing investments based on the free cash flow that is getting generated from the business. This is an initial investment that should get us started. This is not a colo business. This is going to be a full stack play. There are potential possibilities of funding this through a mix of partners, arrangements with silicon and OEM vendors, and committed capacity from clients, and consumption models where the hardware is financed against contracted demand. Even this could be funded through a mix of equity and debt. We are not putting this entire investment in the balance sheet in a single year. We are not funding it at the expense of our stated payout policy. We will provide more details as we progress. You should not correlate and calculate INR 3,500 crores for 50 MW. 50 MW is a long-term plan, and this investment is for a much smaller capacity, which will be an end-to-end stack. Got it. Thank you, CVK, and all the best. Thank you, Abhishek. Thank you. Our next question comes from the line of Abhishek Pathak with Motilal Oswal. Please go ahead. Yeah. Hi. Am I audible? Yes, you are audible. Yeah. Hi, team. Hi, CVK. A fantastic quarter. I had a couple of questions. Firstly, how do you view token costs in context of AI adoption? If they had not been so high, do you think our AI services revenue would have been higher? Over a two to three-year perspective, how does your team look at token costs? Do you guys expect token costs to collapse, which leads to massive AI implementation revenues, or do you expect them to be elevated, which slows down AI displacement and hence leads to better defense for IT services? That's the first question on AI. Maybe I'll just follow up with the second one after this. Yeah. Token costs. If you see about three months ago or six months ago, token cost was not a topic. It is only when enterprises started scaling the adoption of AI, the whole various dimensions of token costs came into play. Now, as the token consumption cost, it really depends on the exact models that you are implementing. Customers are looking at creative ways to reduce their overall token costs. That is where the tiered approach is becoming the most popular enterprise AI architecture, both for data sovereignty for the enterprises, and for the right price performance. Token costs could drop, but however, the overall consumption of tokens will go up, total cost will also go up. You need to build a more economic model, which is where our strategy of building a tiered approach with smaller models within the enterprise, which can be trained on the enterprise data, also zero-trust architecture with a policy enforcement gateway, which ensures that no data or prompts or context leaves the enterprise. That is the model which is becoming prevalent, this will have some very meaningful services revenue opportunity. In every client, training SLMs requires a lot of data work, also training can also be quite intensive in terms of research requirements and all of that. We think it will be like another engineering services wave that we can create by really pursuing our strategy on a hybrid AI stack. Understood. In that context then, it was interesting when you mentioned that Sarvam AI is something that you are looking at from the Indian market standpoint. Is it possible to take Sarvam's low-cost models maybe to global clients as well, are you in discussions about that, too? The last question was to Shiv on margins. Do we expect to get back to our original 18%-19% sort of margin band anytime soon, maybe in FY 2028, or do we expect the AI investments to continue kind of hold back our margins a bit going forward in the medium- term as well? Thank you. Yeah. Abhishek, as you rightly mentioned, apart from what we can do in the Indian enterprises and public sector and government, there is an opportunity with the global enterprises. We have talked about the tiered approach and SLMs model, it is generating a lot of interest. Sarvam is a very good option, where we have a lot more stronger partnership and our ability to really build the entire training infrastructure, training the small language models on enterprise data, some of the research capabilities. All that comes in very handy as we build it. The model dependency itself need not be Sarvam, there are other options as well. I think our closer strategic partnership helps us drive this with a stronger execution. Abhishek, on the margin front, if you remember last year, if you take out the impact of restructuring costs, then our margins were closer to 18%. This year, the guidance is 17.5%-18.5%, and that also includes approximately 40-50 basis point restructuring cost impact. As regard maybe the longer- term, the medium-term horizon of around FY 2028, we will give that guidance at an appropriate time when we give guidance for 2028 next year. At this stage now time, I would just like to focus on this year's margin guidance, which is 17.5%-18.5%. Thank you. Thank you so much, and all the best. Thank you. Our next question comes from the line of Ravi Menon with Axis Capital. Please go ahead. Thank you for the opportunity. Really good performance in the IT and business services, considering both the seasonality and the headwinds in the two telecom customers and I think the SAP program ramp down as well that you had called out last quarter. ER&D decline was a surprise. Which segment was within, and is there any further decline anticipated in the ER&D in the coming quarters? Yeah. The decline in the ER&D was in tech and telecom, media, and entertainment verticals. We did call out that we had some sharp cuts in discretionary spending in two large U.S. telcos. We did say that it will have an impact in the subsequent quarters, and that is what is playing out. We've had a very strong momentum in the tech vertical for last many quarters. Some of this is on the very high base. That's really what it is. Really, what's prompted a rethink on the AI data center investment? Is it because you're seeing more customers now wanting to probably run open weight models and control the hardware where the data resides? Yeah. Absolutely. The closed models have their own significant limitations. Clients are looking at open models, both open weight and open source models. In data center, our play is a fundamentally different strategy because large gigawatt announcements are more capacity plays and they're infrastructure companies where the product is megawatt. For us, megawatt isn't the product, it is just the anchor. Our value is in full stack of AI, high margin services, which we wrap around that capacity. More importantly, it would be deploying efficient SLM-led models, as you did call out, to address industry and vertical needs. 50 MW is good capacity to build a large business if you want to do small language models and not frontier models. This will generate far more enterprise value per megawatt than raw hyperscale capacity, because we monetize the entire solution, not just space and power. This capacity is also going to help us to drive more and more outcome-based contracts and managed services contracts, where we can consume some of this capacity, which gets bundled into our outcome-based pricing and managed services pricing for global clients. I think these two were very important kind of dimensions which made this business very lucrative. Thanks. One last question. As your revenue per employee increases, do you also expect gross margins to expand? Yes, of course. From last year to this year, our guidance is improving gross margins. I think if our strategy works out as we have planned, we do expect the gross margin per employee to increase. However, we will continue to invest because the business is in a significant inflection point and transformation, we will not hesitate making the right investments. While, of course, continuing to demand and get greater value from our clients. Thanks so much. Best of luck. Thank you. Thank you. Our next question comes from the line of Sudheer Guntupalli with Kotak Mahindra Asset Management Company. Please go ahead. Hi, CVK. Thanks for the opportunity. Just a couple of questions. Sudheer, sorry to interrupt, your line is not very clear. I request you to please check the handset mode. Yeah. Hi, CVK. Thanks for the opportunity. Just a couple of questions. General understanding in market is that 1 GW of capacity will cost roughly $60 billion-$80 billion, if we were to provide AI data centers on a full stack mode. So 50 MW capacity should require nearly INR 30,000 crore of overall investment, even if that is spread over multiple years. Is that a fair assessment, or since we are targeting this to more of training SLMs, will the economics be any different? I think your economics at a high level is correct. We did not say that this INR 3,500 crore is for 50 MW. Our overall vision is to drive a business of 50 MW. We are starting with the INR 3,500 crore, which would be a fraction of that capacity. We do not see us investing so much capital into this business. We believe there are funding opportunities through a mix of partners coming in with silicon companies and OEM vendors and committed capacity, also GPUs based on committed contracts, all of that. Some amount of equity and debt combination. We do not expect this to be anywhere near, let us say, INR 30,000 crore kind of investment. Our plan is to invest about INR 3,500 crore and how the business economics works out, then start investing based on free cash flows from the business. Okay. The second question is, there is almost 100 GW of announced data center investments in the pipeline. Recently some of the companies like SpaceX and Meta, they decided to sell or lease their compute. In the backdrop, the growing perception is that compute may not be as scarce as it is made out to be, or maybe we are at the far end of compute-related bottlenecks. By the time our proposed 50 MW capacity becomes fully operational, if the compute demand cycle were to turn for whatsoever reasons, how do you think of the tenancy ratios here and ROIC of the proposed investment? Yeah. I think even now, the market is heavily GPU-starved. There is no ambiguity at all. The reason some of the big companies are renting out GPU capacity is it is very lucrative to rent out GPU capacity. That is possibly one reason. 50 MW is a very small fraction of the total capacity that is needed. This capacity will just get consumed very quickly, including some of the commitments that we have for the initial investment. The next level of investments are going to be based on how we deliver on the initial investments. Okay, sir. Thanks, all the very best. Thank you. Our next question comes from the line of Gaurav Rateria with Morgan Stanley. Please go ahead. Hi. Thank you for taking my questions. I have actually three questions. Let me just lay down that all, and then you can answer based on your comfort on order of preference. My first question is on your strategy around the data center. If we compare the current cycle to the cloud and digital cycle, at that time, as services company, we did not require to build the required infrastructure to support the rollout of our services. We did not have to build a cloud. We had to partner with the right hyperscalers. This time it looks like we have to build out the required infrastructure to be able to roll out the small language model and other capabilities. I'm just trying to understand how is this cycle different from the one that we saw in the cloud and digital side of things. The second question is on your near-term visibility and guidance. My understanding is that this quarter has turned out to be probably slightly better than what we're expecting because our year-on-year growth in services business is ahead of our midpoint of the guide. We are maintaining our guide. It kind of shows some deceleration in the year-on-year trajectory for services business over the coming quarter. Is the outlook incrementally sort of become a little bit tougher than what we saw at the start of the quarter? The last question is on the margins. Our current margin guidance, does it take into account incremental impact from the amortization-related expense that will come because of the M&A? Thank you so much. On the data center strategy and its comparison to the cloud and digital cycle, I think there is a big reversal of how this is playing out because private AI stack is going to be the answer for a lot of enterprise needs. Of course, frontier models will be required, but you use frontier models very selectively. Under this consideration, you have an option to create VPNs with cloud providers. I think, given the data sensitivity and all of this, it's a much better solution for clients. Its price performance is very attractive for an SLM-based solution. I think this cycle is looking different based on the entire analysis of the current situation. On the near-term visibility, guidance on services and all that, I think we're happy that we have done a little better than what we expected. The macro environment and some of the deal client-specific challenges that I talked about in the beginning of the quarter, last quarter, some of them will play out in the subsequent quarters, which was also as planned. Right now, whatever macro-related situation, what we saw in March, which continues to be the same today. We are not able to visualize anything different. We are continuing with the guidance, but obviously after Q2, we will come back to you with any further directional change. Gaurav, on the margins guidelines, as you called out, our guide revenue as well as margin guidance are for the organic business. On top of that, we'll have the revenue and the margin impact of the acquisitions, which we are going to do of Jaspersoft and maybe later this quarter, the other one. That is outside the impact of those acquisitions. Thank you. All the best. Thank you. Thank you. Our next question comes from the line of Vibhor Singhal with Nuvama Equities. Please go ahead. Yeah. Hi. Thanks for taking my question. Congrats, team, for the solid dealings and a great performance in the beginning of the year itself. CVK, just two questions from my side, I have just one small follow-up as well. In terms of verticals, I think you explained the weakness in telecom and high tech, which was kind of expected, and that is kind of leading us down. Our BFSI growth has been quite strong for past, I think, more than almost 10 quarters. How are the clients looking at the spends in the BFSI segment in terms of their AI strategy? Earlier, we had seen a lot of insourcing happening there, but are the clients kind of opening up to a more third-party outsourcing there, That is what is kind of leading us to the kind of growth that we are seeing in this vertical? Secondly, on the healthcare vertical, we've fallen off a bit from, let's say, the run rate that we used to have, almost INR 500 million. It's been a continuous kind of a, not a very sharp one, but a kind of a gradual decline over the past eight, nine quarters. What's ailing that sector, Do you see any turnaround in the sector in the coming quarters? I'll just have a small follow-up for Shiv. Yeah. Thank you, Vibhor. Financial services, as you rightly called out, we've had solid momentum over the last maybe 12 quarters, Even the year-on-year growth is the highest in the industry. It's been driven by our AI-native approach to a lot of large clients. We also have been more proactive about AI adoption. We have Significant wallet share in our top two customers in financial services. That's number one. The second thing is we are seeing a very broad-based traction in the data and analytics space. A lot of it is preparatory work towards building enterprise AI stack. I think that has been a big tailwind, at least in the recent quarters. I think these are the two things. Yeah life sciences and healthcare vertical, of course, we had a good mix of engineering services as well in life sciences and healthcare. We had a strong traction due to certain regulatory work, which was required to be done for a lot of medical devices companies, which was one of the key contributor to strong growth in life sciences business three years ago. Those regulatory work came to an end, and that did not get refilled with something else. That was one reason. The second reason is the healthcare segment itself is heavily stressed in the U.S., Most of our healthcare revenue comes from the U.S., that has been also a cause. I think these are the two reasons. Otherwise, we continue to win regular business and execute well, but there has been some headwinds, which we are facing. Got it. Thanks, Vijay, for that detailed explanation. Just one quick bookkeeping question for Shiv. Shiv, the Jasper acquisition got completed in the first week of July. While it is not included in our guidance, it will still contribute to the revenues from Q2 onwards. Am I right on that? That's correct. Any indication as to how much could be the contribution from the Jasper acquisition to our full-year revenue in FY 2027 or a recurring contribution that we could have on an annualized basis? We're still working on it. Vibhor, I think will possibly, maybe, I would say, $10 million-$15 million per quarter in that range. There is seasonality involved, it's going to be that range, I think. Okay. $10 million-$15 million per quarter. Yeah. Lastly, the CTG acquisition is yet to be closed, right? That is not yet closed. We expect that to be closed maybe later part of this quarter. Yes, I think that's also on the card. Hopefully, this quarter only. We don't know the exact details, maybe towards the later part of this quarter, that will also get closed. Got it. Great. Thank you so much for taking my questions, and wish you all the best. Thank you. Thank you. Ladies and gentlemen, we will take that as our last question for today. I would now like to hand the conference over to Mr. C. Vijayakumar, CEO and MD, for closing comments. Over to you, sir. Yeah. Thank you, everyone, for joining us today. We are very happy that we've started the year on a good note, despite a seasonally weak Q1. We are also very encouraged by our bookings and also the potential bookings in Q2. We have a strong pipeline, and we continue to evolve very strongly as an AI-native and AI-amplified services player. We look forward to your continued support as we evolve into the best AI solutions provider. Thank you, and have a good evening. Thank you. On behalf of HCLTech, that concludes this conference. Thank you all for joining us. You may now disconnect your line.