Good afternoon, everyone, and welcome to Genpact's 2025 Investor Day. I'm Krista Bessinger, the Head of Investor Relations, and I want to thank you all for joining us. Today is an important day for Genpact. As you can see on the agenda, you're going to hear directly from BK, Mike, and the rest of the leadership team about the transformational work that's underway and the clear financial and strategic roadmap that we're executing against. Before we begin, just a few items to note. First, to submit questions remotely, please email us at investor.day@genpact.com. Second, today's remarks will include forward-looking statements. As always, these are subject to risks and uncertainties, as described in our filings with the SEC and in the materials on our Investor Relations website. Third, we'll reference non-GAAP financial measures, and reconciliations to the most directly comparable GAAP financial measures are available in the materials on our Investor Relations website as well. Finally, a reminder that today's event is being webcast, and a replay and presentation materials will be available on our website shortly after the event concludes. With that, I would love to hand it over to our CEO, BK Kalra, to share his perspective on how Genpact is executing against the opportunity ahead. Thank you, Krista. Thank you. Really appreciate that. Thank you, Krista, and welcome everybody in the room and on the webcast on Genpact's Investor Day 2025. Before we dive in, I want to take a moment to reflect on Genpact's extraordinary journey, one I have had the privilege of helping guide since our spin-out from GE, when we shaped the BPO industry. We did not just participate in the formation of the category, we defined it and later scaled it. Today, as third CEO in our history, I believe we stand at another defining moment. My mandate and my passion is to lead Genpact into its next chapter, to pivot and grow as an AI-first, data-led innovation company. This transformation is already underway. Three powerful engines are fueling this next chapter. First, our growth model, built for relevance and resilience, is helping us proactively manage the transition to artificial intelligence. Core elements of our growth model include capabilities, clients, and catalysts. Second, our world-class team, with the mindset and skills needed to shape what's next. These are a few of the key leaders building the future of Genpact. They will be on stage and at the networking event later today. Most importantly, our enduring client relationships with some of the world's most iconic companies. We are proud to partner with more than 125 Fortune 500 companies. Of these larger clients, many have been with Genpact for over a decade. Today, you will hear directly from a few of them. These engines of growth, these powerful forces, are fueling our pivot. We are building a fundamentally new company at Genpact and defining what it means to be an AI-first company powered by process and industry-domain expertise that delivers impact at scale, fundamentally a new company. To better understand our pivot to AI, it's important to first revisit the foundation that we are building on. Over 25 years ago, we were GE's global capability center, and our mission was to perfect, and I mean perfect, a set of shared business processes using Lean Six Sigma and other rigorous methodologies. The work was highly detailed, operationally complex, and it built our fundamental DNA as a business process expert. We were called process geeks, data geeks, including myself, and we went through tough, Lean Six Sigma Black Belt certifications. The discipline around process, around data, around continuous improvement, around industry domains shaped how we think, how we challenge, and how we build. As we scaled, that mindset remained at the center of who we are, and it defined our culture. The end-to-end view of the processes, the ability to benchmark using this granular data, and our operator-led approach together form what we call process intelligence. It is this foundation of what positions us to lead in the world of artificial intelligence. I often say this: there is no artificial intelligence without process intelligence. This deserves a second breath because it is the essence of our journey. There is no artificial intelligence without process intelligence. It is not just a sound bite. It is what we experience every single day. This is a critical point because Genpact's depth in business processes and industry domains is not just essential. It is not just valuable; it is super essential today. Why? Because technology alone does not create business value. To truly move the needle, you need to understand how businesses run, the workflow, the data, the friction points, the bottlenecks. You need deep process expertise and understanding of data and domain insights to unlock real outcomes with AI. That is where Genpact's strength lies. That turns potential into performance. Our pivot to AI and agentic solutions presents an exciting opportunity for Genpact. According to Gartner, by 2030, more than 50% of GenAI models will be domain-specific, tailored to an industry or a business function, up from approximately 5% last year. GenAI solutions must go beyond generic applications to deliver targeted domain-specific value that addresses unique challenges within each industry and function. Our extensive industry domain positions us as an ideal partner for developing domain-specific and contextually relevant GenAI models. We operate in a large, under-penetrated, and growing market. Genpact's unique history positions us to capture this opportunity. Our total addressable market is over $1 trillion and growing. Within the areas we choose to play, our clients consistently recognize us as one of the top two partners they trust to deliver real impact. As we accelerate our growth, we are expanding into new markets with AI-led solutions and overall agentic solutions, unlocking opportunities that did not exist just a few years ago. This is our chance not just to scale, but to lead and shape the next wave of value creation for our clients. Looking back at our last Investor Day, we committed to deliver 10% top-line growth and shared medium-term targets across key metrics. While we delivered on all other metrics, we fell short on revenue. We recognize it, and we do not take it lightly. Therefore, to help focus and rebuild our momentum, we built our 3+1 execution framework at the beginning of 2024. 3+1 focused Genpact on partnerships, data tech AI simplification, and our plus one, which is leading with Genpact as our own best credential for AI-led transformation, and we call it Client Zero. Client Zero also provides us a front-row view of what it takes to adopt and scale AI. While every company aspires to be an AI-first company, it's much harder to do than to say. Companies face a common set of challenges in adopting and scaling and delivering meaningful value from their AI investments. There are many common pain points. Data is fragmented, not curated for AI. Business and technology teams are not fully integrated. Systems that are not orchestrated to work together. Scalable AI-ready talent is in short supply. We have designed a new set of solutions to solve these business problems head-on, bringing together the capabilities, orchestration, and last-mile domain understanding required to unlock real value from AI. I will talk more about that. Our clients know us for our domain expertise and process excellence, which has established our reputation as last-mile experts. Now, as we thoughtfully invest in advanced technologies, we are not just adding capabilities. We are amplifying what already sets us apart. It is early days, but we are seeing clear momentum. Our technology investments are accelerating the impact of our domain strength, Lean Six Sigma foundation, creating a flywheel that compounds over time. This elevates last-mile execution to new levels and helps us deliver sharper, faster, and more scalable outcomes for our clients. It is a distinctive position where deep operational know-how meets innovation. It is enabling us to drive real-world business value like never before. There's some surprise for you. We have already spoken about our 3+1 execution framework, which helps strengthen our foundation and rebuild momentum, but it also laid groundwork for our next phase. Today, we are bringing together a full set of Genpact strength: the process and industry expertise, rich operational data with context, and our ability to manage last-mile exceptions for our clients. We are adding a force multiplier. That force multiplier is advanced technologies. Therefore, our strategy is simple yet powerful: integrate advanced technologies, especially AI, and supercharge what we have done best: process, domain, operational data. That is simply our strategy. This strengthens our differentiation and deepens client trust as we take on greater accountability for delivering real business outcomes. As we integrate advanced technologies, we remove friction, address inefficiencies at the point of execution, and deliver targeted, scalable interventions that drive real impact. To reflect this progress, we are evolving from our 3+1 execution framework to what we call Genpact Next, a strategy centered on our new growth model designed to scale value for our clients and for us. Genpact Next is focused on innovation and growth. Genpact Next is designed to establish Genpact as a global leader in advanced technology solutions, building on the strength of our core business services to accelerate growth and expand margins. It has a few key elements, including our growth model, which includes our capabilities, what we go to market with, our clients, who we serve as we grow, and catalysts, how we plan to further accelerate growth. Riju, our Chief Growth Officer, will cover this in more detail just in the next session. You may be familiar with us in areas of data tech AI, digital operations. We have consistently shared with all of you the revenue desegregation based on both data tech AI and digital operations while we continue to operate and engage in the market through our vertical segments. Today, we are sharing two new terms with you: advanced technology solutions and core business services. First, advanced technology solutions. As Genpact pivots towards AI-led solutions, we have identified the most innovative, most impactful, and differentiated capabilities across our business and brought them together under one unified umbrella we call advanced technology solutions. Advanced technology solutions have four differentiated capabilities: data and AI, digital technologies, advisory, and agentic solutions. Advanced technology solutions apply new technology to our established core competencies of process, industry knowledge, and our understanding of operational data. This enables Genpact to solve client problems that drive growth and enhance productivity. As we help clients unlock productivity and better outcomes, we are evolving our commercial models too. Our commercial models are moving to non-FTE-based structures while preserving the annuity and long-term nature of our contracts. The second term, core business services. Genpact's core business services, defined as decision support services, technology services, and, of course, digital operations, provide a solid foundation for future growth. This visual shows how data tech AI, digital ops, intersects with both advanced technology solutions and core business services. With agentic solutions driving our rotation from digital ops, from core business services to advanced technology solutions, we transition Genpact to an agentic-first managed solution model. This creates more value. As you can see, here is the revenue desegregation of data tech AI, digital operations, advanced technology solutions, core business services. This number is for FY 2024. Our advanced technology solutions designed to solve high-value, complex problems for clients also deliver premium revenue for Genpact. Advanced technology solutions already account for about 20% of total revenues and are growing rapidly. You will hear more about our solutions, our differentiations from Sanjeev and Jinsu, who are leading our development efforts. Another element driving our pivot to become a global leader in advanced technology solutions is Genpact's strong and distinctive culture. While our culture has many dimensions, as you can imagine, four stand out as truly foundational to who we are and how we've been. First, relentless client centricity, an unwavering focus on solving what matters most. It's embedded in our DNA, and you will hear it directly from many of our clients today. Startup mentality: our leaders are hands-on and roll up their sleeves, stay hungry, and our teams act with a sense of ownership. I love our bias for speed and agility. In a world that moves fast, we move faster. Our ability to adapt quickly is a core advantage for us. Of course, an active learning mindset. Continuous learning is also embedded as a strand in our DNA, as what enables us to move ahead in fast-changing AI technologies. These cultural anchors, deeply rooted, actively lived, allow me to tell you a story of one of the long-standing clients, Unilever. We are incredibly proud of our partnership with Unilever, a company with a remarkable legacy and bold vision for the future. Together, we have embarked on a transformative journey. First, by reimagining their global plan to cash operations as part of running their global supply chain operations. In the last couple of years, we expanded and started to help them redefine their supplier operations. By leveraging technology and AI, we help Unilever run and operate both ends of critical interaction points. On one side, tens of thousands of suppliers, and on the other, core operations on the customer side to drive efficiency and effectiveness. This is what we refer to as mission-critical operations. Together, we have co-created global process models, deployed world-class technology, and focused relentlessly on improving both customer and supplier experience. This collaboration reflects our shared commitment to build intelligent, agile, and scalable models. Let's now hear from Steve McCrystal, Unilever's Chief Enterprise and Technology Officer, on our journey together. Unilever is one of the world's leading suppliers of beauty and well-being, personal care, home care, foods, and ice cream products, with sales in over 190 countries and products used by 3.4 billion people every day. Our supply chain is complex. Unilever operates over 280 factories and processes around 24 million customer orders annually. We collaborate with Genpact to enhance supply chain efficiency and create seamless operations. Genpact uses AI and data-driven insights to optimize service, improve agility, and drive continuous improvement. Over the years, our partnership has matured, supporting our AI-led digital transformation to boost innovation, operational efficiency, and both customer and supplier experience. We partner with Genpact to transform our supply chain operations across the entire value chain. In customer operations, Genpact has helped us transform our global supply chain, aiming to be supplier number one for our customers. Together, we co-designed a global program to simplify and standardize our global value chain across the entire order-to-cash process. In supplier operations, we have a vast and diverse ecosystem of 54,000 partners across more than 100 countries. Since 2023, we've been on a journey with Genpact to modernize our end-to-end source-to-pay landscape. Together, we are enhancing our key processes, including seamless contracting, supplier onboarding, and efficient payment processes. Transformation of this size requires the entire organization to come together with strong leadership, shared vision, and a strong technology pipeline. Thank you to everyone at Genpact for the collaboration and dedication as we continue our transformation journey together. Thank you, Steve and the entire Unilever team for entrusting us with mission-critical operations. Really proud and really proud of helping Unilever drive its AI-enabled journey. They leverage both our core business services and advanced technology solutions. Many of you know us for delivering lower cost of ownership. Today, our advanced technology solutions are extending that advantage by embedding AI into the deep expertise we have built over decades in process and industry domains. To our clients, including Unilever, we are also known for something more precious: delivering outcomes. Real, measurable business results that we take ownership of, and we are driving these outcomes faster. All of this is powered by more than 25 years of operational experience and the millions of transactions that we run through the year across industries. Now we are applying these advanced technologies to this operating mode. Our advanced technology solutions not only create more value for our clients, they also generate high-value revenue for Genpact. These solutions deliver more than 2x the revenue per head count compared to the company average and are growing at more than twice the pace of Genpact's overall revenue. What's more, 70% of the revenue is annuitized, and 70% comes from non-FTE commercial models, making it both high-quality, sticky, and strategically aligned with our future direction. We plan to further accelerate the growth of advanced technology solutions with significant investments in product development, sales, and partnership this year. We have referred to a growing base of agentic solutions. You might ask, where are these coming from? Many are coming from digital operations. We are proactively pivoting our business to agentic and, to date, successfully driving net revenue growth despite increasing productivity commitments. We are doing this through higher transaction volume and/or increased scope within existing accounts. We are also driving incremental revenue from entirely new logos for these agentic solutions. Although it's a small sample size today, all agentic deals signed to date in aggregate are driving net revenue growth for Genpact. These are early days. We may see productivity ask increase in the future. We have accounted for this in our prudent medium-term target. Ultimately, our performance will speak for itself. Looking ahead, we believe we are extremely well-positioned to accelerate revenue growth and expand margins as we build momentum in the key areas of Genpact Next. Mike will walk you through more details later, including how we are investing to drive growth while improving margins, how investors should track our progress with new KPIs, and our medium-term targets. Look, I would want to leave you with this. We have a clear and focused strategy. We are building momentum with Genpact Next across capabilities, clients, and catalysts. We are innovating at scale through advanced technology solutions. With our strong foundation, we believe we will accelerate revenue and expand margins. We stand at a pivotal moment for our company and our industry. My role and that of this leadership team is to lead, is to grow, and to pivot Genpact to become a global leader in advanced technology solutions. We are challenging our own playbook with intentional disruption to create more exponential value for our clients and for our investors. We are not just participating in a category. We are defining it. We are building it now, and you will see us scale it. This is Genpact's moment. We are all in. Ready to lead, ready to win with Genpact Next. Super excited to have you all here. I will now pass the baton to our Chief Growth Officer, Riju Vashishth, who will expand on our growth model in Genpact Next. Riju, take it away. Thank you, BK. This truly is Genpact's moment. I'm delighted to be here. Good afternoon. My name is Riju, and I serve as Genpact's Chief Growth Officer. In my tenure with Genpact, I've had the privilege of leading operations and driving digital transformation. Over the next few minutes, I'm going to share with you the growth model that powers Genpact Next. For 25 years, we have earned our reputation inside boardrooms of enterprise clients who have trusted us with their mission-critical operations. These are household names, and we have delivered these operations for them for 25 years. The Genpact growth model builds on this foundation. The model covers three Cs: capabilities, clients, and catalysts that work together to drive momentum. Capabilities are what we go to market with. Clients are who we serve as we continue to grow. Catalysts are how we accelerate this model to grow further. I'll now walk you through each of the three Cs of this model, starting with capabilities. Our capabilities are two sets of interconnected offerings that amplify each other: core business services and advanced technology solutions. Core business services are foundational offerings that include decision support services, technology services, and digital operations. Let me give you a flavor of the type of work we do here. In decision support services, we handle over 50,000 sanction screenings daily, helping some of the world's largest financial institutions comply with the latest regulations. In digital operations, we run one of the largest finance and accounting third-party operations, which means that our teams execute book closures for thousands of legal entities every quarter. That is more than what companies experience in their entire lifetime. We've earned the reputation for running these services with precision and consistency. These services deliver last-mile knowledge to us and data-rich environments, which help us scale advanced technology solutions. Advanced technology solutions is where this gets really interesting. Every transaction we touch, every process we run, and every anomaly we fix generates data-driven operational insights. Our advanced technology solutions are built on this foundation. As BK mentioned, our advanced technology solutions have four distinct offerings. These are data and AI, digital technologies, advisory, and agentic solutions. Our data and AI capability is rooted in operational expertise. When you are processing millions of transactions every day, you develop an informed understanding of how data and AI can drive the biggest impact for you. We have developed over 1,000 domain and industry-specific models, each trained to address specific business problems that we have solved through hands-on work over the years. The second one, digital technology. This leverages our process mastery. Most digital transformation efforts fail because they lack process understanding. As process geeks, we know exactly where processes break down and how digital solutions can fundamentally change them. When we deploy an accounts receivable automation solution and configure it, we know the industry-specific variations and the customer payment behavior that is going to make the maximum difference. Why? Because we have processed millions of these transactions, and this process mastery truly differentiates us. Our advisory services are built on industry intelligence. They are driven by a practitioner's perspective, which is rooted in decades of operational depth. Clients choose us not because we are observers, but because we have lived it, scaled it, and optimized it. We guide our clients through transformational change as practitioners and owners who know the realities of each domain. This results in trusted advisory relationships. Finally, agentic solutions. Our agentic solutions are powered by our last-mile knowledge. We believe that we are pioneering the future of business operations. Agentic solutions fundamentally reimagine how work gets done. We are architecting entirely new ways of working where autonomous AI agents handle routine decisions, manage complex workflows, while humans do higher-level activities. We know it is hard to do. Our agentic solutions possess unique competitive advantage: last-mile operational knowledge, which is all about process and industry-specific nuances. Jinsu and Sanjeev will cover this in more detail in the next session. Every company believes that their capabilities are truly differentiated. We are no different. Here is what unbiased experts have said. Major analyst firms have rated us as market leaders in more than 100 assessments since 2022. Our core business services and advanced technology solutions create a powerful suite of offerings that amplify one another. The next element of our growth model is our clients, who we offer these capabilities to. We focus on two client segments: enterprise and mid-market. Our enterprise client segment consists of companies with over $10 billion of revenue. We proudly partner with more than 25% of Fortune 500 companies, and a majority of them are long-standing relationships for us. These relationships are highly referenceable and form the backbone of Genpact growth. When we deliver predictable and measurable outcomes in one area of their business, they naturally ask us, "What else can you do for us?" That creates expansion opportunities. Clients are not looking only for cost takeout. They want partners who can drive transformation for them and help them being AI-first. Let's bring this to life with one of the enterprise clients, Sysco. Sysco is a Fortune 100 company with revenues of over $78 billion. It is one of the largest food distribution companies, serving more than 730,000 customer locations in over 10 countries. Think of Sysco as the circulatory system of the food services world. If food is moving in bulk, it's likely there is a Sysco truck behind it. Our partnership with Sysco has been a journey of transformation of their core finance and accounting operations. Working together, we deployed advanced digital systems to modernize their processes and automate their transactions. This initiative has unlocked significant efficiency for them and created a more streamlined environment. Today, this platform is a hub of activity, joining 2,000 Sysco users with 450,000 suppliers and customers seamlessly. We are proud to see over 85 million transactions processed annually. This is a testament to the power of these automation efforts. It's created a truly frictionless experience for Sysco. Sysco is also an early adopter of our agentic solutions. Our relationship with Sysco demonstrates a clear progression from core business services to advanced technology solutions. This shows how we expand our footprint with large clients. This is just one of many examples from our enterprise client base. We asked ourselves, "What if we could bottle this credibility that we have with our enterprise clients and take it to the next generation of market disruptors?" These are companies with less than $10 billion in revenue today, but have the DNA and the growth trajectory to become tomorrow's leaders. That question unlocked an entirely new vector of opportunity. We are strategically targeting fast-growing future leaders in our chosen industries. This historically underserved segment is looking for partners who understand their unique needs around driving scale. They are very early in their maturity cycle and provide us an opportunity to grow with them and position us to be the transformative partners to their C-suite leadership. Our approach to this segment has three elements. One, repeatable solutions that are purpose-built for this market. Second, flexible commercial models that deliver client outcomes. Third, a focused go-to-market team. We have established a strong revenue base with these clients and are poised for continued growth. Here is an example of a mid-market client: Advantage Solutions. Advantage Solutions is a leading retail solutions deployment partner in North America. They bring together brands and retailers. Today, they service 4,000 consumer brands and bring together over 100,000 retail locations across North America. They needed an innovative digital solution to manage their growth and their scale. We partnered with Salesforce to co-create a new industry-specific solution in order management. Let's hear from their Chief Digital Officer, Francesco Tinto, about this journey. As our business continued to grow, maintaining efficiency and assurance in client and customer satisfaction remained paramount to our success. To meet this goal, we have embarked on a comprehensive multi-year transformation initiative. To address this, we have decided to partner with Genpact. Their expertise in AI, machine learning, will be instrumental in streamlining our operation and making the process more efficient for everyone involved. As a result of our collaboration, we will be transitioning from our legacy system to a new AI-powered platform. Once everything is in place, we expect big improvement. We expect response time to be reduced by between 60%-70%, and client onboarding to be slashed from weeks to just a few hours. Our MS platform is future-ready. Depending on the business direction and expansion, the platform can natively integrate with our Salesforce platform, like Commerce Cloud, and provide consistent omnichannel experience. Our partnership with Genpact is truly transformative to us. By joining force, we will support rapidly expanding brands, minimize stockout for our retail partners, and generate both increased revenue and significant savings. We are excited about the future and how our transformation will streamline and optimize our operation to generate even more value to our clients, customers, and partners. Thank you, Francesco, for trusting us with your transformation journey. Why do these enterprise and mid-market clients choose Genpact? It starts with our process and industry domain expertise, which allows us to understand and solve complex client problems. Our proprietary tools, data, and technology solutions help us accelerate this transformation. This yields tangible outcomes for our clients. With more than 106% net revenue retention rate, client relationships grow because of these results. The third element of our growth model is catalysts. These catalysts help us accelerate momentum. While there are many catalysts, I'll share two critical ones with you today. The first is our expanding partnership ecosystem. The second is investments in talent to amplify AI. Our partnership ecosystem has three categories: domain, enterprise, and innovation accelerators. Our domain partners are firms like Blackline, Esker, Kinaxis, O9, and others. We've been a top partner with these firms for many years. Our enterprise partners are major firms like AWS, Databricks, Microsoft, Salesforce, and ServiceNow. Our partnership growth efforts with these firms are predicated on, one, enhancing our partnership status, and two, building joint solutions. We have achieved top-tier partnership status with AWS, Salesforce, and ServiceNow, and are on track to do so with Microsoft and Databricks. Our joint solutions portfolio is expanding. A few illustrative examples: we have a financial crime solution hosted on AWS Bedrock. We have an order management solution built on Salesforce and a sourcing and procurement solution on ServiceNow. These solutions help us create a differentiated positioning with partners and accelerate our pipeline. Our innovation partners are startups. These startups are early in their journey, and we leverage them across our portfolio to leapfrog our capabilities. Some examples of our current collaboration are: we use Instabase for intelligent document processing, Parallel.ai for AI-led web data innovation, Zenity for responsible AI adoption. As we continue to invest in our partnerships, we expect the contribution of the critical partnership channel to accelerate. The second catalyst is investment in AI talent. Piyush will talk in detail about how we are reshaping our total workforce. I will emphasize two critical facets of this approach. The first one is investment in AI builders, how we build advanced technology solutions. The second one is investments in sales talent, sales talent who are fluent in data and AI, and on how we sell these solutions. We have thousands of AI builders and growing. This talent helps us rapidly scale AI to deliver enterprise-grade solutions. Second is investment in AI sales leaders who can explain and apply these solutions. While we are upskilling our existing sales leaders and complementing them with specialist sales, we believe this model will help us accelerate sales. We bring together core business services and advanced technology solutions to solve higher-order client problems with this combined Salesforce. Partnerships and investments in AI talent are significant catalysts of our growth journey. In summary, this market is changing, and we are changing too. Our capabilities are truly differentiated. Our core business services give us scale and last-mile advantage. Our advanced technology solutions help accelerate transformation. Our client relationships are referenceable and are the backbone of our growth. We will continue to expand our footprint with enterprise partners and help mid-market clients scale. Our partnership ecosystem and AI talent are catalysts in this acceleration. This is Genpact Next in Action. Thank you. I'm excited about where we are. With this, I'd like to welcome Sanjeev Wora to talk more about our advanced technology solutions. Good afternoon, everyone. I'm Sanjeev Vohra, and I'm Genpact's Chief Technology and Innovation Officer. I'm excited to share how we are building advanced technology solutions that help our clients and Genpact accelerate growth. I spent my career building large-scale services and solution businesses, leveraging the power of data, technology, and AI. I was drawn to Genpact because of the depth and quality of the company's industry domain knowledge, the Lean Six Sigma heritage, and most importantly, the operational data mastery. The opportunity to bring this rich operational expertise with data and AI to create future value filled a vacuum that I've experienced in my previous stints. I could not be more excited to be part of this team leading Genpact's pivot to advanced technology solutions. Our timing is perfect. Our timing is perfect given the evolution of AI in the recent years. Let's spend a few minutes on the fast-changing environment. We all know that the pace of technology and its change is relentless. From cloud to data to AI, generative AI, and now agentic in the last five years. For most companies, effectively deploying emerging technologies, moving from experimentation to production and driving tangible business results is a real challenge. The same challenges show up across all the clients we serve. Most companies have mature transactional systems, their ERP systems, front-end systems like SAP, Oracle, Salesforce, but they all are siloed. There is plenty of data. Every company has plenty of data, but it is fragmented and messy. Business and IT teams, they move on separate tracks. Technology talent with the right blend of domain knowledge is truly scarce. Trust me, that is the fundamental and foundational to unlock the value from data and AI. These issues show up everywhere, negatively impacting the most well-funded programs. The bottom line is that companies see a clear potential of AI, but they struggle to implement AI at scale. As BK mentioned, we process and data engineers, we thrive on speed to value. Genpact's approach to these challenges combines our differentiated processes and the data expertise with a new AI capability that is phenomenal. The advanced technology solutions, these feature all these capabilities and solutions. They feature stronger Genpact IP, future-proof architectures, scalable delivery, specialized talent, and modernized commercial models. They all are high-value, next-generation offerings designed to address challenges our clients are facing towards in adopting AI at speed. They also position Genpact well to accelerate growth. Today, I will do a deep dive in data and AI, which is one of the fastest-growing capabilities within advanced technology solutions. My colleague, Jinsu Khan, will discuss service as agentic solutions later. Let me walk you through the data and AI stack. It all starts with data. It all starts with data, and it's foundational to AI. There are two parts to it. There are two parts to it: the data itself, data as an enterprise asset, and the second one is data supply chain, which is processing and preparing the data to feed into AI. The superpower that we have at Genpact is the knowledge of data itself, which is understanding of these critical data elements in processes and industry domains. These critical data elements are necessary for creating effective AI systems. As operators, we have access to domain-specific data. Add to that, we have our own proprietary data sets and our own models. We are talking about a few thousand data models across industry and processes. These models are a bedrock for data engineering and data management to generate high-quality data, which is a fuel for enterprise AI. When it comes to data supply chain, there are three elements. The first one is upfront industry-driven data strategy, which is creating the business case and roadmap. The second one is data engineering, building the data pipelines and data management. The third one is data management, which is about ensuring the high quality of data. To augment our existing capabilities in data, we recently acquired a company, Exponential Data. Now, having their team now being part of the Genpact family adds strong and future-ready leadership and capabilities in data strategy and data engineering on Databricks and AWS platforms across several industries. They have differentiated offerings. They have repeatable IP. Most importantly, they lead by industry-specific data and AI strategy. We all are super excited about our synergies. With this acquisition, we now have market-leading capabilities across all the three elements of data supply chain that is enabling us to have meaningful client conversations every day. Now, coming to Core AI, this is our strongest capability. We are delivering over 300 programs, leveraging more than 1,000 pre-built industry-domain-specific algorithms and models. These models use machine learning, advanced analytical tools, deep learning, neural networks, and they're building predictive and probabilistic AI systems of forecasting, anomaly detection, optimizations, recommendations across finance and accounting, supply chain, and several industries. A great example to bring this home is our client, Penske, a transportation and logistics industry leader in North America with around $10 billion in revenue and more than 400,000 vehicles in the field. They were struggling with fleet efficiency and maintenance. Genpact introduced an AI-based intelligent planning platform for fleet management, Genpact's own Fleet Management System, to ensure high availability of the right part at the right time at the right price from the right supplier. This was a fairly complex problem. This new platform that we built was on a Microsoft stack, leveraging 16 forecasting models and an artificial intelligence neural network establishing patterns across 42 different variables. This is driving part planning model accuracy, lowering the inventory cost, and enhancing the parts management service levels by 96%. This was made possible by leveraging our own supply chain offerings and our models. Now come to generative AI, which is still, I would say, in the early stages of evolution. This uses large language models provided by the big technology partners like OpenAI, AWS, GCP, and open-source models like DeepSeek and Meta's Llama. We invested last year in Genpact Lab. That monitors the advancement in these new technologies: foundational models, large language models, frontier models, distilled models, all kinds of models. And they compare the technological maturity and cost of its implementation. So far, we have delivered around 215 GenAI solutions in production environment, integrated with the workflow and generating real business and tangible business outcomes. These deployments are across processes and industry domains. These include data extraction and summarization, efficiency in software development, insurance claims and underwriting, customer service, order processing, and many more processes. Now, let me again provide a client example in this space. Our client is a leading global medical technology company with more than $15 billion in annual revenue. We have been their partner on a multi-year transformation journey to simplify their business processes and operations and improve outcomes for them. Together, we launched a comprehensive redesign of operational processes covering the entire spectrum of business processes. Genpact brought its MedTech AI-powered advanced automation capabilities to enhance the operational efficiencies. One of many capabilities is an AI-powered agent for the medical equipment services engineers. These are the people who are fixing or repairing these diagnostic machines deployed in the field. This is a mission-critical function, and one of the ultimate goals is to keep the machine uptime. We worked on lots of data: machine data, field data, operator data using Databricks on Azure, and OpenAI foundational models to create a generative solution that can deliver a clear path to resolution for these field engineers, which is seven times faster than the previous process they were following. This type of transformation is only possible with technologies like generative AI. Now, beyond its efficiency and keeping higher uptime, the observability of these failure patterns in the field and the insights that are being fed to the medical equipment, the insights coming out of this are being fed to the medical product design team to further optimize their machines. From Genpact's point of view, this extraordinary use of AI and associated data models for asset field services and field management is applicable across multiple clients and industries beyond healthcare. That is the power of a repeatable solution. Now, we have made tremendous progress in data and AI. Our sales pipeline has tripled in the last 12 months. Fundamentally, in data and AI, there are two distinct differentiators that we bring to the table. The first one is the access and knowledge of data that is based on our decades of experience running millions of operational transactions, as BK mentioned in his opening session. The second one is the way we are integrating AI into the processes and IT systems, addressing the challenges that every company has today, which is how to implement AI at speed and at scale. This is where Genpact's AI Gigafactory comes into play. Genpact's AI Gigafactory is one of its first of its kind delivery models designed to help enterprises rapidly deploying AI into production, generating business outcomes, and positive change management. There are three factors that differentiate the Gigafactory. The first one is AI Value Studio. The second one is AI Platform. We call it gsolution.ai and a unique pod delivery model. First, when the client enters the Gigafactory, they begin in AI Value Studio, where our value architects identify high-impact use cases and create custom roadmaps for AI solutions that can deliver higher ROI, working closely with the client business and technology teams. The second is our AI platform, gsolution.ai. It integrates the fragmented data across multiple systems. It enriches the data with contextual data. It brings Genpact's own proprietary data and prepares it for model training and refinement. Basically, it makes data usable. Now, once the data is ready, we then accelerate model development by leveraging the pre-built AI models and agentic frameworks. We have more than 1,000 pre-built and reusable AI models and growing. We have 75 differentiated patterns from Genpact Lab, all built with responsible AI by design. The third is our unique pod delivery model. These pods are cross-functional teams with blended skills: industry expert, data expert, and AI engineers, all organized by industry and technology. These pods take end-to-end accountability from design to deployment to management of AI systems, reducing the overall time to value. All engineers are trained and certified on gsolution.ai and our technology platform and our partner technology platforms such as AWS, GCP, Microsoft, Snowflake, Databricks. They all go through rigorous and continuous training that ensures that we have the future-ready talent available on tap to build and deploy scaled AI solutions. This allows us to move clients from pilot to full-scale production at speed. We started the AI Gigafactory in January this year. So far, our AI Gigafactory engagements have delivered tangible results for our clients: up to 40% faster implementation times, up to 30% higher throughput, and up to 50% reduction in typical cost of ownership. An example of how these advantages are translating to client value is with our longstanding client, GE Vernova, a $35 billion company, a company that we know very well for many decades. Let's now hear from our client, Santosh Kudva, who is the Chief Data Officer of GE Vernova, in terms of what he wants to talk about Genpact and our relationship. Vernova is accelerating the path to more reliable, affordable, and sustainable energy. Like many large global enterprises, we were constrained by legacy systems, some built over a decade ago. We require a modern AI-ready data foundation with elasticity and scalability. That is where our partnership with Genpact began. In January 2024, we launched our most ambitious data platform modernization program, migrating a complex ecosystem with 20,000 dashboards, 100,000 data objects, and which was used by over 10,000 users in our company. Genpact is helping us execute this with speed and precision. They brought a flexible pod structure for delivery purpose-built around our business functions and then used their in-house AI accelerators to automate critical steps like code conversion, testing, and lineage analysis, compressing the delivery times by 25%. The impact has been game-changing. At the end of this effort, we will be reducing our technical debt significantly, accelerating delivery of insights by 40%, and enabling real-time data sharing. More importantly, AI and GenAI capabilities embedded in the new data platform will reduce analytics delivery efforts by up to 30%. Genpact has been a strategic partner, bringing in technical capability as well as a deep understanding of how to drive business outcomes in complex global enterprises like ours. A big thanks to Santosh for being a demanding client and a great sponsor. In case you missed, he spoke about 100,000 data objects to one single platform, Databricks. Adding to what he said, the introduction of this AI Gigafactory has been pivotal to strengthening our strategic partnership with GE Vernova. We launched this factory in January 2025, and we have 45 clients in this factory, AI Gigafactory, year to date. To meet the growing demand, we have onboarded more than 100-plus experienced data and AI leaders in the space who have lots of experience doing this work. We are front-loading our talent investments in the AI Gigafactory to meet our clients' on-demand talent needs and already generating meaningful results. We also received strong validation from the industry analysts, partners, clients, and several prominent publications speaking to the differentiation of this offering. Now, let me close by sharing three key takeaways from this session. First one, our approach to delivering business value starts with the combined power of process, data, and AI, not as isolated capabilities, but as a connected engine for enterprise transformation. Second is our AI Gigafactory is a first-of-its-kind delivery accelerator in the industry focused on faster time to value. The third is we are investing in scaling advanced technology solutions to generate strong and sustainable profit growth, and we are on it. With that, I'm delighted to invite Jinsu Khan to talk about service as agentic solution. Thank you, Sanjeev. Hello, everyone. I'm Jinsook H an. I lead Genpact's strategy and corporate development teams, and I'm also responsible for building and scaling our agentic AI offerings within advanced technology solutions. Throughout my career, I worked at the intersection of data science, AI, and transformation. I've closely observed Genpact as a client, as a competitor, and strategist. I was drawn to Genpact by its potential, an expert leadership team with the courage to intentionally disrupt, and a powerful vision of agentic AI. As Sanjeev mentioned, a critical element of our advanced technology solution strategy is the rotation of our digital operations into agentic AI-powered operations. Our service-as-agentic solutions are proprietary Genpact solutions that transform mission-critical business processes from BPO to autonomous AI agent-led delivery. They include specialized large language models, LLMs, modular design, adaptive learning, and responsible AI controls, all designed to deliver efficiency and value for our clients. Today, we focus on these solutions while rotating existing FTA-based processes to agentic operations. As you know, Genpact is one of the largest global players in finance operations, with a significant market share. We have chosen to begin our journey to capture value from this position of strength. A finance and accounting services and technology leader consistently cited by various industry analysts in their latest reports. Our expertise spans the entire finance and accounting domain. The AP Suite is an example of how we transform manual and time-intensive processes to deliver greater efficiency and value. A large portion of invoices globally are handled manually due to OCR errors, messy input data, and complex exception management. Variability and contextual interpretation of data, purchase order mismatches create large leakage. Duplicate payments, overpayments, and fraudulent invoices create further risk and significant costs for businesses. When building our agentic AI solutions, we designed to address these challenges head-on, based on our deep process and industry domain understanding and hands-on operational expertise. Since launching our agentic AP Suite in February of this year, we have been actively transitioning our AP operations from traditional delivery methods to an AI-driven model. Our agentic AP solution provides significant benefits to clients, including more accurate autonomous data capture through AP Capture, greater touchless processing with significant productivity benefits through AP Advance, enhanced cash invisibility, and reduced leakage with up to 90% early discount capture through AP Trace, improved supplier relationships through high-speed processing, and automated supplier query resolution through AP Assist. Genpact's AP LLM, trained on a vast number of live transactions, transforms AP function from a call center to a strategic asset with minimal human input. Let's explore how AP Advance quickly and intelligently resolves order, invoice, and delivery mismatches. And yes, we'll be talking about tomatoes too. A food processor places a purchase order for 1,000 kilograms of tomatoes. Due to moisture loss, spillage, and transit damage, only 950 kilograms are received, very common for perishables. This is recorded in the goods receipt note. The supplier invoices for the full 1,000 kilograms. During a three-way match of invoice, goods receipt note, and a purchase order, the AP system detects a discrepancy. Without agentic AI, this gets escalated to a human reviewer, delaying processing by days, sometimes weeks. Here is how agentic AI handles it differently. The AI recognizes tomatoes as perishable, pulls the historical data showing a 5% typical variance, and dynamically adjusts the threshold. It also factors in real-time contexts like tomatoes in summer, 5% expected variance. This particular supplier in Mexico adjusts to 3% based on past reliability. The result: the invoices process automatically in seconds, not days. It does not stop there. Agentic AI reasons like a purchase officer with experience. It learns supplier patterns, flags anomalies, feeds insights into your Procure-to-Pay system to guide sourcing, renegotiation, or performance scoring. That is how the agentic AP Suite achieves high levels of touchless processing, delivering significant cost savings straight to the bottom line. The impact of the Genpact agentic AP Suite is already proving out across multiple clients. One example is Wesco, a $22 billion global electrical distribution and service company. Wesco is the central nervous system of the distribution industry. It ensures that power flows, networks stay online, and infrastructure is maintained, quietly enabling the world to work efficiently behind the scenes. Through a comprehensive process and technology transformation, we have brought together Wesco's entire AP and procurement organization, collaborating seamlessly on a single unified platform integrated with multiple ERP systems. With the addition of Genpact's agentic AI AP Suite starting last year, Wesco has significantly reduced manual workloads and enhanced data-driven decisions with real-time dashboards. As we continue to enhance the Genpact agentic AI AP Suite, Wesco is targeting even higher performance on invoice extraction and accuracy, as well as enhanced vendor experience through the AP Assist module. Let's hear from Dave Schulz, Chief Financial Officer of Wesco, on their transformation journey. Wesco is a leading provider of business-to-business distribution, logistics services, and supply chain solutions. Wesco operates more than 700 sites, including distribution centers, fulfillment centers, and sales offices in approximately 50 countries. Along with our acquisitions came a variety of disparate ERP systems and legacy business processes. Our partnership with Genpact began four years ago following the merger with Annixter. We essentially doubled the size of the company. This, along with the number of different systems and processes, drove the need to overhaul our accounts payable process. With Genpact's help, we've streamlined, standardized, and automated our AP operations onto a single platform, helping us to lower costs and save time. Genpact's strength lies in its ability to combine deep process expertise with cutting-edge technology to drive real business transformation. A key element of our transformation has been the implementation of AI to centralize and automate core back-end functions so that our AP teams can connect with buyers and suppliers worldwide. The introduction of advanced technology capabilities has significantly reduced manual workloads. Real-time analytic dashboards provide visibility into process health, enabling data-driven decisions. Through iterative development and a commitment to continuous improvement, our system now processes 40% of invoice inflow with zero human intervention. It's a significant improvement in efficiency when you consider that we process over 3 million invoices annually through our systems. We are on a clear path to further increasing zero-touch processing significantly by the end of this year. In addition, our invoice extraction has more than doubled, and we are focused on reaching even higher levels by next quarter. So far, we have implemented three core components of Genpact's intelligent AI solution: extraction engine, exception handling, and invoice duplication detection. We are working on a fourth, a GenAI-powered help desk solution. I look forward to continued success of our business transformation and speak for the entire team when I say thank you to Genpact for your collaboration and support. Thank you, Dave, for your continued trust in Genpact being your transformation partner. All four modules are live, and we are actively developing additional features and agents. As client zero, that is Genpact ourselves, we are already using the AP Suite as well. Let's take a look at the trend we're observing across our agentic portfolio. For existing accounts that have rotated from FTA-led delivery to agentic delivery, we are seeing 3% revenue growth. That's net of productivity commitments. This is driven by higher volumes, increased scope, or a combination of both. Across these contracts, in aggregate, we are seeing gross margin improvement of 300 basis points. Our agentic AI solutions are also driving incremental revenue from new clients with higher gross margins as compared to our existing offerings with FTA-based operations. As agentic revenue continues to scale, we're confident in our ability to further expand margins. From our capabilities in advanced technology solutions, we do discuss our partners, and Sanjeev covered the Gigafactory. Building on that, expert humans are a vital part of our AI capabilities. Our AI talent has grown significantly, and Piyush will share more on talent later. Now, let's take a deeper dive into our agentic AI architecture and capabilities. It starts with the ingestion connector hub that integrates data using our connector library and from gsolution.ai, that Sanjeev covered, and creates structured and unstructured data in our data engine room for using AI models. The AI agent foundry is where we develop, train, and deploy executable agents using domain-specific LLMs and SLMs. These agents are fine-tuned for very specialized functions, enabling contextual task execution across industries. These layers operate within the responsible AI framework, ensuring security, observability, explainability, and controls. We publish mature models for our internal marketplace for reuse and with some commercialized via our partner marketplace. All agents follow the agentic AI development life cycle, where they are monitored, tuned, and retired. Genpact possesses robust baseline capabilities, including agentic infrastructure, exception handling, and representative data sets. However, it's our last mile capabilities that are driving the real differentiation and impact. Since I explained accounts payable as one of the many examples, let me pick up a last mile example in this space. Our experience shows that AP processes often involve multiple ERPs and connectors. What may appear at first glance to be just a few ERPs often turns out to be dozens of highly customized instances, each one uniquely tailored. These custom systems are linked to hundreds of applications relying on inputs like faxes, handwritten notes, websites, downloads, et cetera. Global processes span dozens of countries, numerous languages, and hundreds of jurisdictions, each with its own local tax rules and required audit trails. This is the place where expertise and context really matter. Being process geeks, we understand these issues and nuances deeply. That's what's built into our agentic AI AP Suite: domain-specific LLMs and SLMs, capabilities that handle the toughest level three exceptions, regulatory and geography complexities, and an extensive library of connectors that have been built from real operations over time. The last mile is where we build client trust and deliver real value. With agentic AI, that means creating lasting and sticky revenue. Looking ahead, we have built a robust multi-year roadmap featuring a wide range of agentic solutions spanning our existing digital operations. The roadmap unfolds in three parallel workstreams. Workstream one includes a library of domain-specific and Gigafactory agents. Select examples of our development that are underway span domain-specific agents in report to report, supply chain, order and trade management, insurance claims and underwriting, and sales operations, to name a few. Gigafactory agents include code generator, data connector agents, enterprise risk management agents, agentic AI development life cycle agents, and others. Workstream two includes orchestration and workflow agents. Workstream three addresses agentic AI ecosystems. Before we take a short break, I'll leave you with a few messages today. Last mile strengths are what differentiate us. Our deep process intelligence, robust data, scalable architecture, and domain-specific technology set us apart and position us for success in the market. Our rotation to agentic operations is already driving net revenue growth and gross margin expansion with acceleration expected over time. We're investing aggressively to disrupt ourselves. We're leveraging advanced technology solutions, including our AI Gigafactory, agentic AI architecture, and a tech-savvy workforce to transform digital operations and build a strong partner ecosystem. It's an exciting time for Genpact and our advanced technology solutions team. We are thrilled to share it with you. Thank you. With you, take me where I want to go, yeah. I'm all that you know I know, yeah. The only place I want to go, yeah. No, no, yeah. With you, take me where I want to go, yeah. I'm all that you know I know, yeah. There's no place that I want to go, yeah. No, no, yeah. No, no, yeah. Take me where I want to go, yeah. I'm all that you know I know, yeah. The only place I want to go, yeah. No, no, yeah. With you, take me where I want to go, yeah. I'm all that you know I know. There's no place that I want to go, yeah. No, no, yeah. No, no, yeah. Take me where I want to go, yeah. I remember what I said, spoken in the dead of night with thrall. I hear your voices in my head, saying that you were the one to use. The world doesn't hurt. I left you first, can't admit it to myself. I guess I was wrong. You need time, your time. You were my dearly beloved. You were my dearly beloved. You were my dearly beloved. You were looking into my eyes, saying that you never felt this good. Now I dream of better times, wishing I could hold you close again. Why do you cry? I left you by your side. Why does it hurt? I left you first, can't admit it to myself. I guess I was wrong. You need time, your time. Why does it hurt? I left you first, can't admit it to myself. I guess I was wrong. You need time, your time. You were my dearly beloved. If I say goodbye, then make me a lie, make me a lie. My heart's heating up, this love is on fire, love is on fire. If I say goodbye, then make me a lie, make me a lie. My heart's heating up, this love is on fire, love is on fire, on fire. On fire. If I say goodbye, then make me a lie. If I say goodbye, then make me a lie. If I say goodbye, then make me a lie, make me a lie. My heart's heating up, this love is on fire, love is on fire, on fire. On fire. You keep on calling myself out to tell me you're sorry. I've heard it a thousand times. You always tell me you've changed now. Back from the outside to turn back the hourglass. Why can't you be honest? Changing your mind, wasting my time. Love ain't just a promise. Over your kind, losing my mind. Why can't you be honest? Changing your mind, wasting my time. Love ain't just a promise. Over your kind, losing my mind. Why can't you? Why can't you be? Be loved? Why can't you be? Be loved? Why can't you be? Losing my mind. You keep on calling myself out to tell me you're sorry. I've heard it a thousand times. You always tell me you've changed now. Back from the outside to turn back the hourglass. Why can't you be honest? Changing your mind, wasting my time. Love ain't just a promise. Over your kind, losing my mind. Can't you be? Can't you be? Love? Why can't you be? Be love? Why can't you be? Be love? Why can't you be? I've been going off of broke for my friends to like me old, but I know they see right through me 'cause they listen to my songs, yeah. I don't care, no baby, I don't care. People always tell me take a breath, hey, hey, hey. I've been looking for something that haunts me all night. I've been staying up hours until the sunrise, just in case you're always living the same life. I don't really mind, but I just need to take some time to get away. I don't really mind, but I just need to take some time to get away. I don't really mind, but I just need to take some time to get away. Is there something I could take for this pain to go away? 'Cause I've tried a hundred methods and they always seem to fail. Am I crazy? Do not tell me I'm crazy. I just need to find another way, hey, hey, hey. I've been looking for something that haunts me all night. I've been staying up hours until the sunrise, just in case you're always living the same life. I do not really mind, but I just need to take some time to get away. I do not really mind, but I just need to take some time to get away. I do not really mind, but I just need to take some time to get away. I just need to take some time for me, myself, and I 'cause I'm so bloody tired, yeah. I'm alright, trust me, baby, I'm alright. I'll just sit back and enjoy the ride, hey, hey, hey. I've been looking for something that haunts me all night. Love is filling the bowels until the sunrise, just in case you're always living the same life. I don't really mind, but I just need to take some time to get away. Welcome back, everyone. Imagine a world where mortgage approvals happen in hours and not weeks, where flood insurance gets settled in days and not months, where a small business owner spots an opportunity at 2:00 P.M. and has funding in his account by 3:00 P.M. This isn't the future we are imagining. This is the future we're building today. I'm Sameer Dewan, and I lead the financial services business for Genpact. We help banks, capital market firms, and insurance companies run and transform mission-critical services such as retail and commercial banking operations, perform credit decisioning, comply with risk and regulatory requirements, and support claims and underwriting operations. I can tell you this: with all of this change and opportunity, this is the most exciting time to be part of the financial services industry. Right now, as we sit in this room, 12 of the world's top 20 global banks are running core business operations powered by our solutions. Twelve of the top 15 global investment banks, eight of the top 10 US banks, and six of the top 10 US insurers are all Genpact customers. When the world's most demanding financial institutions need to transform their operations, they choose us. Today, I want to share three important perspectives with you. First, establish the depth of process and industry domain that Genpact brings to the financial services space. Second, demonstrate the strength of our client partnerships by showcasing two transformation stories. Finally, our differentiation and why leading financial services organizations choose Genpact as their transformation partner. Financial institutions today stand at a critical inflection point. Banks and insurance companies are facing unprecedented challenges that go beyond traditional operational hurdles. Our clients come to us consistently expressing three pain points. First, regulatory compliance has become extraordinarily complex and expensive. Financial institutions face an ever-growing web of regulations across multiple jurisdictions. Each new regulation requires additional oversight, documentation, and reporting, often with severe penalties for non-compliance. Second, many banks and insurers operate on decades-old systems that were not designed for today's AI-first world. These systems create data silos, slow down innovation, and lead to high operational costs. Third, changing customer expectations have created a significant experience gap. Today's customers expect the same seamless digital experience they receive from technology giants. Yet, many financial institutions struggle to remove friction and provide a seamless end-to-end experience. Here lies the opportunity. The institutions that move first, that embrace radical transformation now, will build market share and lead the industry. We're combining our capabilities across core business services with advanced technology solutions to help companies transform and stay ahead of industry challenges. Let me illustrate this with two client examples where we have transformed our core business services leveraging advanced technology. The first client is a global leader in property and casualty insurance, operating in over 20 countries and generating about $50 billion in annual revenue. This client faced profitability challenges and embarked on a comprehensive transformation journey. As a long-standing partner, Genpact has been instrumental in helping the client reimagine their business processes by seamlessly integrating technology, operations, and data. One of the many core business services that we provide to the client is managing their property contents insurance claims. These are contents in your home that get damaged when you have a broken pipe, a fire breaks out, or a storm hits town. Our client receives about $500 million in claims of damaged contents every year. The existing claims process was manual. Hundreds of researchers received lists of damaged contents and conducted individual pricing research for each item. This approach resulted in processing delays spanning multiple days, frequent pricing inaccuracies, and customer service levels that failed to meet market expectations. We have redesigned the end-to-end claims journey from initial inventory creation to pricing through AI interventions and replacement of the items through Amazon Prime and other retailers. The Genpact solution being implemented uses proprietary business logic, and our rich contents database was used to train the AWS Bedrock LLM. Our last-mile knowledge has helped us deal effectively with non-standard household items like rugs and artworks that many of us prize. This implementation, once delivered, will deliver two key outcomes. One, reduce claim cycle by 80%, and claims will now be processed in minutes, not days. Second, improve pricing accuracy of property contents by 2%-3%, resulting in an annual save of $10 million-$15 million. This may seem like a small percentage, but for anyone in the insurance business, 2%-3% reduction in the claims cost is a really big deal. This is just one example of over 50 proprietary AI models that we have built to meet the unique needs of insurance clients. These solutions are being implemented across multiple clients and creating a competitive advantage for them. Our delivery excellence and client trust built on the foundation of core business services has enabled us to expand into advanced technology solutions, a key part of our Genpact Next strategy that BK and Raju spoke about earlier. Our second client story is a great example of how we have combined our process and industry domain expertise with enterprise technology partners to co-create solutions that solve for the needs of a specific banking client. For this story, I'm delighted to welcome an esteemed client from Santander U.K. who has traveled all the way from London to be with us. Santander, for those of you who do not know, is part of Global Fortune 100 and has 175 customers worldwide. Please welcome Steven White, Chief Operating Officer at Santander U.K. Thank you so much. Absolutely. Good afternoon. For anyone who's had too much sugar in the break, I can see you all chewing away. That picture is quite old that you saw of me earlier, but I would still like to look at that soon again. Anyway, good afternoon, everyone. Santander UK is part of the Spanish Santander Group, the largest retail and commercial bank in Europe. We serve 14 million active customers in the U.K. every day. Our history is deeply tied to the U.K.'s banking tradition, but today we operate in a highly competitive, fast-moving environment. Digital challenger banks are reshaping the industry. To stay ahead, we needed to offer better customer experiences. We also needed to streamline processes to handle changing demand and improve our cost-to-income ratio. We faced challenges. Our legacy systems, manual processes, were slowing us down. I hope my Scottish accent is okay so far. Thumbs up. Thank you. These systems, inherited through many acquisitions, caused inefficiencies and inconsistent customer experiences. Let me give you some examples. Mortgage applications were often delayed. Business banking account closures took too long. Our operational costs were high because we did not have enough automation. On top of that, seasonal surges like student loan applications stretched our capacity. What did we do? That is when we partnered with Genpact to reimagine how we work. Together, we built a lean digital blueprint. This plan identified a roadmap for automation and digitization of our processes. Genpact took over the running of several of these core banking processes. They introduced automation, AI, and advanced technologies, including Salesforce and ServiceNow. This helped us to streamline tasks like customer onboarding and document validation. Advanced data models and analytics now predict and manage business volume fluctuations. Genpact helped us to meet regulatory demands and compliance deadlines for resilience and consumer duty. The results have been remarkable. In less than four years, we have increased customer satisfaction, our NPS, by 5%. We have boosted our market share in student loans by over 30%. We have closed banking accounts 90% faster with full automation. We have improved our cost-to-income ratio by 10%. We have improved our payments by 94% and reduced our risk and wrong payments by GBP 1.5 billion. Ultimately, it has changed how we are now serving our customers. We are now more agile, we're more efficient, and we're more customer-focused. We have done this by building a deep partnership with Genpact over the last few years. Genpact now serves all of our customers across all retail, commercial banking products, and payments. With Genpact, we are not just improving our processes. We are driving radical transformation to fully maximize data and AI across the whole bank. In summary, together, we are redefining the future of banking. Thank you. Thank you. Thank you. Thank you, Steven. Congrats on the amazing outcomes delivered and for sharing the snippets of the transformation journey with us. You heard the two stories of how we are solving client problems and delivering key business outcomes. Let me now summarize on why clients choose to work with us. One, we lead with our knowledge of the last-mile nuances, built on the deep foundation of our process expertise, data access, and understanding. This enables us to solve client challenges with unprecedented precision to deliver measurable ROI that others cannot match. Two, we are the orchestrators of domain-specific technology ecosystems. Rather than implementing isolated tools, we curate, process, and domain-specific technology solutions, enrich them with our proprietary IP, and create scalable, repeatable assets. We bring business and technology together. Three, we align our success and our commercial model to client outcomes. The skin-in-the-game approach demonstrates our confidence in delivering measurable results and builds true partnerships rather than traditional vendor relationships. Genpact's ability to deliver key business outcomes through a mix of deep business knowledge, operational excellence in delivering our core business services, and advanced technology solutions is why financial services clients choose to work with us. With this, I'd like to hand over to my colleague, Anil Nanduru, to talk about how we are delivering client value across several other industries. Thank you. Good afternoon. How's everyone doing? I know it's a bit cloudy outside, but the views are still gorgeous. thousand five is when the year Genpact became an independent company. iPhone was two years away, and generative AI had not even been coined yet. You fast-forward that to 2025, twenty years is actually a blink in human history. In the fast-paced world of technology and business transformation, that actually represents several lifetimes. I'm here to talk about this evolution, how our clients have transformed in this time, and what's our role in it. Good afternoon, ladies and gentlemen. My name is Anil. I lead Genpact's high-tech and manufacturing, consumer, and healthcare business segments. Two decades ago, Genpact was focused on process excellence within GE. Today, with that same spirit of excellence, we are developing AI solutions that are fundamentally reshaping entire industries. We work with leading companies in the Global Fortune 500 list. Let me give you a kind of a quick glimpse. Thirteen of the top 25 healthcare and life sciences companies, eight of the top 15 food and beverage companies, four of the top 10 high-tech companies. Going back to our roots, we've actually built a strong presence in the manufacturing sector thanks to our origins in GE. We work with established names in the manufacturing sector. We can proudly say that we understand the challenges of these industries, the growth prospects. We understand them deeply. While high-tech, manufacturing, consumer, healthcare are different, they all actually face similar challenges. One, these are global companies with incredible operational complexity and fragmented processes. That is the reason why they struggle to achieve efficiency and scale. Two, they have legacy technologies, and they grapple with siloed data systems and lack of intelligent automation. Guess what? That inhibits their AI adoption. Three, complex supply chains. They are vulnerable to frequent disruptions, such as external shocks, tariffs, geopolitical tensions. All of this leads to delays and reduced resilience. Today, I'll take you behind the scenes where you'll hear about client challenges in more detail and how our clients have partnered with us to solve them. I'm going to share two stories where core business services and advanced technology solutions are deployed. These solutions, both of them, are powered by our deep process and industry domain expertise and operational excellence. That is what our Genpact Next strategy is all about. I'll start with high-tech first. We serve the technology solutions group of NTT DATA. They were formed by a merger of 31 subsidiaries. NTT DATA is one of the largest business and technology services providers in the world, with annual sales of over $30 billion. Our strategic partnership began three years ago, where we started providing them core business services like Source to Pay and Order to Cash. What we saw were inefficiencies driven by error-prone manual interventions, multiple source systems, diverse market nuances. That challenge was actually further aggravated by disparate workflows and nonstandard ways of working. All of this resulted in continuous rework across front, middle, and back office functions. It increased the cycle time. It increased the high cost to serve and actually impacted overall experience. What did we do? We first centralized and standardized the processes. We then deployed advanced technology solutions like AI workflows and AI models. The past nine months, though, has been super exciting, actually. We've established an AI center of excellence for them, and that actually acted as a last-mile integration layer. Let me explain just how transformative these solutions have been with one example. This is in the order to cash space. It is called the Disputes AI solution. In their business, around 5% of the outstanding is disputed. The resolution process is manual. It involves multi-layered investigation and coordination across multiple teams. A few of them can actually take up to 120 days to resolve, which strains the cash flow. Our solution, the Disputes AI solution, is a game changer. It automates dispute investigation. It analyzes patterns and recommends remediation action, drastically cutting the resolution time by 40%. This has led to faster cash recovery, lower operational overheads, and most importantly, elevated customer experience, something we and our clients are deeply passionate about. The COE, the AI COE, which I talked about, has successfully developed 12 AI-powered solutions across the core business services. Four of these solutions are in the Source to Pay space. Let's hear directly from NTT Technology Solutions Chief Financial Officer, William Yong, about the impact of these AI solutions. We are one of the largest business and technology services providers in the world, with about annual sales of over $30 billion. Here at NTT DATA, leveraging advanced technology and AI is key for us to stay ahead in today's extremely fast-paced market. Given our size and scale, our finance operations manage an extensive volume of transactions every month, spanning multiple markets with different regulatory and client requirements. To maintain accuracy and speed, we collaborated with strategic partners to establish a center of expertise for AI-driven smart transformation. Together with Genpact, we designed and implemented AI-driven solutions on smart automation and advanced analytics, giving our finance operations real-time insights to make faster and better decisions. These solutions were designed as specialized AI agents, integrated effectively with our existing people, processes, and tools. Today, our four Source to Pay AI agents, from ProcureAI, Payment Support AI, ETA AI, and Spend Guard AI, are tailored to our specific workflows and processes for us to expedite the creation of purchase orders promptly and accurately, responding to vendor queries all the way to driving predictable fulfillment with automatic tracking updates, as well as smart monitoring for payment anomalies to guard against fraud. We have two Order to Cash AI agents helping our finance operations to perform automated validation for contract compliance, as well as to fast-track billing, resolving client queries and also disputes both kindly and accurately. With the AI agents in place, suppliers now can receive responses almost instantaneously, reducing our resolution time by up to 90%. It all frees up our team to focus on what matters, and that is to drive business growth. Fraudulent invoices have also reduced by up to 80%, along with processing throughput improved by up to eight times. Together with Genpact, NTT DATA has put smart intelligence across the business operations in technology solutions, laying the foundation for strong and sustainable business growth in the years to come. We are equally excited to witness both of us define a new benchmark for the industry. Let's go to the second client story, and this is in the consumer goods sector. Here, there is actually a big untapped market opportunity. According to a study by McKinsey, GenAI use cases are expected to unlock an additional $160 billion-$270 billion in profit annually for all CPG companies combined. We are using the depth of our knowledge of core business services in the CPG industry. We're developing AI and GenAI solutions to maximize value for our clients. Our next story comes from Japan. For that, we'll have to go to Japan. It is in the world of vending machines. Let me introduce you to the unique vending machine culture in Japan. You will see these machines at every corner: parks, buses, bus stops, temples, even remote hiking trails. Our client, CCBJI, Coca-Cola Bottlers Japan, manages hundreds of thousands of these vending machines, and they form a core part of their operations. However, they were actually constrained by a reactive maintenance approach, leading to extended downtime, fragmented inventory management, and siloed data systems. This is a great example of how core business services and advanced technology solutions come together to solve the client's challenge. We modernized field operations. We developed intelligent planning solutions. We set up a Smart Command Center for visibility and control. As you can imagine, AI is embedded in all. All of this led to a reduction in equipment downtime, optimization of spare parts usage, and reduction in costs. To share more, we have the honor to hear it directly from Alejandro, President of the retail company at CCBJI. CCBJI operates across Japan as one of the largest bottlers in the Coca-Cola system. We manage a wide range of beverage sales equipment, such as vending machines, coolers, and dispensers. These machines are key drivers of our revenue and play an important role in our daily business operations. Managing such a large equipment network has always been a challenge. Reactive maintenance led to extended downtime, fragmented inventory management, drove inefficiency, and siloed data systems limited strategic decision-making. These issues raised operational costs, delayed repairs, and made it harder to stay competitive in a fast-moving market. That's why we partnered with Genpact to transform our beverage equipment operations. Together, we launched the Genpact Smart Command Center, a detail hub leveraging real-time data, predictive analytics, and AI-driven insights. The transformation focuses on three key areas. The first is shifting from calendar-based to predictive maintenance, significantly reducing equipment downtime. The second one involves centralizing inventory management, allowing us to optimize spare parts usage and reduce costs. Third, we're equipping field technicians with AI-assisted mobile tools to increase efficiency and streamline the entire service process. By leveraging new technologies introduced by Genpact, we're optimizing field service, automating workflows, and ensuring a seamless customer experience. This is just the beginning. Together with Genpact, we're setting a new standard for equipment services in the beverage industry. We're excited about the journey ahead and remain committed to delivering best-in-class equipment services driven by innovation, technology, and operational excellence. Thanks, Alejandro. We love the partnership. I think both of us should get a quote from that vending machine next time when we're in Japan. As we reflect on these three transformations, why do these industry titans consistently choose Genpact? First, clients value our deep process and domain expertise. We understand the intricacies of each of these sectors that we serve: consumer, retail, healthcare, life sciences, manufacturing, high-tech. We understand the intricacies of these industries. Second, one of our core differentiators is our ability to set up global operations and execute at scale in highly complex environments. Whether it's navigating 31 subsidiaries, managing a supply chain of a network of thousands of vending machines, we bring structure to complexity. This is what I love. This gives us access to high-quality, structured, and unstructured data sets. This provides us with a robust foundation upon which we can actually architect and scale advanced technology solutions. Third, we develop enterprise-wide AI solutions, leveraging our deep understanding of last mile, which Jinsook spoke earlier. Process and industry domain expertise, advanced technology solutions, execution excellence, with a focus on outcomes. That is what wins us the client's trust. Thanks, everyone. Now I'll hand it over to Piyush Mehta to talk about how we are building a future-ready workforce. Thanks, Anil. Hello. My name is Piyush Mehta, and I've been with Genpact for close to 25 years. I've had the privilege of working with all three of our CEOs and therefore a ringside view to our transformation as an organization. What I can tell you is that I'm more energized than ever by the work that we are doing today. I want to start by sharing with you a recent interaction that happened in one of our cross-functional delivery teams. This was a group of data scientists, solution leads, transformation specialists, and medical device experts. They were working on a smart support solution. Hospitals and clinics that were facing issues with medical equipment were having to wait for up to 24-48 hours to get a field engineer visit to examine the device. The team was working on a solution that could suggest resolutions immediately, with the potential to reduce up to 3,000 visits and advancing resolution by up to 72,000 hours. One of the newly hired data scientists said, "I've never understood this industry like I do today." This isn't just about data. We are helping hospitals act faster and, most importantly, save lives. Moments like these are powerful, but they are not rare. This is who we are: a company where tech talent doesn't just build models; they solve real-world problems. Where industry domain experts don't just advise, they co-create with engineers, with data scientists, and with designers. That's our edge. That's the talent journey I'm here to share. Today, a significant proportion of our workforce are domain experts, trained and tested on process improvement methodologies like design thinking and Lean Six Sigma. What differentiates us is the intersection of these skill sets with data and AI skills. Nearly 80% of our domain experts have at least a foundational understanding of data and AI. As we make our strategic pivot to advanced technology solutions, we are reshaping our workforce into two cohorts: AI builders and AI practitioners. AI builders are experts who build the AI solutions. Think about data scientists, think about data engineers, and think about technical architects. AI practitioners are domain experts who are trained to use AI in the flow of work for client processes. For example, a supply chain planner leveraging AI models for inventory management, or a finance analyst leveraging the CFO Action Hub for insights. With the democratization of AI, we will not need as much specialized coders, but we will need techno-functional experts who work with AI. Our goal is to make our entire workforce AI practitioners over the middle to long term. Our talent strategy powers our business through three pillars: attracting advanced technology talent, upskilling with speed and at scale, and unlocking productivity and innovation. Our invitation to dream in digital and dare in reality has served as the anchor to attract advanced technology talent. Within our top leadership team, we have significantly increased the proportion of advanced tech hires in the past two years. When we ask them why they choose to join Genpact over other companies, they tell us it's for the ability to experiment like a startup with the resources of a large global company. We believe the ability to innovate in a meaningful way is a massive differentiator for us to attract and retain talent. Senior leaders such as Sanjeev and Jinsook, both of whom you've heard from earlier today and will meet later in the evening, in turn have served as talent magnets for us to help hire leaders in our top 1,500 cohort. The passion and energy of our leaders is palpable. They enhance the breadth of talent we already had in digital workflows, in analytics, and in automation. Our AI leadership team has enabled us to move with agility and to pivot at scale. At the front line, we are building our gigafactory talent for high-demand skills like Databricks, Snowflake, etc., to tackle advanced technology projects, again, at scale. This allows us to move swiftly and deploy AI-ready teams. For example, for a global energy giant, we deployed 76 Databricks resources from the gigafactory in a really short period of time and helped accelerate the modernization of their data stack by six months. Our employee value proposition is learn, grow, and succeed. This is something we believe in very passionately and drive at an industrial scale. Our proprietary learning platform, Genome.AI, is a critical part of our success. In 2024 alone, we've clocked 11 million learning hours for our employees, averaging 82 hours per employee, which is industry-leading. Interestingly, in the last 12 months, LinkedIn data shows 44x growth in our AI learning for Genpact versus 6x for our peers. Given the shelf life of skills is shrinking dramatically, our learning agenda has to deliver with speed and with agility. For example, our GenAI module was launched in two months, but our agentic AI module, which came after that, was launched in just two weeks. Learning has delivered tangible impact. We've been able to fill 60% of our open roles in the advanced technology organization with internal candidates. In addition, our data shows that we retain employees who learn through our development programs at a much higher rate than other employees, resulting in sustained client value and business continuity. The third tower of our talent strategy is productivity and innovation. This is something our clients know us really well for. We bring this to life internally under the umbrella of Client Zero to drive productivity within the company. Let me take the HR function as a proof point of this. We are investing in AI-enabled tools to provide a consumer-grade experience to our employees across the hire-to-retire lifecycle. For example, in hiring, we have deployed AI tools to provide better candidate matching and engagement. This has increased profile screening by 6x and reduced offer drops by as much as 30%. Our Chief Listening Officer today is an AI-powered conversationalist called Amber. She has helped us move away from the once-a-year traditional employee satisfaction survey to nearly 500,000 conversations a year. We can take action that is hyper-personalized and immediate, resulting in an industry-leading 85% positive employee sentiment. Employee engagement is a hugely critical metric for us, so much so that this is the only non-financial metric that determines the bonus pool for our CEO and our top leaders. Just within the HR function, we have 20 AI builders and 170 AI practitioners who bring this innovation to life within the function for our employees. At the same time, we've reduced our HR headcount by 10% and are targeting an overall reduction of 25% or more by the end of 2026. To summarize, we are dramatically transforming the organization in terms of our talent footprint. We are adding advanced technology talent and upskilling with speed and at scale. We are seeing early gains in productivity, and our differentiation is clear. It's the intersection of process and industry domain, advanced technology solutions, and client outcomes. This is the secret sauce that is not easy to replicate, and it comes from years of building a culture that values all three. It will help us grow revenue faster than headcount in the long term. That's how we deliver long-term value to our shareholders, and that's how we become indispensable to clients. With that, I'll hand it over to our CFO, Mike Weiner. Thanks, Piyush. You've heard a lot today about Genpact Next and how we're leveraging core business services as we accelerate growth in advanced technology solutions. I'll cover three topics. One, our performance over the last three years, which demonstrates the strength of our underlying business model and our ability to execute. Two, early momentum we've built in advanced technology solutions, which gives us confidence in our investment strategy to further accelerate growth. Three, how these elements come together to drive sustainable growth. Let's begin with our financial results over the last three years. From 2022- 2024, we grew revenue at a compounded annual growth rate of 6%. While our performance was above most of our market peers, we did not deliver fully on our potential in 2023. As a result, we adopted our 3+1 execution framework with a focus on partnerships, data tech and AI simplification, and Client Zero, which is the plus one in our 3+1 framework. Client Zero is designed to establish Genpact as its own best credential for data and AI-led transformation. The adoption of our 3+1 drove meaningful financial results in 2024, with revenue growth increasing from 2.4% in 2023 to 6.5% in 2024, largely driven by data tech and AI, including partner-related revenue. Profitability also improved at both the gross margin and operating margin level. Combined, adjusted diluted EPS grew faster than revenue. Over the period of 2022 to 2024, we generated $1.4 billion of free cash flow, returning 70% or $992 million to shareholders through share repurchases of $692 million and dividends of $300 million. We have increased our dividend every year since our program started eight years ago. We also delivered 380 basis points improvement in our ROIC. Looking closer at revenue over the last five quarters, data tech, AI, including partner-related and GenAI revenue, showed clear accelerated growth. Data tech and AI increased from 3% year- over- year in 1Q 2024 to 12% in 4Q 2024, with continued growth in 1Q 2025 at 11%. Partner-related revenue accelerated even more sharply from 30% year- over- year in 1Q 2024 to 86% in 4Q 2024, with continued strength in 1Q 2025 at 80%. The numbers of GenAI solutions in the market and GenAI revenue also accelerated significantly. In Q1 2024, we had 13 GenAI solutions either deployed or going live. That number grew to 145 by year-end. The momentum continued in Q1 2025 with 215 solutions in the market. In parallel, GenAI revenue increased nine times in Q1 2025 from Q1 2024. Now let's look at how core business services and advanced technology solutions revenue evolved over that same period. As we have discussed today, advanced technology solutions has four differentiated components: data and AI, digital technology, advisory, and agentic solutions. While our core business services consist of three components: decision support services, technology services, and digital operations. Here you can see the revenue from advanced technology solutions and core business services for 2024. Looking back over 2022 to 2024, advanced technology solutions grew 3% year- over- year in 2023 and 4% in 2024, which was certainly below our potential. In 2024, however, we defined our strategy, strengthened our leadership team, and started making significant investments. That has resulted in marked accelerated growth. When you take a look at a quarterly view, you can see that advanced technology solutions grew 15% on a year-over-year basis in Q4 2024 versus total revenue growth of 9%. Growth then accelerated to 16% in Q1 2025 versus total company growth of 7%. We expect to see further growth acceleration in Q2 2025 as well. This rapid acceleration in advanced technology solutions reflects a few key decisions. One, significant investments we're making across data, AI, sales, and partnerships. Two, the launch of agentic solutions, which was an important milestone. Although agentic adoption is still in the early stages, we expect it to contribute significantly in the future periods as well. Three, bringing advanced technology solutions together under one unified umbrella, driving improved execution. 20% of our revenue in 2024 was advanced technology solutions. This is higher value in a number of ways. One, it's approximately 70% annuitized, roughly in line with total revenue. Revenue per headcount is more than double Genpact in total. Advanced technology solutions has a higher mix of non-FTE revenue. Non-FTE revenue includes outcome and consumption-based contracts as well as fixed-fee contracts, the vast majority of them which are multi-year. As you can see here, approximately 70% of advanced technology solutions revenue is non-FTE versus 45% for Genpact as a whole. Going forward, we plan to make significant ongoing investments to further accelerate growth in advanced technology solutions, specifically in product development, sales, and partnerships. Turning to core business services, we're proud of the strong foundation we've built, reflecting our robust pipeline, deep process and domain experience, and the last-mile advantage, exceptionally strong client relationships, and a stable base of recurring revenue. We see a long runway of growth ahead with continued demand. Riju spoke about that, but I think it's worth underscoring. Every transaction we touch, every process we run generates deep operational insights we could lever to drive operational excellence. Core business services has three components: decision support services, technology services, and digital operations. These core services are fundamental to our business and are essential critical business processes for our clients. As Riju indicated, one of our most durable aspects of our business has been our ability to consistently deliver strong annual retention rates, net of productivity commitments. We expect this high revenue retention rate to continue to drive growth in our core business services due to higher transaction volumes, increased scope, or both, even as we rotate more of our core business services to advanced technology solutions. We have also expected increased revenue in core business services from new logos as we continue to meet clients where they are. As we actively manage the transition from core business services to advanced technology solutions, there are two key elements we think about: one, driving net revenue growth, and two, margin expansion. Jinsook highlighted what we are currently seeing as we rotate digital operations to advanced technology solutions for existing accounts. Increased scope, volume, or both are more than offsetting the increase in productivity commitments to date associated with the move to agentic solutions. At the same time, new client logos with embedded agentic AI and other advanced technology solutions are bringing incremental revenue. Combined, this will drive net revenue growth for Genpact with higher gross margins as well. We would expect this expansion to continue with the broader rotation of core business services to advanced technology solutions. Next, let's turn to organic investment approach and priorities. First, on talent, advanced technology solutions are more machine-led. As a result, we expect revenue growth to be faster than headcount growth over the long term. That said, the shift won't happen overnight, as mentioned earlier. We are making upfront investments to build and launch new solutions with significant investments in product development, sales, and partnerships. In addition to hiring critical talent, we're also making significant investments to upskill our current workforce. For strategic investments more broadly, we made significant investments in 2024 of $120 million in data and AI partnerships and sales that drove meaningful acceleration in revenue growth. We plan organic investment of more than $150 million in 2025 in these critical areas, driving future growth. Importantly, we are self-funding these strategic investments through gross margin expansion, disciplined cost management, allowing us to deliver improvements in adjusted operating income margins. Client Zero. In our effort to be our own best credential for AI-led transformation, we introduced Client Zero in 2024, identifying more than 50 AI solutions deployed or in production across IT, finance, HR, legal, sales, and marketing. These developments were focused on driving growth, improving employee satisfaction, reducing costs, and improving cash flow. These cases leverage many of the same advanced technology solutions we're implementing for our clients. In 2024, we delivered Client Zero and related simplification cost savings of approximately $19 million, allowing us to fund strategic investments while contributing to the overall adjusted operating margin expansion of 10 basis points in 2024. Incrementally, in 2025, we expect another $20 million of Client Zero and simplification-related cost savings. This will contribute to our expected 20 basis point increase in adjusted operating income margins while simultaneously funding strategic investments to drive accelerated growth. The effects of Client Zero and simplification have allowed us to optimize headcounts in support functions by nearly 10% through May of 2025, with more to come as we continue to implement our AI and agentic solutions. Now let's turn to key performance indicators. Going forward, we'll report additional metrics so you can track our performance on Genpact Next. In addition to our data tech and AI and digital operations revenue disaggregation, we will also report advanced technology solutions and core business services revenue on a quarterly basis. We will also be replacing our current outcome and consumption-based revenue metric with a more complete measure of non-FTE revenue that includes fixed fee. With regard to capital allocation, we continue to aim to return approximately 50% of cash flow to shareholders through a combination of share repurchases and dividends. We have increased our annual dividend every year since the program began in 2017. M&A will also be an important part of our long-term strategy. We regularly assess buy versus build with a focus on technology tokens that can accelerate our time to market. Our recent acquisition of Exponential Data is a great example of that. Before we get into our medium-term targets, I want to quickly talk about how our business is tracking in 2Q, as I know that's on everyone's mind. I'm happy to report today we are trending at or above the high end of our revenue guidance range for the second quarter. We would expect that performance to flow through the full year performance, moving us closer to the high end of our 2%-5% range for revenue. I look forward to providing you with more details when we release our second quarter update and updated outlook for full year in August. Now turning to our medium-term targets, which covers the period of 2026 and 2027. First, total revenue, we expect each year to grow at a minimum of 7% with a potential for significant upside from advanced technology solutions, which I'll discuss more in a moment. For core business services, we expect growth of 4%-5%. This factors in a gradual transition of core business services to advanced technology solutions. For advanced technology solutions, we expect growth at 15% at minimum. Our strong performance, broadening trends in the fast-growing data and AI markets, the size and growth of our pipeline, and significant investments we've made in data, AI, and partnerships together increase productivity commitments. Core business services and advanced technology solutions are expected to drive total revenue growth of at least 7% in 2026 and 2027. We continue to expect continued improvements in gross margin through 2027, with expected AOI margin expansion of approximately 25 basis points per year and significant free cash flow. Importantly, we expect just the diluted EPS to continue to grow double digits through 2027. In summary, we're incredibly excited about the future. We're confident that Genpact Next will accelerate innovation and growth, establishing Genpact as a leader in advanced technology solutions. We believe we are uniquely positioned as the last-mile experts with more than 25 years of deep domain and process experience, as reflected in the stable base of our core business services. Looking forward, we expect net revenue growth of 7% at least, with the potential for significant upsides as advanced technology solutions momentum continues to build. We expect revenue to grow faster than headcount over the long period of time, with self-funding of investments that have allowed us to drive accelerated revenue growth and consistent margin expansion. We're also committed to maintaining a strong track record of returning cash to shareholders, and we expect to drive double-digit growth in adjusted diluted EPS through 2027. With that, I look forward to taking your questions, and let's transition to the Q&A portion. Great. Thank you, everyone. We're now ready to go ahead and start Q&A. I'll just say that if you're in the room, please raise your hand if you'd like a microphone and wait until you get the microphone to speak so that we can capture the audio for people who are listening in over the webcast. Also, for those joining on the webcast, we welcome you to submit your questions at investor.day@genpact.com, and I'll be happy to read those out as time permits. With that, I think we're ready to go ahead and get started. Thank you, Bryan Bergin from TD Cowen. Appreciate all the detail today. Nice presentations. I guess the first one is pace of agentic adoption that you're assuming in the client base and the range of outcomes you've seen when you gave us that 3% uplift and the 300 basis points of gross margin expansion. I imagine that's a pretty wide range of what can happen. Can you just talk a little bit further on what you're assuming on the pace of adoption here and the range of outcomes relative to those average levels? Maybe, Mike, why don't you take the 3% conversation, and then Jinsook and I can talk about the pace of adoption. We'll do. We'll do. I'll answer your second one. Thank you for the question, Brian. When you think about it from that perspective, Jinsook gave you a highlight of what we've seen to date, right? I think the way we want to think about it is really price times quantity, right? When you think about it from the price perspective, we are delivering increased productivity and value to our clients, right? From the quantity perspective of it, we're showing, as we talked about, increased scope, volume, and/or both, right? What's interesting also is that as we do that, our costs go down in addition to what we're bringing on new logos. That's really the way we should think about it: increased price for our clients and productivity associated with it, really more than offset by what we're seeing in terms of the increased scope, volume, and new clients that are coming in. Again, early days, but we've seen adoption really pick up. Maybe just maybe I'll add, and I'll ask Jinsook for you. You are leading at the pace of adoption. I think to Mike's point, Brian, in the existing portfolio is what we refer to as 3% because of net accretion, including our costs are going down faster. Therefore, you see the 300 basis points improvement. Then addition of new logos is on the top. Just wanted to make sure that I talked about that. Thank you. Now new logos, existing, how's the pace, Jinsook? We've been, as I shared, we've been incredibly excited about the pace that it's really picking up. As you heard from our clients directly, Wesco, but also we posted online about Coca-Cola, our sales and services. There are named clients who are existing clients where we are starting with a really basis of strength, and they have continued to trust us in this journey. From the time that we officially made general availability GA in February, although we have been working with clients even the previous time period on the pre-beta and alpha stages, we are seeing the momentum, and that is what we are reporting out today with the numbers that you heard from myself and also Mike. We are still very early days, and we will continue to observe and discuss and with the client testimonials, but we are very excited about the journey that we have embarked on. Thank you, Brian. Next question. Hey, yes, I had some emails. Could you just, I am sorry, could you just wait to get the microphone? I am sorry. I just want to make sure we capture the apologies. Thank you. Thanks. Yeah, Vlad from Bank of Montreal. Appreciate the presentation. Your advanced tech solution growth pretty meaningfully improved in the past few quarters, and also noticed it's related to very strong partnership growth. Can you talk about sort of how partnerships impact that area of the business, where and how, if the improvement and growth are related at all, and sort of what your it's implied for partner-related strength in that 15% or more target over the next few years? Thanks. Vidya, do you want to take that? Yeah. When you think about partnerships, our partners bring core technology capability, and we bring to the table deep knowledge of process, data, and client business problems. When the two combine together, we are able to solve complex problems for clients and have solutions that meaningfully address those problems, and we sort of are able to deliver the outcomes over there. This is what brings the partners closer to us in domains which are differentiated versus the other companies that they currently deal with. That drives the acceleration for us in terms of partnerships. Yeah, maybe the only add that I'll have is that yes, partnership is helping us improve advanced technology solution adoption, but it is also, as an example, our last mile, or take an example of services, agentic solutions, or agentic solutions. A lot of these are our own IP that is also taking shape. Let me just add one more piece of that sort of purpose. We've also made significant investments, right? That is what we're really pleased about, right, is seeing the return on those investments really driving a lot of that in combination to everything else we just talked about. Thank you. Yeah. There was a question here and there. Yeah. Yeah. I see Dave coming here. Oh, there we go. Thank you. Yeah, thanks, guys. I guess my question to advanced tech solutions growing super fast now. Q2 of last year, it declined 2.9%. Just wondering, has something meaningfully changed in terms of recurring revenue, or what's, I guess, how volatile could that be, and maybe what happened a year ago? Yeah, maybe you want to take? I'll take that quickly. Look, I think first, all the investments that Mike was referring to, they started taking shape in a more concrete fashion, Dave and team, towards the middle of last year, point number one. You see certainly that last mile combined with advanced technologies started getting adopted by a lot of our trusted relationships. I think even if you see that and wanted to be transparent about the process, if you see on a gross, we said 20%, so roughly you can say, hey, it is $250 million. The difference is even keel about $4 million-$5 million in that quarter that went, was kind of a little bit down relative to year- over- year versus $40 million-%50 million higher in the next quarter. I think the difference is really stark and really pleased as to how we are progressing on advanced technology solutions. Even in this quarter, we see continued momentum. Thank you. Just one quick thought. The growth, the revenue growth is 7%+. Does that include a modest amount of acquisitions, or is that organic? It is all organic. It is all organic. Okay. Thank you. Here is a question here. Yeah. Thank you. Surinder Thind with Jefferies. Can you actually talk about the agentic component here and the construction of those solutions, meaning in the example that was given, where does Genpact come in in building that solution, and why is that something that maybe not a Salesforce can do with all of the investments that they're making in their agents? You hear that with SAP. Where is that boundary between Genpact and the software vendors, and how are you thinking about that? Great question. Surinder, do you want to take that? Sure. First and foremost, let me start that we are not actually setting out to build any foundational LLMs or SLMs, right? We are starting from the position of strength, and we stated that our strategy is that we're going to stay with always the domain-specific knowledge. When we build the LLMs and SLMs, we're not building on the exception handling that, for example, that I mentioned. Number one is that we're handling not regular exceptions. We're handling what we call level three exceptions. Level three means level one, the clients try to handle them, and then they pass on to the partner, that's level two, and still did not have the overall outcome. It comes to us. When we mention the exception handling, that's a level of knowledge, the level three exception handling that we are doing. The other thing is the rich data corpus based on our real-life operations. When we bring the expertise, the reason why we are building the solutions is based on the real-time experience and solving that level three exception handling that goes into the solution. That is the reason why we are building those on our own and bringing those outcomes to the clients. May I just kind of tangential point? I am a client. Yes. We have implemented the AP Suite in our own operations, right? I take great pride in running what I thought is a phenomenal operation. We have this in payables. 95% of it is fully automated, right? The last 5%, right? We do work. We have a team that is focused around it. We have implemented these solutions, right? We have dramatically reduced that 5% and increased the automation associated with it. Quite frankly, the quality that has come through, I will be frank with you, I was incredibly surprised how well this is working and the enhanced productivity it is giving me as a client. Thank you for being first dubious and then now giving testimonial as a client. I was a little skeptic. I'm going to be frank. It works. I think we have a question down here with Puneet in the first row. Thanks for hosting the event. Very informative. This is Puneet from JPMorgan. I wanted to ask about GigaFactory. It's been like a few months, five or six months since you launched that model. What's the response been like among your clients as well as your employees? Are you seeing employees excited or seeing some natural resistance to adopting this new different delivery model? Maybe I'll start, Jinsook. You and Sanjeev have been at the forefront of it. We'd love to have your reflections. I'll say, Puneet, three or four aspects. Number one, Sanjeev, as he mentioned in his prepared remarks, over 100 new leaders have joined our GigaFactory. That is because of the client validation that they have heard. We also reported just today that we have over 45 clients. We launched this in January. We have about 45 clients today. One of the clients you heard, GE Vernova, only a $35 billion company. As to the results they are getting from GigaFactory. Three, I think given the Genome piece that Piyush talked about is one of the core builder elements that is part of GigaFactory that trains our people and also clients' people. I think it is really a very strong posture overall in our sector, in our industry. Jinsook? First and foremost, the training hours talk for themselves for two reasons. One is these are trainings that are available through the Genome that people are taking, but we also have proprietary training because of the agents, because of the domain knowledge, and those are oversubscribed. Because we want to give the employees the hands-on training, and then when you are talking about these people who go back to their desk, they are going to be actually training and working on them. That is number one. There has been super excitement about those trainings that Sanjeev and I have been working on. The second thing is what I covered at the roadmap. Our agents are not only about the domain-specific on the industry verticals and horizontals. They are also about the AI Gigafactory because that is the mechanism by which our people are going to deliver code generators. When you are looking at the enterprise risk management, whether you are looking at the agent productivity, all those things are actually being built and also managed by people. That is the second thing that really excites our people. The third is this. I talked about the parallel work streams, and this is critical. The reason being is in the AI Gigafactory, it's not about just today. Because if we talk just today to the clients, it's BK says, "That's already a yesterday story." We need to talk tomorrow, even with our employees. Working on these parallel work streams, talking about the agentic AI ecosystem, talking about the orchestration agents, talking about the agents that, oh, it's not only about the domain-specific in the industry and verticals, but it's also about how we deliver in AI Gigafactory. It's what's making difference and why you see the training hours from Piyush, why you see the numbers and outlook that actually BK and Mike are giving. Patrick, nothing good. If I can ask one more. Digital operations is give or take $2.5 billion in revenue. I understand there will be work that will transition from digital operations into agentic bucket over time. What does the outlook assume, like the 15% growth for advanced technology solutions and mid-single-digit growth for the remaining bucket? What does that assume for how much of work will transition from digital operations to agentic on an annual basis or maybe over the next three or four years? Is there a way to think about how fast adoption of agentic will be? Maybe I'll take that. Look, I think overall, I'll make three or four assertions, Puneet. Point number one, we are driving this, the point that you are making, this intentional disruption where at the last mile, we are bringing all of this innovation, bringing these advanced technologies. Having said that, I'll tell you, with all the experience in the marketplace, it is a gradual, long-term journey. We got to meet our clients where they are. As I look at the pipeline of even core business services, it continues to be very, very strong because a lot of clients, as both Sanjeev and I were talking about, their data is not ready. Systems are fragmented. You certainly just cannot jump through. They see the innovation, but I think they have to go through the process. It is a longer-term journey of, and I think the last point I'll make, that typical taking an example of call center, that those kind of businesses, and you saw the breadth of the work that we do. You heard possibly a number of our clients' stories, be it Penske or Unilever and all of these. Things like call center are the minimal part of Genpact. We handle more complex operations in core business services. Yes, we have assumed that rotation. We are, and to Brian's question earlier, we're seeing good adoption. We want faster adoption. I think advanced technology solution being data and AI-rich, data, AI, GenAI, Core AI, these are also a strong suite of Genpact for a pretty long time. With fueling of investments, it's taking off in a pretty significant way. Yeah, just one thing if I can top up to that, BK. If you also think about it, in our digital operations and many parts of the business, it's highly annuitized, right? It is not uncommon to have a five-year contract that's there, right? It's a highly durable base, right, that will rotate. Again, a lot is going to be driven where the client is and their comfortability of it, right? We're seeing demand on both sides. Maybe while we're waiting for the microphone to arrive here, I'll ask one question that's come in over email. This is about Exponential and M&A more broadly. First, it asks about the strategic rationale behind the Exponential acquisition, and then also how to think about the pivot of the company towards advanced technology solutions and whether that might lead to greater appetite for M&A in the future. Why don't I take that and then I'll pass on to you. First and foremost, M&A is definitely part of our strategy. When we do that, it's actually a talking strategy focused on how it is going to strengthen our capabilities and accelerate our capabilities. In Exponential's case, they are a data powerhouse. They are a Databricks partner, and they're working with Snowflake. They are ones who actually, when they come into clients, they work on data modernization, getting the data ready as fast as possible with a domain-specific, going back to the same theme that we had. That was the rationale for kind of company that we are getting into Exponential. Yeah, a few comments. Our capital allocation strategy is very clearly articulated in terms of what we are able to do. Buying token capability-related acquisitions has never left our capital allocation. The key for us is we do not buy revenue, right? From an M&A perspective, we are buying capabilities that we think we make a business decision on buy versus build for those capabilities, which are going to be incredibly important for us as we continue to make the pivot for advanced technology solutions. Thanks. Thank you, guys. Thank you so much for the presentation. This is Brendan from Puneet's team at JPMorgan. I would love to ask about the build side of the buy versus build discussion that you just discussed. Could you help put a finer point on where the $150 million of investments is going? I think self-funding it is great and exciting. Just help us understand for us silly finance people what kind of things you're actually going to spend that money on. Thank you. Maybe I'll take that and you guys can add. Look, I think a lot of the build side is in talent, is in models, is in agentic solutions. For example, a lot of these agentic solutions to Surinder's question earlier, it is, again, we are building at last mile. We are not building what Microsoft has done, Salesforce has done, ServiceNow has done. We are building the last mile repeatable IP, our own IP. That's where a lot of these investments are going. Thank you. I think Surinder here in the second row. Thank you. Thank you. Just a big picture question about the medium-term growth framework. When you talk about 7%, how did you actually come up with that number? Is that relative to what you think an industry is going to grow? Help us understand that because when you look at your prior framework, you obviously grew above the industry average despite not hitting the target, maybe the absolute target that you wanted. How should we think about that 7% and all the components that make that up, the assumptions underlying that? Since you said big picture, Surinder, I'll start from a big picture and then pass it on to you, Mike. Look, I think I hope you all felt the change in the strategy today, Surinder and team. As we came together as a new leadership team with a very strong foundation, core of our strategy is leverage what we are known for best, last mile expertise, and apply advanced technologies at speed there. That is where you see the turn in advanced technology. It is already 20% of our franchise growing in mid-teens and hopefully much better. That is really powering our growth. Point number two, core business services, as I mentioned earlier, continues to be a very strong foundation because as we are talking to many of our clients, they will take it'll be a period of time before they adopt advanced technology solution full scale. They might adopt in different parts of the organization. Really feel good about how we are powering it with advanced technology solution. That is why I think one of the specific terms that Mike used, and I completely back, is at least, but I will give it to you. I think we have demonstrated, because I also do not want, I will say this openly because I say this internally, I do not want numbers to get ahead of our story. I do not want numbers to get ahead of our story and want to be prudent about it. Fundamentally, we have demonstrated that we have been at the top quartile of the growth in our cohort. Mike? Yeah, a few things. I am going to repeat. These are medium-term targets for 2026 and 2027, and it is at least, right? We went through a very disciplined process with the leadership team of the company that when we really thought about our business from an advanced technology solutions perspective and a core perspective on what we're seeing and how we're leveraging the pipeline that we're sitting on right now and where we think we can take it at a minimum, which is the 7% for 2026 and 2027. The most important is how confident we are in that. I think that's what BK was just trying to allude to now. It's not that the numbers get ahead of ourselves. We're building a long-term sustainable growth franchise that's generating tremendous amount of cash flow for us as an organization, for our shareholders. What's also really interesting about the company is our ability to deliver that double-digit EPS growth that I talked about in my comments with that 7% with increased margins as well. The free cash flow is part of the model. Yes. Sorry. We have a couple of questions here. First of all, thank you for a great event and congrats on laying out a very clear path to double-digit profit growth. You mentioned that you expect revenue to grow faster than headcount going forward. I know for you guys as well as for the industry, that kind of has not been the case historically. Could you just elaborate a little bit on sort of why this time is different and why we should expect to see an expansion of revenue per head going forward? Maybe I'll kick off. I think, again, I'll pivot ourselves to advanced technology solutions. It has already demonstrated, and we shared with you, revenue per headcount greater than 2x the company average. We are seeing increased momentum there. I must again continue to emphasize early days, but we clearly see the trend building up. In all of our solutions, newer solutions, existing franchise, when we are bringing this innovation at the point of execution, I really feel good about that. Certainly in long term, you will see that. I think I do want to underscore that we are in our invest cycle and therefore also investing to get and acquire more and more data and AI skills. That might be a little bit more in medium term, but really, really feel good. I think even the Genome.AI piece, it's really priced as at our training platform, is shaping our overall global talent. And they are adopting the AI skills, data skills that is also acting as initial days, a good productivity level. So again, just reemphasize as BK just talked about. We've carefully chosen our words and we said long term, right? Because we're very cognizant of the investment cycle that we're in now that we're self-funding, right? That potentially can manifest itself with some changes associated with it, right? But we still have a very variable, very strong, durable base of our core business services that is growing, right? We expect that to continue to rotate. And that will also affect the decoupling of the revenue and FTE, right? But again, we're very much focused on, again, the revenue growth and the bottom line expansion is key for us. Thanks. On the margin side here, as you have positive mix shift, you have gross margin improvement. You have given us an operating margin expansion within the medium-term framework. Is it too simplistic to think the gross margin expansion should be higher than that so that that funds, or effectively funds, the S&M and development expenses in the income statement, or will it be more variable than that? I am surprised it took this long, but the near-term commentary that you had on 2Q, is that better anticipated in performance? Is it due to greater execution on the base business? Is it due to you signing some of those deals that were stuck in the pipe? Combination of both, anything you could share there? Yeah, let me answer the first one first. The second one first, excuse me, right? On the second quarter, you're 100% right in terms of our ability to execute, right? In addition to it, we had a, when we last talked in our performance, we had some delays and some large deals. One of those deals have closed, right? I can report today the other deals that were delayed, we still feel really good about them. In addition to that, we had some newer large deals that came into our business. We feel good about how we're going to come in for the quarter, right? We also alluded to how we're going to flow that through for the full year, right? Your second question or your first question? Gross margin. Gross margin. Yeah, if you want to think about it, right? We have been expanding our gross margin at a faster pace than our adjusted operating income margin, right? And really the delta of that is the self-funding of the investments. So we carefully monitor and manage that. So while we have not given out any specific targets associated with our commitments in terms of our gross margin expansion, but that is probably a good way to think about it. But I want to again reiterate, for 2026 and 2027, we expect our adjusted operating income margin to expand 25 basis points per year on top of what we will deliver in 2025. Okay. And I will take another question from email. I think, Riju, this one might be for you around mid-market specifically and just giving a little more detail on your strategy as you go after mid-market clients, how to think about what would allow you to scale that business where others may be in the industry historically have had difficulty in scaling that business in a way that worked particularly well. If you could talk, double-click on the mid-market piece specifically. Mid-market industry, I mean, we studied this segment carefully. As BK said, we want to meet our clients where they are. These companies are early in their maturity cycle and are still scaling. They need partners who understand their challenges. They also do not have large procurement functions or large transformation functions who can handle them through this journey. They need a trusted partner who understands their journey and can walk with them through the process. The third is they need a partner who gives outcomes and they are assured of the outcomes. As we studied this, our mid-market levers are therefore building solutions which are built for one, but can cater to many with some last mile configuration, ability to flex the commercial models in line with their scaling. Third, a sales team which is focused on their specific needs and can empathize and understand how they will bridge their journey and help them scale. Those elements we believe set us up for success. You heard from Advantage Solutions how we came together to understand their exact business challenge, worked with Salesforce to create a platform. There are many such examples. Thank you. Riju, if I may add, I think what we collectively hear when we are on our beat in the market is the outcome orientation that we have, which is very endearing. Do you want to speak about that too? Sorry. Yeah, that was my second point that they want partners who give them assurance of outcomes. We have been a partner to most of, I mean, to all of our clients where we have stood by our promises and delivered to the outcomes. That is our reputation in the market. Hi, Puneet from JPMorgan. Thanks for doing this again. I wanted to ask about this 3% revenue increase metric that you shared today when work moves from current model to an AI-based model. What drives that 3% growth? I know you talked about how it will be more processes, more transactions, but who's handling those processes or transactions right now? Where will that shift come from? Who's going to lose in that equation? Okay. I think Mike spoke about that. It's a great question, Puneet. I think I'll just roll from the top. It is more for existing accounts first, point number one. I think a simple way to think about it is P times Q. Price advantage we are giving, put higher productivity to our clients. Q is, which is increase in scope or in volume or both. I think now that's the point where you're asking that, hey, who is losing or whichever way? I think there are various ways to think about it. Point number one, whenever we onboard and you saw many of these clients, Unilever said, we started with this, then we went here, then we went here. A lot of times, or Wesco, they will start maybe in the corporate or in the US. And they are in 50 countries. The adoption takes time in 20, 30, 40, 50 billion companies. That is kind of point number one of volume scope. Sometimes now with these solutions, we have brought in a lot more. One other example we took where they switched the software to Genpact. Some other software player could be the domain player. We gained that market share. I think those are the examples that we are seeing. I'll continue to say early days, but really feel good about that. There was actually a related question that came in over email, which I'll just ask on this topic, which is, what's the level of assumption you've built going forward in the mid-term model around net revenue growth on Agentic? How are you thinking about, will it stay at that 3% net revenue growth going forward? Is that the assumption that's built in? Or is there a different assumption that's been built into the target? You want to take that? Sure. The 3% was an illustrative example of what we've seen thus far with the data. That was really about AP Suite. I think we've made very prudent and conservative assumptions about how the rotation will be, how it will impact our revenue, and how it will impact our margin. Can you dig a little bit deeper on the conversations you're having with clients on shifting to more of an outcome-based model? How big or a large percentage of your revenues do you think you can get to? Is there a structural limit? Is it just partnership? At some point, is there a scale where they don't want to share the economics of an outcome? Do you want to start, Riju? When we think of, let's say, non-FTE models, we think of three different ways. It could be fixed price. It could be transaction-based. It could be outcome or value-based. The industry has traditionally sort of focused on FTE-based because it gives you assurance of cost for the client. Therefore, there has been sort of slow movement out of it. As we are moving to Agentic solutions and advanced technology solutions, we are seeing a shift to first fixed price and transaction-based before it becomes outcomes. That itself is a bigger shift from where our clients are starting. We will continue to see acceleration of that because, as we talked earlier, in this P versus Q equation, it is actually valuable for both parties. Maybe if I will add to Riju, Surinder. Today, in the entire book of roughly $4.5 billion, it is 45% as we reported today in all of these models. Advanced technology solutions is already 70%. More is happening in that direction, point number one. We really feel good that this momentum, especially with advanced technology solution becoming bigger and bigger portion, we will see the momentum happen. I think the one caveat that I certainly want to, with all the experience with clients, we also deal with a lot of regulated industries. In a lot of different specific parts of the regulated industry, they want to have visibility to what is the headcount and so on and so forth. I think increasingly, as our solutions become more Agentic, more advanced technology-led, more machine-led, more and more momentum you will see in that direction. Hey, team, thanks again. What can you share on the big deals as it relates to mix of the advanced technology solutions? How is that similar or different to the mix in the base that you shared that's roughly 80/20? Thanks. Maybe I'll take that, and Riju, if you wish to add. Overall, again, across cohorts of deals, including large deals, we are seeing early days, strong adoption of advanced technology solutions. As we are baking in and as we are seeing this intersection of execution and innovation, last mile and advanced technologies, we are seeing a further adoption by clients. I must also say that we are a large company, so a lot of our people are also learning about it as we are progressing. We really feel good about that moment. If I were to add, clients want to create their operations, which are more Agentic, more data and AI-led. We have the reputation of being a company that has delivered outcomes. When you marry the two together and when they look at their deals, they are more assured of getting not a piece of technology, but a real outcome from that technology powered by advanced technology solutions. One last point. When we talk about large deals in our organization, these are deals that are $50 million or greater. There isn't an industry standard definition of that. I just want everyone to think about it within that context. I'll ask about client zero and your willingness to experiment with client zero here. Can you talk about the stuff that maybe hasn't worked? Or when we think about all of the industry commentary out there, some will say 30% of proposed proof of concepts haven't worked. Others have higher numbers. How are you guys handling that internally? What has worked? What hasn't really worked? Obviously, what works comes into the marketplace. How are you guys working through some of those challenges? I'll tell you what didn't work initially. We had skeptics in the room. They came from some different industries, like insurance or whatever, on a more serious note. Look, I think at the end of the day, Surinder and team, we are a process company. We are a data company. So we had, to begin with, a very strong foundation. I think you are exactly right. This is what we experience with our clients a lot, where data is not structured, business and IT do not work, fragmented systems, so on and so forth. Which does not mean that we have not had learning. We have had many learnings. And you have been champion of that, and you can enunciate a few. Overall, I think we just needed to, and that was another area to earlier question of our pouring investments there, because at least we had a collective belief that if we cannot demonstrate as the best credential, bar none, not in our industry, bar none, then we do not have any right to go to any of our clients. I think now those clients are actually listening to, actually, now he goes and pitches to CFOs as to what, I mean, we are still a small company, but what has happened in closed cycle, you have seen some cash acceleration in our time to build. All of those are results of client zero. Any examples, Jessica? From a strategic perspective, this was very deliberate. Number one is because we are starting from, again, going back to the theme of position of strength. What are we known for? Six Sigma. The idea is that the continuous improvement is there. We iterate and iterate because leading to second one, which was we are about going from factory to production. Why do clients stick with us? Even on a multi-year contract, they continue to renew, not automatically, but actually having gone out to the RFP and bid is because when it comes out of the Genpact factory, it goes through client zero first. We are walking the talk. We are using it. That means that we iterated multiple times, multiple times. Failure is embedded in it. I always tell my team, fail forward. Failure is guaranteed. Just fail forward. Positioning ourselves and having doubting Thomases like Mike really helps us because that client zero experience, then when the clients ask us, and I literally had a couple of CFOs ask me, where is this working right here? We can tell you what it is. Then I can have that credibility to bring that on. From Six Sigma, where that is the culture of the company, we're tinkerers in making sure that it works, then getting to the last mile and to embed the client zero is where we are experimenting. We go from market perspective, factory to production. One last thing. I think when you think about this, leadership is key. I run a function. Piyush runs a function. Coupling that with investments and the ability to challenge the folks that are doing certain things, is there another way to look at it? We've made a huge investment in this company in terms of general AI skill knowledge, tools that we have there, and that ability test in your environment. It's OK to fail. That has to be supported by investments and leadership. We are surprised every single day when we go, hold on a minute. Before we go and do this or hire for this, is there a way we can automate? Is there a technology out there? We are supported by investments and a team that does it, in addition to the products and services that we are developing today for our clients. We are seeing meaningful impact. Piyush talked about what he is seeing just in terms of simplification related in HR function. It is really quite powerful. Thank you. Thank you, Surinder. Great. We are almost out of time. If I could fit one more in from email, if you do not mind, and then I think we can close, unless there are any other raised hands. The very last one of our email is really around longer-term AOI margin potential. There are some peers in the industry that have higher margins than Genpact. The question is whether or not there is really any structural reason that we feel Genpact cannot raise margins to those levels. The way I articulated today, and for 2026 and for 2027, our medium-term targets are 25 basis points per year on top of what we deliver in 2025. There is nothing structural that will not prevent us from potentially doing more, particularly with the focus as we rotate into Agentic solutions. You heard us talk about some of the metrics associated with profitability associated with that. We are focused on the medium term right now. We are also super focused on delivering those outcomes and self-funding the investments that are going to drive this pivotal shift in the company to advanced technology solutions. Great. Thank you. Thank you, Mike. I will turn it back over to you, BK, for. First of all, thank you for engaging Q&A. We hope you leave the room with a strong sense of our vision and the bold pivot that is reshaping Genpact as an AI-first company. We are intentionally disrupting ourselves, scaling advanced technology solutions on the foundation of core business services, and driving accelerated growth and expanding margins. We are building tomorrow's Genpact today for our clients, our people, and our shareholders through Genpact Next. I want to take a moment to thank our global teams, whose relentless focus on clients truly makes this possible and for all of your trust and partnership. For those who are joining in person here, first of all, thanks. Join us at the networking reception and meet our teams and a few of our partners are here. I think this session then ends as a formal for our webcast. Is that fair? Yeah, this formally concludes. Thank you all for your time. It's great to see you. We look forward to connecting at the event. Thank you.