Happiest Minds Technologies Limited (HAPPSTMNDS) Q4 2026 Earnings Call Transcript

Ladies and gentlemen, good day and welcome to Happiest Minds Technologies Ltd. Q4F526 Earnings Conference Call, hosted by HDFC Securities Ltd. As a reminder, all participant lines will be in the lesson only mode, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during the conference call, please signal an operator by pressing star and zero on your touchstone phone. Please note that this conference is being recorded. I now have the conference over to Mr. Vinay Ishwala from my CFC Securities Limited. Thank you, and over to you, Mr. Wala.

Good morning, ladies and gentlemen. Thank you for joining us today on the Q4 Earnings Call of FPS Minds Technologies Limited. On behalf of HGFC Securities, I would like to thank the management of FPS Minds for giving us the opportunity to host this call. Today we have with us Mr. Joseph Anantaraju, Co-Chairman and CEO, Mr. Venkatraman Narayan, Managing Director, Mr. Ram Mohan, CEO, Infrastructure Management and Security Services Business, Mr. Sridhar Manta, CEO, Generative AI Business Services, Mr. Praveen Darshankar, Company Secretary and Compliance Officer. Mr. Anand Balakrishnan, CFO. Ms. Priyanka Sharma, Head Investor Reagulation. I will now hand over to Priyanka Sharma for the safe harbor statement and to take the proceedings forward. Thank you, and over to you, Priyanka.

Thank you, Vinice.

Good morning to all participants on the call, and welcome to the conference call to discuss the financial results for the fourth quarter and year-ended March 31st, 2026. I'm Priyanka Sharma, Head of Investor Relations. We hope you have had an opportunity to review the earnings release. issued yesterday. Now let me quickly walk you through the agenda for today's call. Joseph will begin by sharing his perspectives on the business environment, our strategic priorities, and overall business performance. Sridhar will touch upon our enterprise AI platform, AI-led transformation initiatives, and progress around Gen AI-led engagements and capabilities. Thereafter, Mr. Venkat will walk you through the financial and operational performance for the quarter and full year, followed by our outlook for FY27. Following the management commentary, we'll open the floor for questions. Before we begin, let me read the safe harbor statement. During this call, we may make forward-looking statements. These statements reflect the environment we see as of today and involve risks and uncertainties that could cause actual results to differ materially. We do not undertake any obligation to update these statements periodically. With that, let me now hand it over to Joseph.

Thank you, Priyanka. Good morning, everyone, and thank you for joining us today. FI26 was an important year for Happiest Minds Technologies from both a business and strategic standpoint. We delivered healthy growth, sustained strong profitability, improved utilization, crossed 300 active customers, took several platforms to market, and further strengthened our positioning as an AI-first digital engineering partner. FI 26 also marked 15 years since the founding of Happiest Minds, a proud milestone, giving us an opportunity to reflect on the journey so far, and more importantly, the opportunities ahead. Let me start with a quick view on the market. The year continued to be shaped by a mixed macroeconomic environment. While discretionary spending remains selective in some of the traditional areas, We saw increasing momentum and budget allocation in AI-led business transformation, modernization, automation of internal processes, and productivity-focused programs. AI and GenAI are now central to most customer conversations, and this is translating into happiest minds being viewed as a strategic partner, strong customer engagement, robust pipeline growth, and improving conversion visibility. There also has been increasing discussion around platform companies entering the services arena. Our view remains clear. We see this as a positive structural shift for the industry and for happiest minds. Historically, when platform companies such as SAP and Microsoft expanded into services, it spurred further demand and created significantly larger opportunities for the broader IT services ecosystem. Platform providers often generate demand through co-innovation and partnership programs and have traditionally relied on partners for scale and execution. Turning to performance, FI26 revenues crossed 2,315 crores, representing a year-on-year growth of 12.3% in INR terms, while the constant currency growth for the year came in at 9.27%, which is among the higher growth rates in the industry. EBITDA margins remain within a guided range of 20% to 22%, despite continued investments in AI capabilities, platforms, sales, expansion, and future-ready talent. From a customer standpoint, we ended FI26 with 306 active customers, including 51 additions during the year, reflecting the success of our NN strategy. We also continue to deepen engagement across large enterprise accounts and today serve over $91 billion corporations globally. Importantly, during Q4, we saw a record pipeline growth of 27%, which gives us increasing confidence in our FI27 outlook. Based on this momentum, the board has reconfirmed FI27 growth guidance of 12.5%, while we continue to remain aspirational About a 15% growth trajectory. This is reflected in the planned hunt count of 1,050 for F527, with the bulk of hiring taking place in the Genitive AI business unit and the analytics and AI COE. Over the last few quarters, we have spoken about our early investments around Gen AI and our broader AI first strategy, which Sridhar will expound further on. During F526, we saw this translate more meaningfully into scaled engagements, customer adoption, and stronger pipeline momentum. And enterprises today are increasingly looking for partners who can help them move AI initiatives from experimentation towards measurable business outcomes, and that is where Happiest Minds is seeing strong relevance. Based on our internal innovation initiatives and experience implementing AI strategies for our customers, we recently announced the launch of our Enterprise AI platform. The platform is designed to help enterprises accelerate their adoption in a secure, scalable, and enterprise-ready manner while reducing execution complexity and implementation risk. The overall momentum buildup was also reflected in several strategic wins during the quarter, including engagements such as a U.S.-based insurance and financial service provider for product engineering services, a global warehouse automation leader for engineering and security applications, and a European healthcare software company for modernization of its hospital management platform. Shriva will talk a little bit about some of our experiences in the AI space. From a vertical perspective, growth during the year was led by BFSI and Healthcare and Life Sciences, both of which continue to see strong momentum, driven by AI-led transformation, digital engineering, and modernization programs. Retail and travel, media and entertainment verticals also delivered steady growth during the year, while industrial remained stable. We are additionally seeing signs of revival in the education sector, driven by Gen A adoption, which we are capitalizing on with our EduV platform, Repeatable Solutions. Geographically, the U.S. remained the largest market with healthy momentum across AI-led transformation and modernization programs while India, Europe, and the rest of the world all showed good growth during the year. We also strengthened our leadership team during the quarter with the addition of Prathmesh Kulkarni as Executive Vice President to lead our BFSI, Healthcare and Life Sciences, and retain CPG verticals. We have Suresh Chatur, who joined us as the Digital Post Automation COE Head, Siddharth Dandapani to spearhead our GCC business, and Samarjit Singh as Vice President of our newly launched SAP Center of Excellence. Overall, we are entering FI27 with stronger strategic positioning, a strong pipeline, healthy order book, and momentum across customers and markets. We believe the convergence of AI, engineering, modernization, and automation is expanding the digital transformation opportunity, and Happiest Minds remains well positioned to participate meaningfully and take advantage of the opportunities offered by this evolving landscape. With that, let me hand it over to Sridhar to share more details on our AIFS strategy and the enterprise AI platform. Sridhar, over to you.

Thank you very much, Joseph, and good morning, everyone. Over the last year, of course, as all of us are observing, enterprise have moved decisively from AI experimentation towards scale deployment. The challenge today is not access to the AI models or the quality of the AI models, but integrating AI securely into the enterprise workflows and driving measurable operational outcomes. That's precisely where our enterprise AI platform is focused. The platform brings together intelligent agents out of the box and orchestration capabilities with all the agents that exist as well as get developed, governance framework for security and guardrails, and reusable engineering components into a completely unified enterprise-ready architecture. We are leveraging our experience in building multiple AI solutions for customers and our repeatable solutions experience over the last several years to create a customizable platform for our clients across multiple verticals. We are seeing increasing traction across AI-assisted software engineering, AI-led modernization, intelligent automation, infrastructure optimization, leveraging AI, and AI workflows within cybersecurity operations and enterprise co-pilots. We are also working on merging hybrid coding paradigm, combining the coding agents with the human developers, creating a meaningful opportunity for enterprises to modernize complex legacy environments in a more efficient and lower risk manner while driving productivity improvements. As shared last quarter through our AI for strategy, we continue to add more generative AI and agentic AI use cases that have moved beyond prototypes, as Joseph mentioned, into scaled customer engagements with several demonstrating replicable sales potential across customer accounts and industry verticals. And today, we have 50 use cases identified and already implemented. We are also increasingly embedding agentic AI frameworks into enterprise workflows where autonomous and semi-autonomous systems can improve operational efficiency while maintaining governance and human oversight. I'll give a quick view about three new wins we started working as well as delivered in some scenarios we had last quarter that illustrate the kind of projects that we are currently working in the AI space. We won a project from a bottling company in Africa where we had to also create necessary digital infrastructure so that we can actually leverage the AI in terms of IoT enabling their coolers and then creating the agentic AI solution addressing asset performance optimization. The solution basically analyzes the efficiency of all their coolers and makes the necessary recommendations like reallocation of some coolers, which in turn saves money through effective utilization. So this is an example where customer wants to leverage AI, but we have to actually create the necessary digital infrastructure as IoT sensors,

et cetera, for their hardware devices and coolers.

The second example I would like to talk about is for a large automobile company in India, we're actually creating an agentic infrastructure because a lot of times before we actually start creating agentic solutions, we need to actually rely upon the enterprise systems for data and information so that the agents on the top can actually leverage that information to create more intelligent applications. So we actually are creating MCP servers wrapping their 900 APIs so that new agentic AI solutions can be developed. So this is an example where creating the necessary agentic infrastructure for the new agentic solutions to be further developed. The third and last example I want to talk about is for one of the largest CPG companies, and they want to create a marketing survey application for a new product they were planning to launch. And traditional software development methods require six months to build such an application, and they were under tremendous time pressure because the product has to be launched quickly so that in the malls, people can actually test the products and all the survey information can be entered through application, et cetera. We leveraged our RelayBuild, which is an agentic SDLC tool that can significantly accelerate the software development by using cloud agents and other technologies. So we won this project because we are able to actually complete the project in three months and deliver to the customer. These are three distinct examples of various kinds of AI projects in terms of agentic infrastructure, digital infrastructure, as well as complex AI solution. And also in line with our AI first strategy, we'll continue to invest across AI capabilities within the organization, as well as platforms, accelerators, and of course, the most important one is the talent. And as part of this effort, we are in the progress of building a dedicated thousand AI and generative AI focused team by end of FI27 to support growing customers' demand to build generative AI solutions. Of course, in terms of the AI productivity, we are targeting towards all of our workforce to be trained, and of course, we already started adopting various AI productivity tools. With multiple client projects, and our goal is to reach 90% of all our engineers, testers, and all service delivery personnel will be trained and will start using effectively AI tools in the productivity space by 90% by the end of FI27. Overall, our focus remains clear, helping enterprises to deploy AI safely, responsibly, and at scale while delivering measurable business outcomes. With that, I now hand it over to Venkat.

Thank you, Sridhar.

Good morning, everyone. What I'll do in the next few minutes is give you a highlight of our financial and operation performance for the quarter and the year that ended on March 31st, 2026. Starting with our fourth quarter performance, our revenues in Conscient Currency grew 0.5% sequentially and 6.4% year-over-year. Operating revenues for the quarter was $604 crores, a sequential growth of 2.8% and approximately 11% year-over-year. Total income, which is operating income plus other income, was $621 crores, a sequential growth of 3.1% and 9% sequentially and year-over-year. It's pertinent to note here that we have grown every quarter since our IPO and most importantly, on a profitable basis. As you will all be aware, the last quarter was one of fluctuations, be it currency, geopolitical situations, or technology changes. However, I am happy to say that we have managed to navigate these very well and continue to grow. Here I would be remiss if I did not say that our industry has also pulled it off decently well. With the fourth quarter behind us and almost two months into the new year, we are now looking forward to the new year with optimism and vigor. We are putting all our energy and focus into meeting our guided growth of 12.5% in Conscient Currency for the next year. Operating margin for the quarter remains stable at 106 crores and 17.5% of revenue. Investments made in GBS, our AI-first strategy, and our new sales engine have helped deepen our existing customer relationships while helping open many new doors. The GBS unit now contributes almost 3.3% of our revenues while improving on its profitability metrics. At the risk of repetition, I should mention that GBS is our AI innovation engine, while AI and AI-led services are now a dominant part of our overall business. To make this amply clear, in the coming months, we'll be reporting on a metric that is revenue from AI-led services. We will also, in the coming months, begin reporting on pricing models, which reflect our AI-first approach and AI-led business, as distinct from what we call out today under contracts model, namely revenue split by time and materials or fixed price. This is a much-needed clarification, as markets tend to mix these two distinct terms. Turning to some of the operational metrics, we continue to maintain... Strong utilization numbers, and we are at about 81% compared to 77.4% in the previous year in the same quarter. PAT for the quarter at 61 crores has shown a significant improvement over the previous year and the previous quarter. However, to be consistent with what I have been talking about until now, our adjusted PAT, which is PAT adjusted for exceptional items and intangibles, was 72 crores, and it stood at 11.5% of our total income, showing growth both sequentially and year-over-year. On working capital, DSO increased marginally to 94 days from the 92 that we were earlier on, and we should bring that back through accelerated post-quarter collections. Coming to the full year performance, Operating revenue was 2,315 crores, representing a year-over-year growth of 12.3%. Growth in constant currency came in at 9.2%, slightly below our guidance that we had made for the year of 10%, primarily driven by a delay in the ride-shifting of a couple of our Artha license deals. This also impacted our fourth quarter growth. Efforts are underway to close these right-shifted deals in the first quarter of the current year. Total income for the year stood at 2,400 crores, which I must say has a nice ring to it as a number. Growth on discount was 11%. Operating margin was 17.4% versus 17.3% in the previous year, and at 401 crores, it has grown 12.3%. So, the 17.4% and thereabouts has been largely in line with previous year. While I spoke about our growth guidance for FI27, Our expectations on operating margin, though we are not calling it as a guidance, is to improve the same by about 100 basis points. That means about 17.5 to 18.5 on operating margin is what we are seeking to achieve. We will be driving this on the back of improved utilization, execution discipline, and efficiencies that come from integrating acquired entities while continuing to make investments in our AI initiatives. Utilization for the year remained above 81% compared to the 77% in the previous year. PAT for the year at 213 crores has shown a growth of 15% over the previous year. I'm not comparing it with the previous quarter because we had certain exceptional items. Adjusted PAT came in at 279 crores, or 11.61%, showing a growth of 9.4% of the previous year. From a customer perspective, we ended the year with 306 active customers, that is 51 additions during the year. I would like to draw attention to our billion-dollar clients, which has grown from 82 to 91. Very interesting to know that this cohort continues to contribute almost 58% of our revenue, giving you a good insight into our quality of earnings. We ended the year with about 6,500 happiest minds, a slight drop from the previous year. While attrition has been high at 17%, it is not unmanageable. It is within the region that we have been seeing a trend over the past couple of quarters. From a balance sheet standpoint, we continue to maintain a healthy financial position with robust cash flows, generating sufficient liquidity and flexibility to continue investing in our strategic growth initiatives. Our return on capital employed has improved to 22% compared to the 21% in the last year. As I look ahead into FI27, our focus remains on sustaining growth momentum through AI-led transformation opportunities and enterprise modernization programs, while continuing disciplined execution and strategic investments in AI capabilities, platforms, sales capacity, and future-ready talent. Our growth guidance for FI27 is supported by a healthy and improving pipeline, traction and AI-led opportunities, and customer engagements. Overall, I believe we are entering FI27 on a strong footing. Before I conclude, I am happy to share that our board has announced a final dividend of Rs. 365 paisa per share. Which, when approved by the shareholders, will take the total dividend for the year to Rs. 6.40 per share. Thank you for listening to us patiently. I will now request the moderator to open the call for questions.

Thank you. We will now begin the question and answer session. Anyone who wishes to ask a question, press star and 1 on your touchstone telephone. If you wish to remove yourself from the question queue, you may press star and 2. Participants are requested to use handset while asking a question. Ladies and gentlemen, we will wait for a moment while the question queue assembles. The first question comes from the line of Aditi Patil with ICSA Securities. Please go ahead.

Hello? Thank you for the opportunity. My first question is on the Q4 revenue growth. Well, you mentioned that there was a ride-shifting of Artha licenses in Q4. Was there any other reason for a software growth? Like in high-tech vertical, we see a sharp QQ decline in both Q3 and Q4. So, if you can help me on this.

Yeah. Go ahead, Joseph.

Yeah. So, you know, if you look at the Q4 growth, you know, we did 0.5% quarter on quarter at constant currency and INR growth was 2.8%. And for the year, constant currency was 9.2%, slightly short, you know, very tad bit short of the 10% that we had projected at the beginning of the year. And at INR was, you know, 12.3% year on year. Now, if you just get down to... You know, a couple of verticals that did well and a couple where, you know, where we saw a little bit of a drop. BFSI continues to do well, whether you look at a quarter-on-quarter growth or year-on-year growth, you know, the bets that we made on pure software and all years. The call is paying off and, you know, so that's one. Second is, if you look at EdTech, from a Q4 perspective, there was a good growth of 8.4% quarter-on-quarter. And we are seeing, you know, in a couple of accounts where we had held a challenge, we are seeing traction back in those accounts. We're also seeing our EduWeave platform getting traction. We have a couple of customers already for this platform, and there are quite a few prospects. Now, as far as, you know, high-tech is concerned, there was, you know, A big reason was for one of our customers who's based out of, you know, Canada and who has operations in China, we were developing a completely new product for them, a mixture of, you know, an automated cooking system on the hardware and backed up by a low-code, no-code platform that was AI-driven. And this got completed. The customer is trying to take it to market, and there's a pause in the engagement. And the drop in that revenue to the pretty sizable account for us, that's what resulted in the drop in high-tech. I can almost link it back to one customer. Now, healthcare grew 12.8% year-on-year. But for the quarter, there was a dip of 5%, and that's because one of the customers in the pharma space, there was an engagement that also included some license revenue that got completed in Q3. And therefore, in Q4, we had that thing. But overall, I would say BFSI and healthcare continue to show good resilience, as I pointed out in my talking points. We also see retail and CPG having good traction. EdTech already talked about, we see budding shoots and eduweave should lead to growth. NAI is driving a fair bit of interest in this segment.

Adity.

We have lost the line of Sajiti. A reminder to all the participants that we have the star and one to ask a question. Once again, a reminder to all the participants, I do not press star and want to ask a question.

Yeah, operator Vinesh here, so I will go ahead with the question.

Yes, please, Hupayat.

Yeah. So, sir, on our AI-first initiatives, how does the AI-first initiative fundamentally defaults from the company's previous digital engineering approach, and what specific changes in the operating model or service delivery or client engagement have we implemented since its loan? Good.

So let me take the first question, first part of the question, and let you talk about some of the initiatives and some of the work we're doing in the AI space. So, you know, we started the company as, you know, a digital native company, Vinesh, and I would say, you know, A lot of the work we did was around data, cloud, customer user experience, but, you know, one thing that was common was data all along, and even in our initial years, we did quite a bit of AI work with the customers, but it was more of the traditional legacy AI, right? And three, four years back with GenEI, with the announcement of co-pilot and seeing the prospects for this technology or this trend, we started Generative AI business unit. And we've seen very good traction in Generative AI business unit. And what we are seeing is that And what we are also evangelizing to customers and guiding them is that any initiative they take up now, any platform that they build, They should look at, you know, how does AI become a central part of this? And it could, you know, a lot of it would be digitization or digital engineering or transformation. And, you know, for those who have not really fully realized the benefits of digital transformation, the advantage is now they can do it with AI at the central part of it. You know, so that is the overall thought process behind the AI for strategy, which has multiple elements. I thought I'd actually talk about some of the things that you're doing on, you know, on multiple fronts from an AI perspective, and also a little bit about how the legacy IML ops and generative AI, you know, how we view them. So, Sridhar, over to you. Thank you, Joseph.

There are two sides. Of course, AI is an integral part of, or classically, it has been an integral part of our digital positioning as well as the capabilities historically, as Joseph shared. However, as you could see from the examples that we are illustrating, customers, to take the advantage of the AI, there's a lot that happens behind the scenes that could be even sometimes creating the digital infrastructure. I did talk about even creating the IoT sensors kind of infrastructure before leveraging AI. And sometimes it could be you need to have the data or AI infrastructure. I have taken the automobile example, right? So think about it more like the tip of the iceberg when it comes to the AI solutions. However, the reason for us to actually go heavily on the AI first strategy is not what we build for the customers, but also how we build. For the customers. That's where the AI productivity tools for the entire service delivery come into the picture, be it engineering, testing, infrastructure, management, or cyber security. All the services that we are delivering, historically, and we continue to deliver, is being significantly impacted by the AI. So that way, from the talent, as well as our offerings. Right, be it AI-centric offerings or leverage in the AI for other kinds of work that the customer requires. All those pieces already are various programs that we have in the organization. I already shared some kind of... There are three goals I mentioned, right, which is 90% of when we started the digital initiative, we had the goal of doing the digital work only, and eventually we reached approximately 95-96% as a company. Very similarly, when it comes to leveraging the AI productivity tools at varying levels, be it agentic or AI augmented, we want to hit 90% plus by end of the year. So fundamentally, it is changing every service offering that we are having. That's the reason why we wanted to take it as an AI-first initiative that has an impact on our learning function, project managers, and how we price our customers, more focus on the outcome-based models, and then, of course, our offerings also integrated with AI. And that allows us also to start looking at certain tools I mentioned, ReliBuild, and, of course, the most important flagship solution is the Enterprise AI platform.

Yeah, sir. Got it. Thanks for the elaborate answer. So, one more thing. Right now, all the companies are in the partnership. So, how are we looking at the partnership with some of the players in order to scale this AI-led capability?

Thanks, Dinesh. Actually, I missed that part as part of telling. There were two new partners. Of course, historically, we do have strong partnership with Microsoft. As well as with AWS. However, in the last quarter itself, we did establish with two interesting companies. Of course, one is Anthropic. When they started a formal partnership program, we became one of the early partners for them. So we closed a partnership with Anthropic in the last quarter. The second one, which is much more interesting, is a young startup called Unify Apps. They actually are, they have a product which actually can connect the data side of the enterprise environment all the way up to the AI. We created a 360-degree partnership with them, and we work very collaboratively with them in terms of taking out-of-the-box AI-based solution with low-code, no-code way of developing agents on the top of it. So that way, we are looking at the industry giants. Historically, Microsoft, AWS, we already did have. Anthropic, we established already in the last quarter. And then, emerging startups that are transforming the enterprises, like Unify Apps, we established a partnership also in the last quarter. So, two new partnerships in the last quarter, Anthropic and Unify Apps.

Okay, thank you. Thank you, sir. And I will join back with you again.

Thank you. Next question comes from the line of Aditi Pati with ICICI Securities. Please go ahead.

Yeah, thank you for the follow-up. So, I wanted to, I had two questions on the GBS business unit. While the revenue growth this quarter, like, it has grown sequentially, but there is a drop in the segmental margins. Can you share the reason for this drop? And also... In terms of the AI platform, what kind of, I mean, apart from Artha, what other platforms are already being adopted by customer, and if you can share some matrix of the platform adoption?

So, Ajithi, let me take the first one on the margins, and I'll hand it over to Sridhar. Joseph, for the second. See, as far as GBS business unit is concerned, it contributes about 3.3% of our total, you know, company's revenues. It's actually nothing but an AI's, you know, center of innovation if you really look at it, because if you look at this concept of AI-led services or AI-induced, you know, services, that number is much, much larger. But what we do in GBS is the AI, it's an AI center of innovation. We started it to take a lead in all that thing we do in AI. Created it as a BU, and like I've been saying in the past, we have dedicated people to it, about 200 people, but the large part of AI is now becoming, it's going into various other parts of the business. So while there is this concept of BU and BU profitability, the intent at GBS is to make sure that we create solutions and tools which are ahead of time, focused on customer needs and that kind of a thing. So, it's not profitability. The profitability tends to get captured in the larger PDS and the IMSS area of work. Just to give you a case in point. The conversion of Artha Banking or inducing it with AI is something that's happening. The entire revenue of Artha Banking sits inside BFSI, and it gets attributed to PDS. Something that we do in Alera or Ellipse, our platforms on the security and the customer support standpoint, that gets counted as part of IMSS, which is another view. But, you know, without GBS giving you the tech direction and the direction on the innovation and where the markets are headed, we are not going to be able to do that. So what we are trying to do is over a period of time, GBS becomes a horizontal, they supply and they will serve the entire company with the AI capabilities that are built. So, as a BU, the first order of preference is to make sure that the people deployed in that unit, they are completely, you know, used across the company, but at the same time, they stand for certain element of revenue, and let me not say profitability, but at least to make sure that it makes economic sense for having that team. Does that make sense, Aditi?

Okay, yes, it makes sense. I understand.

Yeah, over to you, Sridhar.

Yeah, so Aditi, in terms of the, of course, the platforms that we're building, I'll put them into three buckets, Aditi. One is the AI productivity. I mentioned something called reliability, right? We have something called agent hub. So the idea is like when the engineering teams are like looking at the requirements, how can we generate near 100% code? From the specifications directly, that's what the reliability address is, and today I already did talk about one customer. Which is a large CPG, and also within our internal projects in a lot of places, we are using it. The other one is Agent Hub, where enterprise quality card drives can be put on these coding agents, because we are seeing a lot of these news articles on coding agents removing the production database or turning rogue, etc., right? So checks and balances, card drives, etc., so that they at least are controlled. So those are more on the AI productivity side. And on the service delivery side, of course, one example, Alera was mentioned by Venkat, and that is predominantly on the customer support side, a completely AI-based solution that we have, which is a little bit skewed towards the pharma industry, but is applicable to other verticals too. And another one on the cybersecurity space, again, falls broadly under our IMSS umbrella, is SecEIA Genie, which is actually on the cybersecurity side. So a lot of the issues are text-based and complete AI solution that can analyze and identify what kind of security threats can be there. And the last category is the vertical solutions. Joseph did talk about the Edgeweave, which is actually a collection of multiple AI use cases for the education institutions, along with the digital infrastructure, so that any academic institution can leverage. One example out of all AI use cases we have is student engagement. So, leveraging the video analytics, image analytics, and everything, how well the students are engaged in the classrooms. So, multiple AI use cases in the education space, and we have insurance in a box, right? Again, a lot of AI use cases along with the complete insurance workflows as part of it are there anyhow on the banking side we have. And all this. The experience is what made us to come up with an enterprise AI platform that can be highly customizable for each of the vertical, for us to start rapidly creating vertical-oriented solutions. So these are some examples of the various AI solutions. Apart from that, we do have bioinformatics solution, multi-omics solution, etc., which are, again, very AI-focused and a little bit narrower than the solutions I mentioned.

Okay. Got it. Can you share some adoption metrics for these platforms, or they are still in the initial stage?

So, in terms of the adoption, like the AI productivity, of course, naturally, you can assume as well as understand that the adoption is extremely much higher because these are not vertical solutions. Pretty much every software development project we can use, right? So, that way, the relay build, which is on the AI productivity side, at this point, we already have 40% adoption within our internal projects and the customer projects and everywhere, and from there, like, of course. They'll keep adopting more. And Alera, for example, is actually a companion solution for our well-established Ellipse platform, which actually can allow complete infra AIOps kind of solution. So that way, we have Ellipse very well adopted with a lot of our projects, and Alera is being adopted in those places for the customer support.

Okay. Okay, got it. I had a couple of more questions on the guidance. So, revenue guidance of 12.5% is very assuring. Can you help me understand how much of it is due to the deals we have already won and how much is contingent on the high probability of pipeline conversion?

You know, it's a mixture of both, Aditi. The approach we took is to do a, you know, grounds-up revenue plan in March. We had each of the industry groups and the IMSS and generative air business unit. to come up with their plans. We also had the Centers of Excellence come up with independent plans to make sure that it's all aligned. And just before this board meeting, you know, last week and the week before last, we did a stress test of the Q1 and Q2 guidance, because if you can meet the first half yearly numbers, It gives much higher level of confidence that we'll be able to meet the annual plan, and we've built the plan for 15%, whereas we've kind of – the revenue plan, but the P&L has been built on 2.5%, so that's a little bit of a cushion. And, you know, as you said, our pipeline has grown by 27% quarter on quarter. This is a mixture of, you know, NN and opportunities in our existing business. As you know, our repeat... Business is 92%. It varies between 92% to 94% depending on the quarter. So that gives quite a bit of solace, right, having that stability. And the good thing about the pipeline also is there are several large deals that are cutting across quarters and across years, which gives a little bit more of stability and cushion to the overall projection. I've already talked about vertical outlook that we have. So, based on all, and we've talked about how we're getting a lot of traction and success in the AI-first strategy. So, all of these factors have contributed to giving us the confidence for the 12.5% guidance that we provided.

Okay, got it. And on the margin side, what would be the planned headwinds in terms of, like, investments on sales and marketing or AI capability building and the annual wage agreements, if you can call that?

Yeah. So, Aditi, we have called that out in the press release yesterday. See, we did have tailwinds and headwinds last year, thanks to, you know, the way the foreign currency moved in our favor. We have also had currency losses because of the forwards that we have taken. So, quite a few moving parts, but despite that, focus will be to maintain, protect the 17 and a half.

Okay. I was asking from FY27 point of view, would our sales and marketing investments and AI investments would be higher in FY27 versus FY26?

I think my chat has dropped off.

So let me take that, Aditi. I think, you know, there would be a little bit of increase in the sales headcount and cost because, you know, there were some open positions that took time to fill up last year that are seeing people come on board right now. And we also have to do a little bit of a... A shift because when we moved from hybrid BDMs to client partners or account managers for existing accounts and hired a new set of NN BDMs, we also found that some of the people that we had were not fitting into that pure client partner profile that can grow accounts into large customers. So those shifts are taking place. On AI, we'll continue investing, whether it's on the platforms. Sheila talked about many platforms that we are building. All of them have well-detailed GTM and positioning behind them. And even capability building, because we feel quite confident that the business will come. Because as we speak from an AI and generative AI perspective, GPS, we do have money sitting on the table. So we don't look at this as really being headwinds. It could be And that's why what Venkat said, you know, that we will make sure that we operate in the guided EBITDA margin and operating margin of between 17.5 to 18.5 percent is what we are targeting in FI 27. Hey, sorry, did I get cut off somewhere in between? You got cut off and cut off. Yeah, you got cut off. I just addressed the question.

Yeah, yeah, thank you. And we have covered this in our press release, 17 and a half to 18 and a half is what we are trying to maintain while, you know, balancing out all the headwinds and tailwinds on the expenditure and revenue front. But investments will continue, and we will obviously prioritize that if it comes to a question of where to deploy money.

Okay, got it. Thank you.

Thank you.

The next question comes from the line of Dipesh Mehta from MK Global. Please go ahead.

Yeah, thanks for your opportunity. A couple of questions. I just want to understand the guidance part. We expect revenue growth to accelerate into FY27. Now, what gives us confidence? Can you provide some sense about, let's say, DIL, TCV, SCV related, anything? Pipeline, I heard you said, but pipeline obviously is a need to get converted and then revenue revenue to it. So, if you can give some more detail and which vertical you expect to lead to the growth.

The page, I'll... Shall I? I'll quickly cover the TCV, ACV question, and then hand it over to Joseph. See, we have traditionally not been giving TCV, ACV, because there is no one standard formula adopted by the industry. I'm not making a statement that it's not something that is possible, not possible, but we have stayed away from giving it that. But that said, we are, you know, pulling that together, and we'll hopefully in time be able to share that. But the larger thing is you should see the way we build our business numbers. One is based on repeatable business, the extent of new business that is expected to come in from the pipeline. When we are talking about pipeline, it is new business, existing new and new new. And then you have the existing business, which is growing at a certain clip, forming part of a large percentage, 93, 94% of the total business. You put that together, that's how we build up our business plan. So, it was on the same basis that we have been reporting over the last, you know, four, five years. While we are getting our, you know, numbers together, you know, the TCB large deal value, These are all something that makes possibly sense in the large kind of an environment, large company environment, but at our size of 300 million, it's all about focused execution on the current pipeline and the opportunities we wish.

I understand.

Just to add to that, Dipesh, I'll break it up into three sections. Some of the deals that we've closed, I'll just give you a high-level view with one of a P-owned company that's in the warehouse and logistics solution space. Signed a deal to take over all of their applications and infrastructure. So a three-year deal, that's around $12 to $15 million, right? And we are in discussion to sign up for taking over their technology as well, right? The engineering arm. And that will, you know, it's a very active conversation. Again, over three years, it will be $8 to $10 million, right? Now, for a large insurance provider in Southeast Asia, during the year, we won a couple of new contracts or deals. It's an existing customer where we've been able to grow the account. It's a $10 million plus account. We've been able to grow 40% year on year and got two large programs from them, you know, and we're in discussion for a couple of more such programs. Again, with a large CPG company, we have a five-year deal to help them with some of their marketing experience. The company that provides agency care platform, we've done a 360-degree partnership where we have their implementation arm and, you know, it's already a multimillion-dollar engagement. So that's on what we've won. But in terms of pipeline as well, right, we have several large deals, both NN and, as I mentioned earlier, that are quite large and cutting across multiple years. That's the pipeline part of it. And if you look at some of the initiatives that we had, right, we had talked about a PE initiative. And as we speak, we're the preferred partner for four of, you know, four PE firms. And I did give you, you know, some of the wins that I talked about or pipeline I talked about is coming from these, you know, PE companies. We have talked about GCC strategy, and we brought on board, as I mentioned in my talking points, we brought on board a head for that, who's putting a strategy that we will be implementing, and we should get traction over there. The large account strategy, you know, we've created two business units, one under Rohit Mathur, which has high-tech industrial manufacturing and FPEC, and the other one with Pratmesh, who came on board four months, five months back, that has detailed CPG, BFSA, and healthcare. Both are very seasoned leaders who have grown large accounts, so they will be leading the industry groups and the client partners to make sure that the foundation we laid for a large account strategy last year will be able to take it to the next level, and the goal is to create multiple large accounts. And this year, maybe... We'll create one or two $20 million accounts, but at least lay foundation for multiple of these accounts. And another area that we thought where we're leaving money was on the SAP front. And we'll take up very specific areas over there. We're not going to boil the ocean. So we brought a very seasoned leader on board, you know, to lead that practice. So if you just look at all of this, you know, there's so much, and, you know, we have all of our platforms that Shira talked about where they're getting good traction. So this is what has given us the confidence, right, that we'd be able to hit this revenue growth that we've guided.

Thank you.

Thank you. Next question comes from the line of Kuber with Access Securities. Please go ahead.

Yeah, thank you for taking my question. Thank you for the opportunity. Two questions from my end. So, I would like to know about your acquisitions. I mean, historically, we have done a lot of acquisitions, right? So, how these acquisitions are going to get benefited to us in the future? And when we talk about 1.3% of top-line growth, could be a mix of, if you can share some mix of inorganic as well as organic growth. And the second question is on AI. So everyone is talking about AI and uplifting their platforms as well. How different are we from those players? If you can just share some thoughts on that.

I'll just address the question on organic, inorganic. Whatever we have put out there, 12.5% is organic first. There's no question of inorganic because there's nothing in the pipeline as of now. Whatever acquisitions we have done in the past have been integrated a year and a half back. I, too, covered that. So, it's completely part of our company. So, we are, in fact, our plan for next year considers some of the efficiencies that are coming on account of, you know, the integration that we are talking about. So, we have progressed far deep into integration, and even if you are looking from a regulatory standpoint, the company should not be in existence post a couple of months. So, the number of 12.5 is completely organic. Joseph, so just, yeah, thanks, Renka.

Just adding to that, Kuber, if you look at it, last one and a half years, you know, that's me. We've been, you know, meeting all of these customers, others from Pure Software, Aureus, and from, you know, the earlier acquisitions as well. And the planning and the cross-selling, all of that is being carried out, you know, by us out here. And... We are also at the same time leveraging some of the capabilities that, you know, the people in Pure Software and Aureus brought to the table in some of the other customers that we have, whether it's in the insurance space or the banking space. So, it's a totally integrated unit now, and as Venkat pointed out, the 12.5% is purely organic that we projected. If we do an acquisition, that will be on top of it. We are quite clear internally. In terms of AI, I'll give my point of view, and I'll let Shrever also jump in. So if you really look at it, And I think Happiest Minds is the only company that has a separate business unit for generative AI. And, you know, what that allows us to do is to just focus on the space, either Praveen, RPA, and the team to focus on the space, develop, you know, depth in AI and generative AI, work closely with analytics and the DPACoE, which, you know, which have become kind of overlapping or extensions of the generative AI business unit because there's so much of. If you look at automation, right, business process automation, there's a lot of agent TKI coming in there. If you look at analytics, data is the underlying need for doing anything on AI. And so we are able to put this integrated story with GBS leading the way with the depth to bring to the table. The second thing I would talk about is the repeatable solutions that we are looking at and the platforms. I think the number of repeatable solutions that we have, and Shira talked about quite a few of them, brings a lot of value to the table. On the SDLC front, we've created a separate center of excellence for making sure that we keep, we saw that change. The pace of change was just too fast, and very often, you know, for us to advise the customer or to make pivots internally in terms of what to use, what not to use, we felt that having a separate center of excellence that could focus on these productivity tools, whether it's Cloud Code, Copilot, Gemini, all of the others, Cursor, and just keep track of the changes, how customers are adopting it, so we can distill all of these learnings, go back to customers, as well as to implement it internally, you know, that, again, I think is something that I don't think too many companies have done. So given our size, I think we are putting quite a bit of investment. We are making... A lot of progress on multiple fronts. Our whole AI first strategy has been, you know, has got multiple elements to it, including internal adoption of AI tools, which we can then be leveraged to advise customers. And I think that's what we are bringing to the table as a value proposition to our customers.

The only point I want to add is, of course, there is always excitement by multiple IT services companies to keep coming with platforms, right? And that's how we differentiate and why clients actually like what we are coming up with. One of the strategic decisions we have taken is we didn't want to build a broader enterprise AI platform two years back because everything is in total flux. At that point, I'm saying any platform clients are not in a position to believe they themselves don't know what this technology is. So what we did is we wanted to wait so that we gain sufficient experience, some of the examples Joseph shared, in terms of our repeatable solutions. And all the knowledge and experience that we gained is what prompted us to start thinking about, as well as start developing and creating an enterprise platform. The rest, we were actually using our existing experience with EIA, for example, Elipsy Understanding and Experience. We enhanced and moved into Alera kind of solution. So that's how we created multiple point solutions. And now is the time for us to create a broader enterprise AI platform after two to three years of experience with Generative AI.

Thank you. The next question comes from the line of Siddhant Saraf, an individual minister. Please go ahead.

Yes, sir. Thank you for the opportunity. So, my question is, little liar, I would say, from a long-term governance perspective, could management provide some color on succession planning and development of the next line of leadership? Considering substantial promoter holding of around 32%.

Yeah. So, you know, from one of the things that... Some of us in the founding team found it surprising is that in 2012, just a year after we had started the company, Ashok had initiated a succession planning discussion, and he said, we've just started the company. So it's become, I would say, an annual exercise that we have not missed a single year where we take all the senior and next-level roles, and we look at the people playing those roles, what are they going to be ready for next. And had discussion on who could be a potential successor, what is the areas that can be considered for development, and then what are the programs, you know, that are available or that we can avail of. And this gets discussed with the board as well. Last year, we also included Hogan Assessments to get a different view of these leaders and, you know, and had that reviewed by the board again. And one of those have been multiple development programs, including having some of our leaders attend IM Bangalore, ISB for specific, you know, training programs. We've started some training programs, development programs, not training, development programs internally, and we feel very confident in the kind of succession planning that we've done. At the same time, as I mentioned, we've got a few leaders externally because we also believe that getting some leaders from outside brings in fresh ideas and challenges some of the ways of doing things. So this is the approach we've taken to succession planning, and it's all been done with involvement, active involvement, and inputs from the board.

Okay, that answers.

Thank you. Ladies and gentlemen, due to time constraints, we have reached the end of question and answer session. I now hand the answers over to Priyanka Sharma for closing comments.

Thank you, everyone, for joining us today. We would also like to sincerely thank HGSE Securities for hosting this call on our behalf. We appreciate your continued engagement and support. Should you have any further queries, please feel free to reach out to the Investor Relations team at irabduridhappiestminds.com. Thank you once again, and have a great day ahead.

Thank you. On behalf of SDFC Securities Limited, that concludes this conference. Thank you for joining us. You may now disconnect your line.