R Systems International Limited (RSYSTEMS) Q1 2026 Earnings Call Transcript

Ladies and gentlemen, good day, and welcome to the R-Systems Q1-FI26 Earnings Conference Call. As a reminder, all participants will be in the lesson on Emote, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during this conference call, please signal an operator by pressing star, then zero on it at stone 4. Please note that this conference is being recorded. I now hand the conference over to Mr. Kumar. Thank you and over to you, sir.

Thank you, Dr. Nali. I welcome all participants to R-System quarter 126 earning conference hall. Since R-System follow calendar year as its financial year, Jan to March quarter is quarter 14. We have today with us Nitesh Manson, Managing Director and CO R-System and Nantra Danna, CO R-System. We shared the investor presentation late evening yesterday as well as uploaded on company and stock exchange website. Hope all of you have received that. We will start the call with opening remark on the performance of the company by Nitesh, followed by financial overview by none. Thereafter, we will have a closer statement by Nitesh. Subsequently, we will open up for a Q&A session. Before I hand over, let me read out the customary disclaimer statement on the app of the company. Investors are questioned that this presentation contains certain forward-looking statements that involve risk and uncertainties. Company undertakes no obligation publicly to update or revise any such statement. These statements may undertake revision because of the information, future event, or otherwise. Actual reserve performance achievement could differ from those expressed or implied in such forward-looking statements. Now, I am handing over to Nitesh for his opening comment.

Thank you. Over to you, sir. Thank you, Kumar, and welcome to everyone from my side as well to this first earnings call of this year. For those of you who are following the presentation, I'll call out the slide number. Others, of course, you know, as I walk through the numbers and performance, I'm sure you'll be able to follow me. So I'm going to be starting with the overall financial performance for the first quarter, which is slide number four. I'm very happy to report that we posted a revenue of 574.8 crore rupees or $62.8 million in the first quarter, which represents year-over-year growth of 29.9 percent and a quarter-over-quarter growth of 3.5 percent. The adjusted EBITDA adjusted for RSU expenses and non-recording costs. It stood at 115.7 crore rupees, or $12.6 million, which is an EBITDA percentage of 20.1%. This is a year-over-year growth of 50.6% and a quarter-over-quarter growth of 13.7%. The adjusted net profit for the same period stood at Indian rupees 75.8 crores, or $8.3 million, which is an adjusted net profit of 13.2%. This represents a year-over-year growth of 74.8% and a quarter-over-quarter growth of 25.5%. The adjusted EPS stood at rupees 6.4, which is a similar 74.6% year-over-year growth or a 25.4% quarter-over-quarter growth on the EPS numbers. If you look at the last eight quarters graph, you know it shows consistent growth every quarter that the company has posted, barring a minor dip in Q125, very minor indeed, and with a strong growth and deal momentum across the last four quarters, as is quite visible. We've continued to maintain our margins in a very healthy range, as we had guided in the 17-plus kind of a range. And this quarter, if you look at the bridge, of course, we all know that we had sharp movements in foreign exchange and in rupee depreciated significantly against the dollar. So we have also seen a significant rupee depreciation benefit, which has taken our EBITDA to 20.1%. But even without that, we stand in the, you know, 18 or rather actually 19 point something range. Quickly moving over to detailed margin and EPS analysis, slide number five, comparisons based on the same quarter last year or year-over-year. Last year, Q1, our revenue stood at $442.5 crores, which has now come to $574.8 crores. That's a 29.9% growth year-over-year. I just said EBITDA at 76.8 crores, which is now 115.7 crores, that's a 50.6% growth, or from 17.4 to 20.1%, which is 276 bps of increase year-over-year. On a net profit basis, from 43.4 crores to 75.8 crores, that's a 74.8% growth in net profit, or 9.8% to 13.2%, which is a 339 basis points increase. And the EPS going up from 3.7 to 6.4 rupees, which is 74.6% increase. Same numbers compared over quarter, which means from Q425 to Q126, we went from 555.1 crores to 574.8 crores in revenue. That's a 3.5% quarter-over-quarter growth. Or 101.7 to 115.7 crore rupees in EBITDA, which is a 13.7% growth, or 18.3% to 20.1% EBITDA, which is 180 basis points. Sorry. On adjusted net profit, 60.4 to 75.8 crores, that's a 25.5% growth, or 10.9% to 13.2% as a percentage of revenue, which is 231 basis points growth. And on EPS basis, from 5.1 rupees to 6.4 rupees, which is a 25.4 percent growth on EPS. Quickly looking at the operating metrics on slide number six. Our revenue distribution is largely in the same range. America's contributes to about 69.3% of our revenue, with APAC contributing 17.5% and Europe 9.6%. And Middle East and Africa, or rather mostly Middle East in this case, geography that got added due to the acquisition of Navigo contributes about 3.6% of the total revenue. Which is not a significant change from last quarter. That's a few percentage points here or there. In client concentration basis, while a total contribution from our top 10 clients in revenue and dollar terms has remained the same, because the baseline total of the company has increased, we see slight percentage dip. In top three clients, going from 13.2% to 11.5%, top five going from 18.2% to 16%, and top 10 going from 26.9% to 24%. But broadly speaking, approximately 25% of our revenue comes from our top 10 clients. Our top client contributes about 5.8% of the total revenue. So utilization, as we had been talking about a lot of investment in AI and building our systems as an AI-first company over the course of last two quarters, we have significantly expanded our bench and COE investments in AI and data, which has also led to the launch of our AI studio called Execo, and I'm going to talk about it in a short while. But there's a deliberate, you know, decrease in utilization as a result of which for creating that COE and the deliberate bench on both data and AI talent, thus bringing our utilization down to about 80%, 80.5%, which was at its peak at about 84%, largely in the last two quarters taking approximately 2% to 2.5% dip on utilization. To be able to invest in creating the AI first, put the platform, service offering, having the people ready, and being able to service the market in that space. DSOs remain largely in the same range, you know, 60 to 63, 64 days in terms of built DSO, in 76 days in terms of DSO, which is built for Sunbuilt. Quickly looking at a few key wins in 2026, first quarter and important thing is that as the market has heated up in the AI space, our readiness in those service offerings and preparing our organization to be AI first has actually started showing results or paying dividends. The first one is a leading global technology research advisory company, which has asked us to develop an API-based platform for making sure that all their research templates, all their research data, et cetera, can be properly, you know. Secured, accessed, delivered in form of custom research reports, as said, that they deliver. It's a microservices environment built using AI, and that's something that, you know, we've been – we obviously won against some stiff competition, and the customer awarded us looking at our capabilities in the space. The second one is a North America-based technology company. They specialize in creating digital engagement, and by digital engagement, it means, you know, for a lot of B2C platform companies, these are the ones. Who helped them create the digital experience of the customers, so they onboard large B2C platforms as their customers to create digital experiences using AI, creating the golden records of data, creating the personalized experiences around it, and we are the ones who are actually helping them and working with them to do this. The third one is a leading platform on life insurance and annuity insurance, which obviously is, you know, extremely both secure and data sensitive. And this platform is used by some of the world's largest life insurance companies to write their life insurance and annuity plans. The platform had been written in certain legacy languages. has been working for over 20 years, and they wanted to modernize both the platform tech stack as well as the experience that it delivers to make it more maintainable, but for each customer, because every customer has their own products and et cetera, you know, which are written on it. So we have been, you know, chosen as the trusted partner to create those playbooks for platform upgrades for each of those large life insurance companies. There we go in and upgrade the platform using AI tools so that it creates minimum disruption and is done in a very quick timeline. The fourth one is a major hyperscaler, one of the large hyperscalers, leading cloud and cloud data services companies using our capabilities and the platform that we have created, an AI platform that we have created, to actually accelerate cloud adoption and improve performance and efficiency of... And last but not the least, a very interesting global life sciences company in the aesthetics and cosmetic product space has asked us to develop an end-to-end consumer loyalty program, which is spanning both medical aesthetics as well as retail products spaces. Which can create the digital engagement for their clients and help them to make those clients for life. So, all in all, every single, I'm sorry, every single deal that we've been part of, every single. Conversation today obviously has a little bit of an AI flavor. A lot of it is to do with data, but ultimately using AI and delivering those outcomes to the customers. Quickly moving on, something that we had shared with you last quarter, a trading 12-month ACV view of wins. So we had $76.5 million of ACV on a TTM basis last quarter. We are reporting $82.5 million of ACV wins this quarter. So it shows positive deal momentum, continued wins in the market, and we continue to build our book of business according to it. Moving on to slide number nine, very proud to share with you that we've refreshed our brand. While we've not changed the name, we are Our Systems International, but has the brand logo and the entire look and feel of how people see us, how we are perceived, how our website and the content around it has all become very AI first. And it is a refreshed brand look as well as the image. And I would invite all of you to please look at it. If you go to rsystems.com, you'll get to see the new RSI branding and logo. Along with that, we've also launched our AI studio. It's called Execo. It stands for EX for experience, IQ for intelligence, and O for orchestration. Execo is RAI Studio, which combines... The Power of People, our AI-trained talent, we call them AI-EV-trained talent, along with the Optima AI platform, which I've obviously talked to all of you about in the last so many calls. We have worked on it over the last 20-odd months, matured the platform. It covers the learnings that we have had across over 130-odd projects that we've done using the platform. All of that experience and intelligence coming together, orchestrated to deliver governed, enterprise-grade, authentic AI solutions, and the traction we're seeing in the market, et cetera, is very high. I would invite you to go to execo.ai, which is our AI studio website, or you can go to it through our RSI or rsystems.com website as well. They're also proud to report that within the first quarter, we also won the AI Iconic Award, hosted by Financial Express, for the best use of AI in manufacturing. And this was for what we've built as an AI-powered factory co-pilot solution, which works. We developed it for an IoT SaaS platform company who... It sells to various manufacturing companies to gather all their IoT data and produce the insights and analytics that will lead to good manufacturing decisions that ultimately those companies can implement. The role of the agentic AI-powered, you know, the whole AI engine that we built behind it was acknowledged and awarded through this iconic award. And then last but not the least, I'm very happy to also announce that we recently onboarded Farouk Ahmed as our chief revenue officer. He's going to be leading our sales engine, strengthening the go-to-market approach, and, you know, lead the key growth across key markets, especially focusing on North America in the tech space. He's based in the Bay Area. He comes with a very deep background and almost three decades of experience working. Largely in the tech sector, in the Bay Area, you know, helping companies grow their revenues. Very happy to onboard Farooq to the leadership team. At this point, I would probably want to hand over to Nand to walk through the detailed financial statements before I come back to the final summing up point looking ahead kind of a summary. Nandzi, over to you.

Thank you, Nadejji. Good morning to all. Thank you, everybody, for attending this call. For those referring to the investor presentation, this is the last speech. Revenue for the quarter was Rs. 574.8 crore or $62.8 million as against Rs. 555.1 crore or $62.5 million last quarter and Rs. 442.5 crore, that is $51.1 million, in the same quarter last year. This is year-on-year growth of 29.9%. This is on account of volume growth as supported by rupee depreciation and Novigo acquisition. We have started witnessing the results from our investment in cloud, data, AI, and automation in terms of large yield conversion, which is supporting sustainable revenue growth. The gross margin was 36% compared to 38.9% last quarter and 36.7% same quarter last year. Our quarterly margin are prominently impacted by reduction in utilization due to investment in AI and one lesser day. Also, Q4 has the benefit of some fixed price projects to work. As yen expenses decreased by Rs.22.9 crore from Rs.14.3 crore in last quarter to Rs.191.4 crore this quarter, this is mainly due to reversal of conservative AR provision on account of realization in this quarter, as well as two above year-end provision taken last quarter, being the year-end. The adjusted EBITDA was 20.1% compared to 18.3% last quarter and 17.4% in the same quarter last year. The company has been able to report robust margin percentage through operational leverage, improved revenue mix, and favorable exchange rates. The RSU cost under management incentive loan is Rs. 6.4% compared to Rs. 7 crore last quarter. EBITDA net of RSU expense is 19% as against 17.1% last quarter. Getting down to depreciation and amortization, the total expense was Rs. 21.5 crore compared to 19.3 crore last quarter. This includes Rs. 9.3 crore for intangible capital life on account of past acquisitions. Non-recurite expenses are on account of severance payment for certain redundant positions. Interest expenses are Rs. 9.6 crore compared to 6.8 crore last quarter. Increases on account of fourth quarter impact of debenture interest. Other income was Rs. 13.1 crore compared to income of Rs. 2 crore last quarter. For effective 1st January, we have adopted hedge accounting, where the effective portion of changes in fair value loss amounting to Rs. 18 crore has been recognized in the hedge reserve under equity. This will be reclassified to profit and loss account when the corresponding hedge transition occurred. Other we used to mark to market such gain or loss, but now we have aligned with most of the IT companies which follows hedge accounting. Further, we had an exchange gain of Rs. 11.34 compared to exchange loss of 10 lakhs last quarter. Further, the other income comprised of interest income of Rs. 60 lakhs this quarter compared to 1 crore last quarter. During the quarter, the average rate for USD and Euro was 91.48 and 107.12 respectively, as against last quarter, average rate of USD 89.06 and Euro 103.65 respectively. These are the two main currencies for our system. As at year-end, we have total forward cover of $46.25 million with average rate of 91.13. Our tax expense was Rs. 24.2 crore this quarter, as against 9.4 crore last quarter. Our effective tax rate is around 27 percent due to non-deductibility amortization for intangibles acquired through acquisition as observed by a certain tax tool. Our normalized effective tax rate is around 28 percent. Net profit after tax was Rs. 65.4 crore or $7.2 million compared to Rs. 36.4 crore or $4.1 million last quarter. Basic EPS for the quarter was Rs. 5.52 compared to Rs. 3.08 last quarter. Adjusted EPS for the quarter is Rs. 6.4 as compared to Rs. 5.1 last quarter. With this, let me hand over to the HG for closing remarks.

Thank you. Thank you, Nand. Coming back to, you know, this is slide number 10, and I usually take a view of the market and provide how we are seeing it and what it means for us. So, we ourselves had conducted a research study covering over 200-plus organizations to look at How the mid-market players are adopting AI and how are they scaling it? And some of the findings of that result, of course, you know, that helps us in kind of building our narratives and our offerings to the market. The survey in this global mid-market, also authored jointly by Everest Group, shows that almost 43% of the organizations are leapfrogging directly from the classical ML And, you know, Advanced analytics directly to agentic AI models without going through a middle phase of using generative AI and generative AI solutions. There are almost 64% organizations that show high adoption of, you know, of AI in various things, but the actual productive deployment is only at about 15%. This gap between where the organizations are already spending and doing stuff on AI versus only 15% getting it deployed is the clear opportunity for organizations like us to help those organizations realize value from their AI investments, and that's really the big market which is available to us. Second point, as we saw through the survey and also through our experience throughout the year, getting ROI from AI is not really a tool question. It is an AI talent question, and our moves in training our people and having all our people trained on AI with 1,400-plus people AI EV certified is a great asset and a differentiator to be able to service the market in a proper manner. So if you look at the trends that are shaping this year, of course, organizations are running towards adopting AI in whatever manner, but also beginning to look at the cost of running AI as an important factor. And as they start looking at what does it cost to run AI, they obviously then start looking at players like us to architect AI-efficient solutions and the end-to-end systems which will actually deliver the results without burning a hole in their pocket. Legacy modernization continues to be a very large, totally addressable market, and across all sorts of companies, whether they are dealing with legacy code bases, legacy data states, or reporting landscapes that they want to modernize, we have ourselves seen significant wins in this area both last year and this year as well. Enterprises have begun to recognize that engineering velocity is a key differentiator in achieving ROI from AI initiatives. And this has been our narrative on Execo right from day one, that through our AI studio in Execo, we deliver engineering velocity, because finally with the same commercially available tools, everybody can potentially theoretically achieve the same outcomes. But the gap between those who achieve the outcomes versus those who don't is really the engineering velocity that is brought in by AI experts who do it the first time right and get the efficient solutions rolled in in an enterprise-ready manner very quickly. I think all of these forces that are shaping up and the way we have prepared ourselves over the last, you know, year or 20 months is definitely going to create a convergence. We are seeing that kind of momentum in the market, and we are very hopeful that it will continue to help us and become a tailwind for us. So with that, I'll end the presentation and open up for questions.

Thank you very much. We will now begin with the question and answer session. Anyone who wishes to ask a question may press star and then 1 on the touchstone telephone. If you wish to remove yourself from the question queue, you may press star and then 2. Participants, you are requested to use hand tips while asking a question. Ladies and gentlemen, we will wait for a moment while the question queue is assembled. A reminder to all, you may press star and then 1 to ask a question. We will take the first question from the line of Sandeep Shah from Aquarius Securities. Please go ahead.

Yeah, thanks. Thanks for the opportunity. Sir, first question in terms of the AI impact on the SDLC software development lifecycle. So, where various industry research reports indicate SDLC may have relatively higher impact versus others. So, how are you witnessing such kind of... conversation with the clients about opportunity or threat. I do agree that we have done a lot of development in terms of pivoting from just the manpower kind of a delivery to AI-led delivery, but will this have immediate impact on the growth where clients are upfronting, asking and demanding AI-led productivity gain pass-on versus revenue recognition may happen later?

Sandeep, thanks for your question, and again, thanks for always being the first one to ask. So, clearly, look, AI and SDLC is a huge area, and our report also suggests that SDLC is one of the largest areas that gets impacted and has the best outcomes and returns. We ourselves have been using AI and SDLC for, like I said, over the last 20 months, developed a lot of reusable assets. Our Optima AI platform actually boasts almost around 50-plus agents, more than 1,500 prompts, and a bunch of other reusable components that actually enable AI and SDLC to be enterprise-ready. Now, to the second part of your question, and I think, you know, I said this in the past also. So, AI and SDLC is a huge benefit or efficiency gainer for all parties. For us who are doing the work, we can do the work in much lesser effort and much lesser time. And for the customer, it is an outcome which can be delivered in a much faster manner with high efficiencies. Now, does that create a risk for us or an opportunity? It's a huge opportunity for us. Reason being, we are a projects organization, and we've said that multiple times. Most of our, in fact, over 90% of our revenue is coming from discretionary spend where we're doing project work for our customers. What that means is that it does not take away anything from us, right? It's not that we are doing some support maintenance, et cetera, in a very traditional manner, which will now shrink in size because of AI. In fact, what it does is, because we are constantly going after that discretionary spend and new projects every time, every new project that we bid for is already bid in a much more efficient manner, which keeps us ahead of the competition. I think it is almost impossible for us to think today that we will bid for a project or a new development, enhancement, modernization, migration, whatever it is, without putting AI into it. And that's become the norm, and it acts as a competitive advantage for us. It gets us into those deals, and we win those deals. So NetNet, it is expanding the target market, total addressable market for us. And we are winning those deals. And hence, it's a huge opportunity for us. Average deal size, if you compare, the deal sizes have become smaller because it doesn't take the same amount of time and effort to do it. But on the other side, in the target market or total addressable market has expanded, it overcompensates for it. I hope that answers your question.

Yeah, yeah. And just further to this, in the last few days, the frontier model vendors like Entropic and OpenAI are also announcing floating their IT services company in association with some of the global investment bankers, where they want to tap the small and medium-sized enterprises. So, I do agree, it's early days, may not have a view, but how do you see? So big or

small, only time will tell, Sandeep, but the first thing that I see with that is it validates two points. Number one, it validates that, you know, AI is fundamentally a people problem, not a tools problem, right? Because if it was only tools, then those frontier companies have already released the tools. They are also realizing that everybody who is buying their tools and using their tools is still complaining about not getting the benefits, right? So they need the right kind of people in the equation to make those tools work. And to deliver the enterprise benefits. So, one, it is a huge validation of what we have been saying and also doing is that it is a people issue, not a tools issue. Everybody has the same commercial tools. Number two, if it comes down to talent, it is about what kind of talent are they going to be assembling up and hence at what price point and how will they be able to serve the mid-market organizations. Clearly, sure, they have a game plan. There are large private equity companies who are joining hands and forces. So there will be some play over there. But the market is so big that, again, it becomes... Availability of talent, right kind of talent in the right places, at the right cost, right? And that obviously is not something that can run at the speed of AI. They will also have to go through the same motion of assembling a team, training them, getting them ready, bringing them in front of the client, etc. Sure, they will become a competition, but if as a total, it expands the market and there are one more player in it, then I'm already, you know, a player who's playing. I think there is enough to go around and we all will have a significant piece to kind of work with. So right now, I see it as validation of what we are doing, and as they really grow their feet and hit the ground, we'll start seeing what kind of competition they become.

And just last few and then I will come in the follower. It seems the growth could have been driven by full quarter consolidation of Novigo in this quarter, and there could be a possible decline in the organic revenues, which could be also due to a seasonal week where a higher number of holidays being there on a Q1Q in the first quarter. So, do you believe this is a quarterly aberration and we can organically... Have a growth turnaround starting again from the second quarter, and ACV, which we have disclosed in this quarter, is on the same definition, excluding Novigo, correct?

So, let me answer the three parts in three different things. Number one, we do have the benefit of full quarter consolidation of Novigo, so no doubt about it. However, I just wanted to clarify, and this question may come up later again, is that, you know, the Novigo revenues Though they are a full quarter, this was the first full quarter of Novigo that got consolidated with our systems, and this was also the first fiscal year end for Novigo that happened together with us. As a result, and which is the right practice to do, we have aligned a lot of their accounting practices to align with our systems practices, including accounting policies and revenue recognition norms, et cetera. So, as a result of which, you know, there is a certain amount of revenue recognition change that has taken place going from, you know, gross basis to net basis on some certain kind of license revenues, some norms on fixed price accounting and those kind of things. What we had originally, you know, what you may have in mind is what we had given as the size of, you know, Novigo revenues, full-year revenues when we had acquired the company at about $32 million a year. That restated will stand at about $21, $22 million a year. And as a result, you would see that, you know, yes, there is a small amount of degrowth in quarter-on-quarter basis because, of course, you know, there's a reduction in the number of days versus Q4. And like Nanji said in his financial statement readout, that we also had benefits of some... Fixed-price project two-ups in Q4 as they normally take place. But having said that, you know, we have largely remained flat organically, and we have very strong deal momentum, and we have been confident that the organic growth continues to be there, and we continue to gain the market share, and we continue to grow. Novigo adds to that, and they also continue to grow in their markets. They obviously were also impacted by the Middle East crisis. To some extent in Q1. So that hopefully will be a thing behind us, and then that will contribute to positive growth in that front as well. So overall, I don't see any challenges to the positive outlook for this quarter as we are in Q2, and we'll continue to report accordingly.

Okay, thanks. We'll come in the follow-up.

Thank you. We will take the next question from the line of Vinay Menon from Monarch Capital. Please go ahead.

Hi, sir. Hi. Thank you for the opportunity. A couple of questions from my side. One, we recently, you know, read that Blackstone is, you know, partnered up with Anthropic and a couple of other private equities are also there. And they're planning basically to deploy their engineers within the organization and even to, you know, the portfolio companies within Blackstone now. That is an area where we have done well over the last year, year and a half. So how do you see this playing out and could this kind of model set in other mid-market players as well?

First, again, thanks for joining in and for your question. Blackstone and a bunch of other private equities have joined in to put in money in what would eventually be some kind of a consulting company with Anthropik, etc. Without reading too much into it, whether it's any private equity, they are all going to look at a good opportunity as an investment opportunity and would invest. So, not reading too much into that. Going back to whether this will, you know, get deployed across P port cores or mid-market companies and they will benefit from it. Possibly all of that. Obviously, early days, they need to stand up the team and build the team and build their playbooks. Like I was saying earlier, I see it as a strong validation of our playbooks that value from AI and ROI will come through engineering velocity, and you need those kind of AI specialists to be able to implement it in a manner that it brings that velocity. It is also a combination of understanding your client's business and how they are going to use AI, which we believe we have developed over the last 20, 30 years of working with clients in various industries in learning their business and then understanding how we can impact. That's, again, something that will be slightly challenging to stand up over overnight. But having said that, you know, when it comes to Blackstone business, we have continued to win against competition. I have said that earlier in many calls as well. We are lucky to be part of Blackstone portfolio because we do get... Introduce to various portfolio companies and have a quicker path to having a conversation with them. But beyond that, I have to win a deal based on merit against competition in the same manner as anybody else does. And we would just see them as one more competition because neither us nor them will get pushed into an account as... Like somebody is mandated to use either of us, right? So we will have to continue to play to our strengths, and we believe that the experience we have, that the platform we built, which is directly targeted towards delivering ROI to enterprises, and all our working practices will continue to hold us in good stead. They will have their strengths, and just like any competition, we will have to measure up their strengths and then continue to pivot on our playbooks to make sure that we continue to win. So right now, it's a lot of hypothetical winners. They don't really have a company today. So we'll keep a good watch on it and clearly see how it plays out.

Okay, thanks for that. And in terms of the ACV, you have mentioned that the deal sizes are coming down. So if you can just mention what kind of deal sizes were there, which we have added this quarter. And you said the time is increasing. So a little bit more color on that would be helpful.

So, Vinay, when I say deal sizes are coming down, I don't mean deal sizes for us are coming down. What I meant was that a deal which is delivered in a traditional manner So would I have been X now because of AI can be delivered in a much lesser than X kind of a thing, right? But for us, on the other hand, average deal sizes have gone up because We are now being able to, you know, as we have transformed our own offerings, we are now doing, we are taking end-to-end objectives. We are doing transformations for our customers. So what used to be, you know, build one feature or put a sprint team together and put a pod of people has now converted to conversations where we're like, here is a large application, the three million lines of code written in legacy. See, can you migrate it in a short period of time using AI? And we would, we would have that as probably a million dollar deal, right? Now, that itself in the past would have been a one and a half or two million dollar deals, which is now a million dollar because it is, it is done through AI. But for us, deal sizes, because of this new TAM, our deal sizes are still improving, right? So the markets may look at it as, okay, you know, it takes much lesser to do the same thing. That's the AI efficiency. But we are benefiting from it because we are able to play in that new TAM and build our deal sizes accordingly.

Okay, and just last one thing that SG&A came down, you know, this quarter, just wanted to get an idea on how it will be going on because we obviously we in terms of the growth we are doing, I think, you know, it should normalize maybe in the next few quarters.

Yeah, SDNA coming down is not a reflection of any reduction in investment or people, neither in sales nor in GNA. It's actually, and Nanji would probably explain it if needed in detail, Q4 being the last quarter and, you know, before closing the books, we have to provision for any AR, et cetera. And through whatever follow-ups, et cetera, in Q1, we ended up collecting all of that AR. And that reversal is what, you know, kind of reflects in the reduction of SG&A. So, it's our investments in sales and marketing and all of those are intact. In fact, we continue to increase those. And hence, you know, when we look at going forward, perhaps, you know, I think this quarter we're talking about 10 million. It will probably – our normal run rate is at 11, 11 point something, and we'll come back to that. Okay. Thank you. I'll get back in a minute.

Thank you so much.

Sure. Next question is from the line of Anmol Garg from Dam Capital. Please go ahead.

Hi, thanks for the opportunity. I have a couple of things that I wanted to understand. Firstly, now that Nuvego has been fully integrated within our systems, and as I understand it, is that it has a relatively larger set of customers. So, have we been able to make any inroads with our system delivery portfolio for particularly Nuvego clients? I know it's early days, but anything that you want to highlight.

Yeah, sure, Anmol, and thanks for that question. While it is early days, but right from day one, we have focused on getting our go-to markets aligned and making sure that both Novigo and our systems are able to leverage each other's capabilities. Very happy to say that today there are at least, I would say, close to a dozen deals where Novigo and our systems teams are cross-engaged, and at least maybe three clients where Novigo clients have received our systems service delivery because of competencies or new capabilities that we sold to them, And at least one client where our systems client is using Novigo's competence to deliver. So that kind of cross-leverage is already happening. That's the... Fundamental premise of, you know, doing an acquisition which complements us in capabilities and so that we can expand our offerings with our clients. So absolutely, we're seeing the evidence of that taking place.

Understood, understood, sir. I also wanted to understand organic growth in this quarter. You said that it is plattish. However, if we include one and a half months off. So, just from that perspective, I wanted to understand what would be the organic growth in this quarter. And secondly, also the outlook for this year, how are we thinking about growth in this particular year organically from the art system perspective?

So, like I said, you know, given that last quarter we had half a quarter of Novivo coming in, this quarter, full quarter, and the adjustments to accounting policies, as well as, you know, some amount of, you know, fixed price, true ups, et cetera, that took place. I think the last quarter numbers do not provide a very clear straight line method to look at, you know, top line in that manner. Good news is that all those adjustments, all those alignments to accounting policies, et cetera, have already been done. So what you're seeing as this quarter numbers is a good baseline to understand what the combined numbers look like. And like I said, you know, and maybe on a one-on-one, Nanji can provide a little more detail. But, you know, overall, we have grown as a company. Like I said, organically, this quarter was flat, but that's, again, largely due to reduction of days and some fixed price two-offs in Q4. We have one new business, and our overall, while we don't provide any forward guidance and flavors, But very high confidence that both organically as well as combined entities, we are on the right trajectory for, you know, doing what we promise to our investors to continue to grow the organization. If you look at EBITDA numbers, we have delivered on the EBITDAs promised, and because none of the accounting adjustments impact, you know, our overall EBITDA. And profit margins, and we've posted a very strong number with 12.6 million there, and we continue to be positive about capability to maintain our overall EBITDA in the line.

Sure, sir. And, sir, lastly, I wanted to understand in terms of the, you know, are we seeing any trends where, you know, GCCs are established by the mid-market players as well? And is that a risk to our client base as of now, or do you see that maybe this can be an opportunity in terms of the GCC revenue that we might get from potential new clients?

So Anmul, we had launched our own GCC services like six quarters ago when we started helping mid-market customers to establish their COEs, create their GCCs, or participate in their GCC scale-up offerings. We have successfully helped close to eight or nine organizations in various stages of their GCC formations. What we see is that when customers decide and they want to have a GCC, they will obviously want to do that, but when they do it with us, they have a much higher chance of establishing a successful GCC or COE, whichever name they want to call it. And we have actually gained a lot of trust and confidence with the customers in doing so, which basically means it gives us a sustainable business on a long-term basis. Even if, you know, there is a part of the business that they will run themselves, we become long-term partners. So, yes, we do know that there is always going to be, and, you know, at least in mid-market, it's something that every mid-market player is looking at, that they will look at GCC plays, but they also want experts like us to work alongside, and we are using that as an opportunity for our growth.

Understood. And lastly, one very industry-specific question that I wanted to ask is, you know, how are we seeing the token cost, particularly right now when we are using EI models, and who is bearing that cost, whether the client is bearing it or we are bearing it, and does it differ in time and material versus outcome-based contract or who bears this cost?

So, token cost for output delivered to the client is usually, I would say, in almost 100% cases borne by the client. Either they provide us subscription to the front-end model that they are subscribed to, or we would do it, but we'll pass on the cost. So, to that extent, the token costs does belong to the client. We also end up incurring our own token costs because of the trainings, because of our own, you know, COE, R&D, development, et cetera, that we do. We believe that... Our ability to deliver AI with most optimal token costs is one of the differentiators because we built FinOps models within our AI ecosystem in Optima AI, and that is something that the CFOs at the client sites really love to see because when they are implementing themselves, they actually have no clue of what those costs would be. We are at least able to give them a clear metering of what the costs are and how the costs are going to be reduced. But, to your question, most of those costs, when delivering to the clients, belong to the clients.

Okay. Okay. Sure, sir. Thanks for answering.

Thank you. We will take the next question from the line of Varun Kulkarni from Incred ANC. Please go ahead.

Hi, good morning. Thanks for taking my question. So, the question on GCD has already been answered, so I'll probably skip that. Some basic questions would be, in terms of the AI and non-AI, is there a revenue split, or is it too nascent at this point to actually give that number split?

It is – well, we do try and keep a track of how our AI revenue is developing because, obviously, with all the investments we are making, it's not coming from a system, so we're not reporting it yet. But just to give you an idea, approximately 29% of our revenue today comes from AI and AI-enabled services.

And, I don't know, I just wanted to ask you, in terms of the total employee headcount, do we report that number because it's not there in the investor PPT? And what would be the attrition rate at this point?

So, we report the total headcounts as part of the press release. We would be able to see it there. We are about 5,400 employees globally, and attrition currently is running at, I believe, approximately 11%, which is lower than the industry. Sure, sure.

And another very basic question, in terms of the verticals, so do we have the specifics for that? And also, are we seeing in which vertical are we seeing optimum usage of AI at this point? And going forward, where are we anticipating this, you know, the AI implementation to be more in like which sector?

To answer the first part, we do share the split. Again, it's part of the press release. TIPS, which is tech internet platforms and services, is our largest vertical. It contributes about 40% plus of our revenues. Being the entire technology product space, you know, obviously, it's a very fast adopter of AI. So from our perspective, we do see a lot of usage of AI in that space. Our second, third largest verticals are telecom, media, entertainment, and healthcare, and again, in those spaces, we are seeing AI adoption happen at various spaces, depending on, again, the maturity and size of the customer. I think the jury is still out in terms of who or which industry will lead the AI race, but clearly, you know, Tech companies are definitely eating their dog food, so tech companies will continue to lead this for some time before other industries start catching up and have enough investments to say that they're doing more AI than the tech companies themselves. Just a small correction.

Think of the report as part of annual report, but not in the quarterly press, please.

No, I stand corrected. Thanks for that information. Yeah. It's part of our annual report, yeah.

Yeah, but it's more or less, you know, saying, you know, like, they're not moving the same thing.

Sure, sure, yeah, that's the other one.

That should be the last question. Take the last question, please.

Thank you. We will take the last question from the line of Mayank Babla from Chameleon AMC. Please go ahead.

Hi, am I audible?

Yes, you are audible.

Yeah, thank you for taking my question. So the question was around, you know, your AI offerings, be it the Execo AI studio or the Optima AI platform. Could you pinpoint, you know, which specific problem statements are you trying to solve within the enterprise architecture with this?

So, Execo.ai Studio is, like I said earlier, it's people plus platform and orchestration, and the platform in there is Optima.ai, so it's one and the same thing. And if you look at our execo.ai website, it very clearly also lays out, we are basically addressing three essential problems or addressing three narratives. We are doing AI for achieving acceleration in SDLC, the software development lifecycle. This is the core bread and butter of our business. We do engineering for a living, and now we are doing engineering with AI, and we are helping companies accelerate their software development lifecycle using AI. Second, we are addressing a specific component, which is about doing legacy modernization. Like I've said, it's a massive time for us and for everyone. And legacy modernization, whether it is legacy code base, whether it is legacy data state or legacy reporting infrastructure, we are able to modernize it using AI from anything to a modern stack and do it in a manner that, you know, like we love to call it, we change it from black box to glass box. The third playbook that we are addressing is AI for business objectives, and this is where right from customer experience, contact center, customer service, all the way to deep down, deep business domain workflows, which can be now done agentically. And, for example, whether it is, you know, insurance claims process, whether it is revenue cycle management process in healthcare, whether it is KYC process in banking, or it is a bunch of the horizontal processes in the CFO area, whether account receivables, payables, you know, the P2P matching, the three-way matching of invoices, a bunch of those things which can now be done agentically. And we've built end-to-end agent ecosystems orchestrated together to accomplish these kind of business objectives. So three problem statements that we are addressing, SDLC, modernization, and business workflows.

Sure. And if you had to highlight, you know, the differentiation or moat this platform has versus platform offerings by PR IT companies, what would that one or two moats that would be for, you know, have your right to win versus others?

So, our right to win is built on the fact that this platform, while we don't sell the platform, this platform is essentially providing reusable artifacts across all of these three narratives that I talked about, and enables any organization to achieve Enterprise-ready AI outcomes within a matter of weeks because all the essential elements, we built this like a five-layer take, all the essential elements of security, guardrails, usage policies, token optimization, specific compliances, all of those things are pre-built that can be applied directly to any enterprise. In a matter of weeks. And this is something that organizations take six months to build with expert talent also. So once that is done and with all the reusable agents, assets, or everything that's there, and then our AI EV trained talent. And, you know, again, our differentiation is that AI EV is not a certification that one can buy from outside. It's a proficiency-based framework that we have come out with. And our people who know how to use AI, especially all this enterprise-ready AI assets, which can then be deployed to a client, hence delivering the real ROI of achieving outcomes within months. And that's what we show on the website also, almost, you know, 2x productivity, almost 50% reduction in turnaround time and those kinds of things. So that's what creates the moat for us with our clients wherever we're using this.

Thank you. Thank you for that. And this last question is a data point question. So, how much does fixed-price projects and time and material contribute to revenue? And how has this mix changed over the last one and two years? Thank you.

Traditionally, the company's revenue was largely diamond material-based because that's how tech companies usually contract, and there were long-term customers where we're building products or the feature sets for them, et cetera. But as we've changed our offerings to more of these transformation offerings, especially data and AI-led, Our business mix has obviously moved more towards fixed price, and AI will obviously lead to more outcome-based pricing as well. While these numbers are not accurate to the point, but approximately speaking, what till last year would have been approximately, let's say, 10% fixed price. Last year, as in 2024, has already probably changed to maybe closer to 15% or 16% in 2025, and we believe that it will continue to move in the favor of fixed price as we go along and as we do more and more of these transformation objectives.

Sure. Any target in mind over here, if you can give?

No, not really, because we have to play with what is the business that we are attracting, and we don't have a target mix because we don't, you know, there is, it's not a trade-off between A or B, right? I mean, we are better off doing AI objectives on fixed-price basis versus serving the legacy mandates on time and material basis. So I think it will move along with the business mix change.

Sure, sure. Thank you so much and best of luck on the rest of the year. Thank you.

Thank you very much. Ladies and gentlemen, we will take that as a last question for today. I now hand the conference over to Mr. Nadesh for closing comments. Thank you and over to you, sir.

Well, thank you so much, and once again, thanks to all participants and everybody who asks questions. Like I've always observed, you know, these questions act as a good, you know, input to us to continue to focus on all the right areas and things that if we have, you know, left out or not really considered, then take them into consideration. I continue to enjoy these calls and look forward to seeing you all on the next investor call in a quarter from now. Thank you.

Thank you, members of the management. On behalf of our systems, that concludes this conference. Thank you all for joining with us today, and you may now disconnect your lines. Thank you.