R Systems International Ltd — Q4 FY26

R Systems International Ltd Q4 FY2025-26 Earnings Conference Call https://www.youtube.com/watch?v=PTHPchEwibI Published: 6 days ago

0:01 1 second Ladies and gentlemen, good day and welcome to the R systems Q1 FR26 earnings conference call. As a reminder, 0:10 10 seconds all participant nights will be in the listen only mode and there will be an opportunity for you to ask questions after the presentation concludes. 0:19 19 seconds Should you need assistance during this conference call, please signal an operator by pressing star then zero on it at stone. 0:28 28 seconds Please note that this conference has been recorded. I now hand the conference over to Mr. Kumar. Thank you and over to you sir. 0:36 36 seconds Thank you Salu. I welcome all participants to our system quarter 1 26 earning conference call. Since our 0:44 44 seconds system follow year as it financial year Jan to March quarter is quarter 4s. We have today with us Nitesh Managing 0:51 51 seconds director and co system and Sadana CFO system. We shared the investor presentation late evening yesterday as well as uploaded on company and stock of 1:00 1 minute change 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 1:08 1 minute, 8 seconds financial overview by none. Thereafter we'll have a closure statement by Nit. 1:12 1 minute, 12 seconds Subsequently we'll open up for a Q&A session. Before I hand over let me read out the customary disclaimer statement on behalf of the company. Investors are 1:21 1 minute, 21 seconds cautioned that this presentation contains certain forward-looking statement that involve risk and uncertaintities. Company undertakes no 1:28 1 minute, 28 seconds obligation publicly to update or revise any such statement. These statement may undertake revision because of new information, future event or otherwise. 1:36 1 minute, 36 seconds Actual result, performance achievement could differ from those expressed or implied in such forward-looking statement. Now I am handing over to 1:44 1 minute, 44 seconds Nitesh for his opening comment. Thank you. Over to you sir. 1:48 1 minute, 48 seconds Thank you Kumar and uh welcome to everyone from my side as well uh to this uh first earnings call of this year. Uh 1:57 1 minute, 57 seconds for those of you who are following the presentation, I'll call out the slide number. Others of course you know as I as I walk through uh the numbers and 2:05 2 minutes, 5 seconds 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 2:13 2 minutes, 13 seconds number four. uh very happy to report that we um we posted a revenue of uh 2:20 2 minutes, 20 seconds 574.8 cr rupees or 62.8 million in the first quarter which represents a 2:27 2 minutes, 27 seconds year-over-year growth of 29.9% and the quarter overquarter growth of 3.5%. 2:33 2 minutes, 33 seconds The adjusted IDA adjusted for RSU expenses and non-recurring costs uh stood at uh 2:42 2 minutes, 42 seconds 15.7 cr rupees or 12.6 million which is an AIDA percentage of 20.1%. 2:49 2 minutes, 49 seconds Uh this is a year-over-year growth of 50.6% and a quarter quarter growth of 13.7%. 2:56 2 minutes, 56 seconds The adjusted net profit for the same period stood at uh Indian rupees 75.8 8 crores or $8.3 million which is a adjusted net profit of 13.2%. 3:08 3 minutes, 8 seconds Uh this represents a year-over-year growth of 74.8% and a quarter overquarter growth of 25.5%. 3:15 3 minutes, 15 seconds The adjusted EPS uh stood at rupees 6.4 which is a uh similar 74.6% 3:23 3 minutes, 23 seconds year-over-year growth or a 25.4% quarter-over-arter growth on the EPS 3:29 3 minutes, 29 seconds numbers. Uh if you look at uh the last eight quarters graph, you know, it shows consistent growth every quarter that the 3:37 3 minutes, 37 seconds company has posted by a minor dip in Q125. Uh very minor indeed. Uh and u and 3:46 3 minutes, 46 seconds with a strong growth and deal momentum across the last four quarters as as is quite visible. uh we've continued to uh 3:54 3 minutes, 54 seconds maintain our margins in a very healthy range as we had guided in the 17 uh in 4:00 4 minutes the 17 plus kind of a range and uh and and this quarter if you look at the bridge of course we all know that uh we 4:10 4 minutes, 10 seconds had sharp movements in foreign exchange Indian rupee uh depreciated significantly against the dollar so we have also seen uh a significant rupee 4:19 4 minutes, 19 seconds depreciation benefit u which uh has taken our IIDA to 20.1%. 4:25 4 minutes, 25 seconds But even without that we stand in the you know 18 or rather actually 19 something range. 4:33 4 minutes, 33 seconds Quickly moving over to uh detailed margin and EPS analysis. Slide number five. Um comparisons uh based on the 4:41 4 minutes, 41 seconds same quarter last year or year-over-year. Uh last year Q1 our revenue stood at 442.5 crores which has 4:50 4 minutes, 50 seconds now come to 574.8 crores. That's a 29.9% growth year-over-year. 4:55 4 minutes, 55 seconds U if it adjusted a bit at 76.8 crores which is now 115.7 crores that's a 50.6% 5:02 5 minutes, 2 seconds 6% growth or from 17.4 to 20.1% which is 276 pips of increase year-over-year on a 5:11 5 minutes, 11 seconds net profit basis from 43.4 crores to 75.8 crores that's a 74.8% growth in net 5:17 5 minutes, 17 seconds profit or 9.8% to 13.2% which is a 339 basis points increase and the EPS going 5:25 5 minutes, 25 seconds up from 3.7 to 6.4 rupees which is 74.6% increase. same numbers compared over quarter uh over quarter which means from 5:33 5 minutes, 33 seconds Q425 to Q126 we went from 555.1 crores to 574.8 8 crores in revenue. That's a 3 and a 5:42 5 minutes, 42 seconds half% Q quarter over quarter growth or 101.7 to 115.7 5:49 5 minutes, 49 seconds uh cr rupees in IIDA which is a 13.7% growth or 18.3% to 20.1% IDA which is 5:57 5 minutes, 57 seconds 180 basis points sorry on adjusted net profit 60.4 to 6:04 6 minutes, 4 seconds 75.8 date crores that's at 25 12% growth or 10.9% to 13.2% as a percentage of 6:12 6 minutes, 12 seconds revenue which is at 231 basis points growth and on EPS basis from 5.1 rupees 6:18 6 minutes, 18 seconds to 6.4 rupees which is a 25.4% 4% growth on EPS. 6:24 6 minutes, 24 seconds Quickly looking at the operating metrics on slide number six, our revenue distribution is largely in the same 6:32 6 minutes, 32 seconds range. America's contributes to about 69.3% of our revenue uh with APAC uh contributing 78 12% and Europe uh 9.6 6:42 6 minutes, 42 seconds six and Middle East and uh Africa or rather mostly Middle East in this case geography that got added due to the 6:49 6 minutes, 49 seconds acquisition of Novigo contributes about 3.6% 6% of the total revenue which is not a significant change from last 6:56 6 minutes, 56 seconds quarter. It's a few b few percentage points here or there. Uh in client concentration basis while at uh total 7:05 7 minutes, 5 seconds contribution from our top 10 clients in in revenue and dollar terms has remained the same because the baseline total of 7:12 7 minutes, 12 seconds the company has increased. We see slight percentage dip uh in top three clients uh going from 13.2 2 to 11.5%. 7:21 7 minutes, 21 seconds 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. 7:32 7 minutes, 32 seconds Our top client contributes about 5.8% of the total revenue utilization. Um as we had uh been 7:40 7 minutes, 40 seconds talking about a lot of investment in AI and building uh our systems as an AI first company over the course of last 7:48 7 minutes, 48 seconds two quarters we have significantly uh expanded our bench and COE investments in AI and data which has also led to the 7:58 7 minutes, 58 seconds launch of our AI studio called Exico and I'm going to talk about it in a in a short while. uh but there's a deliberate 8:05 8 minutes, 5 seconds uh you know decrease in utilization as a result of which uh for creating that COE and the deliberate bench onboard data 8:13 8 minutes, 13 seconds and ex and AI talent thus bringing our utilization down to about 80% 80.5% 8:21 8 minutes, 21 seconds uh which was at its peak at about 84% uh largely in the last two quarters taking approximately two to two and a 8:28 8 minutes, 28 seconds half% depon utilization uh to be able to invest in creating um the AI first uh 8:36 8 minutes, 36 seconds both the platform service offering having the people ready and being able to service the market in that space. Uh DSO has remained largely in the same 8:44 8 minutes, 44 seconds range you know uh 60 to 63 64 days in uh terms of build DSO in uh 76 days in 8:52 8 minutes, 52 seconds terms of DSO which is build plus unbuilt. 8:58 8 minutes, 58 seconds Quickly looking at a few key wins in 2026 uh first quarter and u important thing is that as as the market has 9:07 9 minutes, 7 seconds heated up in the AI space our readiness in in in those service offerings and preparing our organization to be AI 9:14 9 minutes, 14 seconds first has actually started uh showing results or paying dividends. Uh the first one is a leading global technology 9:22 9 minutes, 22 seconds research advisory company which has asked us to develop an API uh based platform uh for making sure that all 9:30 9 minutes, 30 seconds their research templates all their research uh data etc can be uh properly um uh you know secured access delivered 9:39 9 minutes, 39 seconds in in form of custom research reports etc that they deliver uh it's a uh it's a microservices environment uh built 9:47 9 minutes, 47 seconds using AI and uh Um and that's something that uh you know we've been uh we obviously won against some stiff 9:54 9 minutes, 54 seconds competition and u the customer uh awarded us looking at our capabilities in the space. 10:02 10 minutes, 2 seconds The second one is a North America based technology company. They specialize in uh in creating digital engagement and by digital engagement it means you know for 10:10 10 minutes, 10 seconds for a lot of B2C platform companies these are the ones who help them create and uh the digital experience of the 10:18 10 minutes, 18 seconds customers. So they onboard large B2C platforms as their customers to create digital experiences using AI, creating 10:26 10 minutes, 26 seconds the um you know creating the golden records of of data, creating the personalized experiences around it and 10:34 10 minutes, 34 seconds we are the ones who are actually helping them and working with them to do this. 10:40 10 minutes, 40 seconds The third one is a is a leading platform on on uh life insurance and annuity uh insurance which uh obviously is um you 10:49 10 minutes, 49 seconds know uh extremely uh both secure and and data sensitive and this platform is used by some of the world's largest life 10:58 10 minutes, 58 seconds insurance companies to write their life insurance and annuity plans. The platform had been written in certain 11:06 11 minutes, 6 seconds legacy languages has been working for over 20 years and uh they wanted to modernize both the platform text stack as well as the 11:14 11 minutes, 14 seconds experience that it delivers to make it more maintainable but for each customer because every customer has their own 11:22 11 minutes, 22 seconds products and etc you know which are written on it. So uh we have been uh you 11:29 11 minutes, 29 seconds know chosen as as the trusted partner to create those uh playbooks for platform upgrades for each of those large life 11:36 11 minutes, 36 seconds insurance companies where we go in and and upgrade the platform using AI2 so that it creates minimum disruption and is done in a very quick timeline. 11:47 11 minutes, 47 seconds The fourth one is a major hyperscaler one of the large hyperscalers uh leading cloud and cloud data services companies 11:54 11 minutes, 54 seconds using our capabilities and the platform that we have created an AI platform that we have created to actually accelerate 12:01 12 minutes, 1 second cloud adoption and uh improve uh performance and efficiency of of clients who use their cloud services. 12:11 12 minutes, 11 seconds And last but not the least, a very interesting uh global life sciences company in the aesthetics and cosmetic 12:17 12 minutes, 17 seconds uh um uh product space is uh has asked us to develop an end-to-end consumer 12:24 12 minutes, 24 seconds loyalty program which is spanning both uh medical aesthetics as well as retail products uh spaces which can create the 12:33 12 minutes, 33 seconds digital engagement for their clients and and uh help them make those clients for life. 12:39 12 minutes, 39 seconds So all in all, every single I'm sorry, every single deal that we've been part of, every single conversation 12:49 12 minutes, 49 seconds today is obviously has a little bit of a AI flavor. A lot of it is to do with uh 12:55 12 minutes, 55 seconds data, but um ultimately using AI and uh and and delivering uh those outcomes to the customers. 13:04 13 minutes, 4 seconds Quickly moving on um something that we had uh shared with you last quarter a trailing 12 month ACV view of wins. Um 13:14 13 minutes, 14 seconds we we had $76.5 million of uh of ACV on a TTM basis last quarter. Uh we are 13:21 13 minutes, 21 seconds reporting $82.5 million of ACV wins this quarter. So it shows positive deal momentum, continued wins in the market 13:30 13 minutes, 30 seconds and we continue to build our build our book of business according to it. 13:36 13 minutes, 36 seconds Moving on to slide number nine. Um very proud to um to share with you that uh we've refreshed our brand. Uh while 13:46 13 minutes, 46 seconds we've not changed the name, we are our systems international but has the brand logo and the and the entire um look and 13:54 13 minutes, 54 seconds feel of of how people see us, how we are perceived, how our website and the content around it has all become very AI 14:01 14 minutes, 1 second first and uh and it is it is a refreshed brand look as well as the image and I would invite all of you to please look 14:09 14 minutes, 9 seconds at it. If you go to rsystems.com, you'll you'll you'll get to see the new RSI branding and and logo. Along with that, 14:17 14 minutes, 17 seconds we've also launched our AI studio. It's called Exico. It stands for ex for experience, IQ for intelligence, and O 14:24 14 minutes, 24 seconds for orchestration. Exico is our AI studio, which combines the power of people, our AI trained talent. We call 14:32 14 minutes, 32 seconds them AIE EV trained talent. uh along with the optimi platform which I've obviously talked to all of you about in 14:39 14 minutes, 39 seconds the last so many calls we have worked on it over the last 20 odd months matured the platform it covers the learnings 14:46 14 minutes, 46 seconds that we have had across over 130 odd projects that we've done using the platform all of that experience and intelligence coming together 14:55 14 minutes, 55 seconds orchestrated to deliver governed enterprisegrade agentic AI solutions and uh the traction we are seeing in the 15:02 15 minutes, 2 seconds market etc is very I um I would invite you to go to exico.ai which is our studio website or you can go to it 15:11 15 minutes, 11 seconds through our RSI or rsystems.com website as well. 15:17 15 minutes, 17 seconds We're also proud to report that uh within the first quarter we also won the AI conic award uh hosted by Financial 15:24 15 minutes, 24 seconds Express for the best use of AI in manufacturing and this was for what we've built as an AI powered factory 15:32 15 minutes, 32 seconds co-pilot solution uh which works uh we developed it for a IoT SAS platform company who sells to various 15:41 15 minutes, 41 seconds manufacturing companies to gather all their IoT data and produce the insights and analy analytics that will lead to uh good manufacturing decisions that 15:50 15 minutes, 50 seconds ultimately those companies can implement. Uh the role of the agentic AI powered uh you know the whole AI engine 15:59 15 minutes, 59 seconds that we built behind it was acknowledged and and awarded uh through this uh iconic award. 16:06 16 minutes, 6 seconds And then last but not the least I'm very happy to uh also announce that we uh recently onboarded Faru Khmed as our 16:13 16 minutes, 13 seconds chief revenue officer. uh he's going to be leading our sales engine strengthen the go to market approach and uh you 16:21 16 minutes, 21 seconds know lead the key growth acts across key markets especially focusing on North America in the tech space he's based in 16:27 16 minutes, 27 seconds the Bay Area he comes with a very deep uh background and almost three decades of experience working uh largely in the 16:37 16 minutes, 37 seconds tech sector in the Bay Area uh you know helping companies grow their revenues uh very happy to onboard Faruk uh to the leadership 15. 16:50 16 minutes, 50 seconds At this point, I would probably want to hand over to Nand to uh walk through uh the detailed financial statements before 16:58 16 minutes, 58 seconds I come back to uh the final summing up and looking ahead um uh kind of a summary. Nanji, over to you. 17:07 17 minutes, 7 seconds Thank you, N. Good morning to all. Thank you everybody for attending this call. 17:11 17 minutes, 11 seconds For those referring to the investor presentation, this is the last page. 17:15 17 minutes, 15 seconds Revenue for the quarter was rupees 574.8 cr or 62.8 million as against rupees 17:22 17 minutes, 22 seconds 555.1 cr or $62.5 million last quarter and rupees 442.5 cr that is $51.1 million in the same quarter last year. 17:32 17 minutes, 32 seconds This is yearon-year growth of 29.9%. 17:36 17 minutes, 36 seconds This is on account of volume growth as supported by rupee depreciation and noiggo acquisition. We have started witnessing the results from our 17:43 17 minutes, 43 seconds investment in cloud data AI and automation in terms of large deal conversion which is supporting sustainable revenue growth. The gross 17:51 17 minutes, 51 seconds margin was 36% compared to 38.9% last quarter and 36.7% same quarter last year. Our quarterly margin are primarily 18:00 18 minutes impacted by reduction in utilization due to investment in AI and one lesser day. 18:05 18 minutes, 5 seconds Also Q4 has the benefit of some fixed price projects too up. SGN expenses decreased by rupees 22.9 cr from rupees 18:13 18 minutes, 13 seconds 114.3 cr in last quarter to 91.4 cr this quarter. This is mainly due to reversal of conservative a provision on account 18:21 18 minutes, 21 seconds of realization in this quarter as well as two of year end provision taken last quarter being the year end. The adjusted 18:29 18 minutes, 29 seconds was 20.1% compared to 18.3% last quarter and 17.4% 4% in the same quarter last year. The company has been able to 18:37 18 minutes, 37 seconds report robust margin presented through operational leverage, improved revenue mix and favorable exchange rates. 18:44 18 minutes, 44 seconds The RSV cost under management incentive plan is rupees 6.4 cr compared to rupees 7 cr last quarter. Aida net of RS 18:53 18 minutes, 53 seconds expense is 19% as again 17.1% last quarter. Getting down to depreciation amortization, the total expense was 19:00 19 minutes rupes 21.5 cr compared to 19.3 cr last quarter. This includes rupees 9.3 cr for intangible capitaliz on account of past 19:08 19 minutes, 8 seconds acquisitions. Nonic expenses are on account of severance payment for certain redundant positions. Interest expenses 19:17 19 minutes, 17 seconds rupees 9.6 cr compared to 6.8 cr last quarter. Increase is on account of four quarter impact of debenture interest. 19:24 19 minutes, 24 seconds Other income was rupes 13.1 cr compared to income of 2 cr last quarter for effective 1st January we have adopted 19:32 19 minutes, 32 seconds hedge accounting where the effective portion of changes in fair value loss amounting to rups 18 cr has been recognized in the hedge reserve under 19:40 19 minutes, 40 seconds equity. This will be reclassified to profit and loss account when the corresponding hedge transaction occur. 19:47 19 minutes, 47 seconds Earlier we used to mark to market search gain or loss. But now we have aligned with most of the IT companies which follows hedge accounting. Further we had 19:55 19 minutes, 55 seconds an exchange gain of rupees 11.3 cr compared to exchange loss of 10 lakhs last quarter. Further the other income 20:02 20 minutes, 2 seconds comprised of interest income of rupes 60 lakh this quarter compared to 1 cr last quarter. During the quarter the average rate was USD and euro were 91.48 and 20:12 20 minutes, 12 seconds 107.12 respectively. as against last quarter average rate of USD 89.06 and 20:19 20 minutes, 19 seconds euro 103.65 respectively. These are the two main currencies for our system. As at year end we have total forward 20:26 20 minutes, 26 seconds covered of 46.25 million with average rate of 91.13. 20:31 20 minutes, 31 seconds Our tax expense was rupes 24.2 cr this quarter as against 9.4 cr last quarter. 20:37 20 minutes, 37 seconds Effective tax rate is around 27% due non-deductibility amortization for intangible acquired through acquisition 20:44 20 minutes, 44 seconds as offset by certain tax dup. Our normalized effective tax rate is around 28%. 20:51 20 minutes, 51 seconds Net profit after tax was rupes 65.4 cr or $7.2 million compared to rupees 36.4 20:58 20 minutes, 58 seconds cr or $4.1 million last quarter. Basic EPS for the quarter was rupes 5.52 compared to rups 3.08 last quarter. 21:06 21 minutes, 6 seconds Adjusted EPS for the quarter is rupees 6.4 as compared to 5.1 last quarter. 21:12 21 minutes, 12 seconds With this uh let me hand over to the team for closing remarks. 21:17 21 minutes, 17 seconds Thank you. Thank you Nant. Um [clears throat] coming back to you know uh this is uh slide number 10 and um I 21:26 21 minutes, 26 seconds usually take a view of the market and um uh provide how we are how we are seeing it and uh and what it means for us. So 21:35 21 minutes, 35 seconds uh we ourselves had conducted a a research study covering over 200 plus organizations to look at how the 21:42 21 minutes, 42 seconds mid-market players are adopting AI and and how are they scaling it and some of the findings of that result of course 21:50 21 minutes, 50 seconds you know that helps us in kind of building our um our narratives and our offerings to the market. The survey in 21:57 21 minutes, 57 seconds this global midmarket u also authored by jointly by Everest group shows that almost 43% of the organizations are 22:06 22 minutes, 6 seconds leaprogging directly from uh the classical ML and uh you know um advanced 22:12 22 minutes, 12 seconds analytics directly to agentic AI models without going through uh uh a middle phase of using generative AI and 22:20 22 minutes, 20 seconds generative AI solutions. there are almost 64% organizations that show high 22:26 22 minutes, 26 seconds adoption of um you know um of AI in various things but the actual productive 22:34 22 minutes, 34 seconds deployment is only at about 15%. This gap between where the organizations are already spending and doing stuff on AI 22:42 22 minutes, 42 seconds versus only 15% getting it deployed is the clear opportunity for organizations like us to help those organizations 22:49 22 minutes, 49 seconds realize value from uh their AI investments and that's that's really the big market which is which is available to us. 22:59 22 minutes, 59 seconds Second point uh as we saw through the survey and also through our experience throughout the year uh getting ROI from 23:06 23 minutes, 6 seconds AI is not really a tool question. It is an AI talent question and our moves in training our people and having all our 23:14 23 minutes, 14 seconds people trained on AI with 1400 plus people AIE EV certified is a great asset and a differentiator uh to be able to service the market in a proper manner. 23:25 23 minutes, 25 seconds So if you look at the trends that are shaping this year, of course, organizations are uh running towards adopting AI in whatever manner, but also 23:34 23 minutes, 34 seconds 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 23:43 23 minutes, 43 seconds 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. 23:53 23 minutes, 53 seconds Legacy modernization continues to be a very large total addressable market uh and across all sorts of uh companies 24:02 24 minutes, 2 seconds whether they are dealing with legacy code bases, legacy data estates or reporting landscapes that they want to modernize. We have ourselves seen uh 24:10 24 minutes, 10 seconds significant wins in this area both last year and this year as well. uh enterprises uh have begun to recognize 24:18 24 minutes, 18 seconds that engineering velocity is a key differentiator in achieving uh ROI from AI initiatives and this has been our 24:26 24 minutes, 26 seconds narrative on Exico right from day one that through our AI studio in Exo we deliver engineering velocity because 24:34 24 minutes, 34 seconds finally with the same commercially available tools everybody can potentially theoretically achieve the same outcomes but the gap between those 24:41 24 minutes, 41 seconds who achieve the outcomes versus those who don't is really the engineering velocity that is brought in by AI 24:48 24 minutes, 48 seconds experts who do it the first time right and get the get the efficient solutions rolled in uh in an enterprise ready 24:56 24 minutes, 56 seconds manner very quickly. I think all of these forces that are shaping up uh and the way we have prepared ourselves over 25:04 25 minutes, 4 seconds the last uh you know year or 20 months is definitely um going to create a convergence. we are seeing that kind of 25:12 25 minutes, 12 seconds momentum in the market and we are very hopeful that it will continue to help us and become a tailwind for us. So with 25:19 25 minutes, 19 seconds that I'll end the presentation and um and open up for questions. 25:26 25 minutes, 26 seconds Thank you very much. We will now begin with a question and answer session. 25:31 25 minutes, 31 seconds Anyone who wishes to ask a question may press star and then one on the stone telephone. 25:37 25 minutes, 37 seconds If you wish to remove yourself from the question queue, you may press star and then two. Participants, you are 25:44 25 minutes, 44 seconds requested to use handsets while asking a question. 25:48 25 minutes, 48 seconds Ladies and gentlemen, we will wait for a moment while the question assembles. 25:56 25 minutes, 56 seconds A reminder to all you may press star and then one to ask a question. 26:09 26 minutes, 9 seconds We will take the first question from the line of Sep Sha from Equir Securities. Please go ahead. 26:16 26 minutes, 16 seconds Yeah, thanks. Thanks for the opportunity. Uh sir, first question in terms of the AI impact on the SDLC 26:24 26 minutes, 24 seconds software development life cycle. So where various industry research report indicates SDLC may have relatively 26:32 26 minutes, 32 seconds higher impact versus others. So how are you witnessing such kind of 26:39 26 minutes, 39 seconds conversation with the clients about opportunity or a threat? Uh I do agree that we have done a lot of development 26:47 26 minutes, 47 seconds in terms of pivoting from uh the just the manpower kind of a delivery to AI 26:54 26 minutes, 54 seconds delivery. But uh will this have immediate impact on the growth where clients are upfronting asking and 27:01 27 minutes, 1 second demanding AIEL productivity gain pass on versus revenue recognition may happen later. 27:10 27 minutes, 10 seconds So Seps and again you know thanks for um always 27:16 27 minutes, 16 seconds being uh the first one to ask. Um so clearly look um AI in DLC is is a huge 27:24 27 minutes, 24 seconds area and um and our report also suggests that SDLC is one of the uh one of the largest areas that gets impacted and has 27:34 27 minutes, 34 seconds the best outcomes and returns. We ourselves have been using AI and SDLC for for like I said over the last 20 27:41 27 minutes, 41 seconds months developed a lot of reusable assets. Our Optima AI platform actually boasts almost around 50 plus agents, 27:49 27 minutes, 49 seconds more than 1500 prompts and bunch of other reusable uh components that actually enable CI and SDLC to be 27:57 27 minutes, 57 seconds enterprise ready. Now to the second part of your question and I think you know um I've said this in the past also SDL AI 28:05 28 minutes, 5 seconds in SDLC is a huge uh benefit or efficiency gainer for uh for for all parties. For us who are doing the work, 28:13 28 minutes, 13 seconds we can do the work in in in a much lesser effort and much lesser time and for for the customer it is an outcome 28:20 28 minutes, 20 seconds which can be delivered in a much faster manner with high efficiencies. Now does that create a a risk for us or an 28:27 28 minutes, 27 seconds 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 28:35 28 minutes, 35 seconds 90% of our revenue is coming from discretionary spend where we doing project work for our customers. What that means is that it does not take away 28:43 28 minutes, 43 seconds anything from us right it's not that we are doing some uh support maintenance etc in a very traditional manner which 28:50 28 minutes, 50 seconds will now shrink in size because of AI in fact what it does is because we are constantly going after that 28:57 28 minutes, 57 seconds discretionary spend and new projects every time every new project that we bid for is already bid in a in a much more 29:05 29 minutes, 5 seconds efficient manner which keeps us you know ahead of the competition um I I think it is uh it [clears throat] 29:13 29 minutes, 13 seconds is uh almost impossible for us to think today that we will bid for a project or a new development, enhancement, modernization, migration, whatever it is 29:22 29 minutes, 22 seconds without putting AI into it and that's become the norm and it it gives it acts as a competitive advantage for us. It gets us into those deals and we win 29:30 29 minutes, 30 seconds those deals. So netn net it is expanding the target market total addressable market for us and we are winning those 29:38 29 minutes, 38 seconds 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 29:47 29 minutes, 47 seconds of time and effort to do [clears throat] it but on the other side since the target market or total addressable 29:54 29 minutes, 54 seconds market has expanded it overcompensates for it. I hope that answers your question. 30:00 30 minutes Yeah. Yeah. And so just further to this uh in the last few days uh the frontier model vendors like Enthropic and OpenAI 30:10 30 minutes, 10 seconds also announcing floating their uh IT services company in association with some of the global investment bankers uh 30:18 30 minutes, 18 seconds where they want to tap the small and mediumsiz enterprises. So I do agree it's early days uh may not have a view 30:27 30 minutes, 27 seconds but how do you see this kind of an announcement from the frontier model is will it be a big competitive threat? 30:37 30 minutes, 37 seconds So big or small only time will tell Sep. 30:39 30 minutes, 39 seconds But the first thing that I see with that is it validates two points. Number one it validates that um you know AI is 30:48 30 minutes, 48 seconds 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 30:56 30 minutes, 56 seconds 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 31:05 31 minutes, 5 seconds right kind of people in the equation to make those tools work and to deliver the enterprise benefit. So one it is a huge 31:12 31 minutes, 12 seconds validation of what we have been saying and and also doing is that it is a people issue not a tools issue. Everybody has the same commercial tools. 31:21 31 minutes, 21 seconds Number two, it is and if it comes down to talent, it is about what kind of talent are they going to be assembling 31:29 31 minutes, 29 seconds up and hence at what price point and how will they be able to serve the mid-market organizations. Clearly uh 31:37 31 minutes, 37 seconds sure they have a game plan. There are large private equity companies who are joining hands and forces. So there will be some some play over there. But the 31:46 31 minutes, 46 seconds market is so big that again it becomes availability of talent, right kind of 31:52 31 minutes, 52 seconds talent in the right places at the right cost, right? And that obviously is not 32:00 32 minutes 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, 32:07 32 minutes, 7 seconds bringing them in front of the client, etc. Sure they will become a competition but if as a total it expands the market 32:15 32 minutes, 15 seconds and there are one more player in it where I'm already you know a player who's playing I think there is enough to go around and we all will have a 32:24 32 minutes, 24 seconds significant piece to to kind of work with. So right now I see it as validation of what we are doing and as 32:31 32 minutes, 31 seconds they as they really grow their feet and and and hit the ground we'll start seeing what kind of competition they become. 32:41 32 minutes, 41 seconds Okay. Okay. Fair enough. And just last few and then I will come in the followup. Uh it seems the growth could 32:48 32 minutes, 48 seconds have been driven by full quarter consolidation of Noviggo in this quarter and there could be a possible decline in 32:55 32 minutes, 55 seconds the organic revenues which could be also due to a seasonal week where higher number of holidays being there on a Q on 33:03 33 minutes, 3 seconds Q in the first quarter. So uh do you believe this is a quarterly operation and we can organically uh have a growth 33:13 33 minutes, 13 seconds turnaround starting again from the second quarter and ACV which we have disclosed in this quarter is on a same 33:21 33 minutes, 21 seconds definition excluding no correct. 33:27 33 minutes, 27 seconds So let me answer the three parts in uh three different this thing. Number one um we do have the benefit of full 33:35 33 minutes, 35 seconds quarter consolidation of Noviggo. So no doubt about it. However, uh you know, just wanted to clarify and this question 33:42 33 minutes, 42 seconds may come up later again is that um you know the Noviggo revenues uh though they are a full quarter this was the first 33:50 33 minutes, 50 seconds full quarter of Noviggo that um that got consolidated with our systems and this was also the first fiscal year end for 33:57 33 minutes, 57 seconds Noviggo um that happened together with us as a result uh and which is the right practice to do we have aligned a lot of 34:05 34 minutes, 5 seconds their accounting practices to align with our systems practice practices u including uh you know accounting policies and and revenue recognition 34:13 34 minutes, 13 seconds norms etc. U as u as a result of which you know there is a certain amount of uh uh revenue recognition change that has 34:22 34 minutes, 22 seconds taken place uh going from uh you know gross basis to net basis on some certain kind of license revenues uh some norms 34:30 34 minutes, 30 seconds on fixed price accounting and those kind of things. So uh what we had uh originally u you know 34:39 34 minutes, 39 seconds what you may have in mind is what what we had given as the size of you know noiggo revenues fullear revenues when we 34:47 34 minutes, 47 seconds had acquired the company uh at about $32 million a year. Um that restated will 34:53 34 minutes, 53 seconds stand at about 21 $22 million a year. Um and as a result you would see that you know yes there is small amount of 35:02 35 minutes, 2 seconds degrowth in quarteronquarter basis because of course you know there's a reduction number of days versus Q4 and uh and like Danji said in his uh in his 35:11 35 minutes, 11 seconds financial statement uh readout that we also had benefits of some u fixed price project two-ups in Q4 as they normally 35:20 35 minutes, 20 seconds take place. But having said that you know we um uh we have largely remained flat organically and uh we have very 35:28 35 minutes, 28 seconds strong deal momentum and we very confident that uh the uh organic growth continues to be there and we continue to 35:36 35 minutes, 36 seconds gain the market share and we'll continue to grow. No adds to that and uh and and they they also continue to grow in their 35:44 35 minutes, 44 seconds in their markets. they obviously were also impacted by the Middle East crisis uh to some extent in Q1. Uh so that 35:53 35 minutes, 53 seconds hopefully will be a thing uh behind us and then um that will contribute to positive growth in that front as well. 36:01 36 minutes, 1 second Um so overall u I don't see any challenges to um uh to the positive 36:09 36 minutes, 9 seconds outlook for u uh for this quarter as we as we are in in Q2 and we'll continue to report accordingly. 36:18 36 minutes, 18 seconds Okay, thanks. Uh we'll come in the follow. 36:24 36 minutes, 24 seconds Thank you. We will take the next question from the line of Vin Manon from Monarch Capital. Please go ahead. 36:31 36 minutes, 31 seconds Uh hi sir. Hi, thank you for the opportunity. A couple of questions from my side. uh one we recently you know read that Blackstone has you know 36:38 36 minutes, 38 seconds partnered up with Anthropic and a couple of other private equities are also there and they're planning basically to deploy 36:45 36 minutes, 45 seconds their engineers within the organization and even to you know uh the portfolio companies within Blackstone now that that is an area where we have done well 36:54 36 minutes, 54 seconds over the last year year and a half. So how do you see this playing out and and could this kind of model threaten uh you know other mid-market players as well? 37:05 37 minutes, 5 seconds So V first again thanks for joining in and um uh and for your question. So yeah Blackstone and bunch of other private 37:13 37 minutes, 13 seconds equities have joined in to put in money in what uh would eventually be uh some kind of a consulting company with 37:21 37 minutes, 21 seconds Enthropic etc. And you know without reading too much into it uh whether it's um any private equity you know they are 37:29 37 minutes, 29 seconds all uh going to look at a good opportunity as an investment opportunity and and would invest. So I'm not reading 37:37 37 minutes, 37 seconds uh too much into that. uh going back to whether whether this will uh you know 37:43 37 minutes, 43 seconds get deployed across uh PE port codes or or mid-market companies and they will 37:50 37 minutes, 50 seconds benefit from it possibly all of that. uh obviously early days you know they they need to stand up the team and u and and 37:58 37 minutes, 58 seconds build the team and build their playbooks like I was saying earlier uh I see it as a strong validation of of our playbooks 38:07 38 minutes, 7 seconds that you know value from AI uh and ROI will come through engineering velocity and you need those kind of uh AI 38:15 38 minutes, 15 seconds specialists to be able to implement it in a manner uh that it brings that velocity. It is also a combination of understanding your client's business and 38:24 38 minutes, 24 seconds how they are going to use AI which we believe we have developed over you know over the last 20 30 years of working 38:31 38 minutes, 31 seconds with clients in various industries in learning their business and then understanding how we can impact. Um 38:38 38 minutes, 38 seconds that's again something that uh will be slightly challenging to stand up over overnight. But having said that you know 38:47 38 minutes, 47 seconds um when it comes to Blackstone business we have continued to win against competition uh I have said that uh 38:55 38 minutes, 55 seconds earlier in many calls as well uh we are lucky to be part of Blackstone portfolio because we do get introduced to various 39:03 39 minutes, 3 seconds portfolio companies and and have a have a quicker path to having a conversation with them but beyond that I have to win 39:12 39 minutes, 12 seconds 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 39:21 39 minutes, 21 seconds neither uh neither us nor them will get pushed into an account as like somebody 39:28 39 minutes, 28 seconds has is mandated to use uh either of us, right? So we will have to continue to play out play to our strengths and we 39:34 39 minutes, 34 seconds believe that the experience we have that the platform we built uh which is 39:42 39 minutes, 42 seconds directly targeted towards delivering ROI to enterprises and all our working practices will continue to hold us in 39:50 39 minutes, 50 seconds goodstead. They will have their strengths and just like any competition we will have to measure up their strength and then uh continue to pivot 39:58 39 minutes, 58 seconds on our playbooks to make sure that we continue to win. So right now it's a lot of hypothetical win. Um they don't 40:06 40 minutes, 6 seconds really have a company today. So we'll we'll keep a good watch on it and clearly see you know how it plays out. 40:13 40 minutes, 13 seconds Okay. Thanks for that. And and in terms of the ACV if you can like you have mentioned that you know the deal sizes are coming down. So if you can just 40:21 40 minutes, 21 seconds mention what kind of deal sizes were there which which we've added this quarter and uh you know you said the time is increasing so a little bit more color on that would be helpful. 40:32 40 minutes, 32 seconds So when I when I say deal sizes are coming down uh I don't mean deal sizes for us are coming down. What I meant was that a deal which in delivered in 40:41 40 minutes, 41 seconds traditional manner uh would have been X now because of AI can be delivered in a in a in a much lesser than X kind of a 40:50 40 minutes, 50 seconds thing right but for us on the other hand average deal sizes are gone up because we are now being able to you know as we 40:58 40 minutes, 58 seconds 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, 41:07 41 minutes, 7 seconds you know, build one feature or or put a put a uh sprint team together and put a pod of people has now converted to 41:16 41 minutes, 16 seconds conversations where we're like here is a large application the 3 million lines of code written in legacy can you migrate 41:24 41 minutes, 24 seconds it in a short period of time using AI and we would we would have that as probably a million dollar deal right 41:31 41 minutes, 31 seconds now that itself in the past could have been a one and a half or $2 million deals which is now a million dollar because it is it is done through AI but 41:40 41 minutes, 40 seconds for us deal sizes because of this new TAM our deal sizes are still improving 41:46 41 minutes, 46 seconds right so the market may look at it as okay you know it takes much lesser to do the same thing that's the AI efficiency 41:55 41 minutes, 55 seconds but we are benefiting from it because we are able to play in that new time and and build our deal sizes accordingly 42:04 42 minutes, 4 seconds okay and just last one thing that SG GNA uh came down you know this quarter. I just wanted to get a idea on how it will 42:11 42 minutes, 11 seconds be going on right because uh we obviously we in terms of the growth we are doing I think you know it should normalize maybe in the next few quarters. 42:19 42 minutes, 19 seconds Yeah. SGNA coming down is not a reflection of any reduction in investment or people neither in sales 42:26 42 minutes, 26 seconds nor in nor in GNA. It's actually and Nani would probably explain it if uh if needed in detail. uh Q4 being the last 42:35 42 minutes, 35 seconds quarter and uh you know before closing the books we have to provision for any AR etc and uh and through uh whatever 42:44 42 minutes, 44 seconds follow-ups etc in Q1 we ended up collecting all of that AR and that reversal is what you know kind of 42:51 42 minutes, 51 seconds reflects in the reduction of LGNA so it's u our our investments in sales and marketing and all of those are intact in 42:59 42 minutes, 59 seconds fact we continue to increase those and um and hence you know when we look at going forward perhaps you know u I think 43:08 43 minutes, 8 seconds this quarter we're talking about 10 million it will probably our our normal run rate is at 11 11 something and we'll come back to that 43:17 43 minutes, 17 seconds okay thank you I'll get back in that thank you sure thank you next question is from the line 43:23 43 minutes, 23 seconds of g from dam capital please go ahead hey hi uh thanks for the opportunity uh 43:31 43 minutes, 31 seconds had couple of uh things that I wanted to understand. Um uh firstly uh now that uh uh NVGO has been fully integrated uh 43:41 43 minutes, 41 seconds within uh within our systems uh and as I understand it is that it has relatively larger uh set of customers. So have we 43:50 43 minutes, 50 seconds been able to make any inroads uh with our system delivery portfolio uh for uh particularly uh you know uh no clients? 43:59 43 minutes, 59 seconds I know it's early days but anything that you want to Yeah sure and thanks for that question. 44:08 44 minutes, 8 seconds Uh while it is early days but right from day one we um uh we have focused on getting our uh go to markets aligned and 44:17 44 minutes, 17 seconds making sure that uh both Noviggo and our systems are able to leverage each other's capabilities. very happy to say 44:23 44 minutes, 23 seconds that today uh there are at least u I would say close to a dozen deals where Noviggo and our systems teams are 44:31 44 minutes, 31 seconds cross-engaged and at least maybe three clients where uh where Novivo clients 44:39 44 minutes, 39 seconds have received our systems service delivery because of competencies or new capabilities that we sold to them and at 44:47 44 minutes, 47 seconds least one client where our systems client is using noigos competence to deliver. So that kind of cross leverage 44:55 44 minutes, 55 seconds already happening. That's the fundamental uh premise of you know doing an acquisition uh which complements us 45:03 45 minutes, 3 seconds in capabilities and so that we can we can expand our offerings with our clients. So absolutely we're seeing the evidence of that taking place. 45:13 45 minutes, 13 seconds Understood. Understood sir. Yeah. And also wanted to understand uh organic uh growth in this quarter. you said uh that 45:20 45 minutes, 20 seconds it is uh flattish uh however if we include one and a half months of uh nogo 45:27 45 minutes, 27 seconds acquisition uh which could contribute uh nearly about 5 6% uh to the growth rate even if there's some reduction in the 45:35 45 minutes, 35 seconds revenues then also there would be around 3% of the the revenues which will be 3 to 4% which will be uh you know which 45:45 45 minutes, 45 seconds will be from the mobile acquisition incrementally so just from that perspective wanted to understand what would be the organic growth in this 45:53 45 minutes, 53 seconds quarter and secondly also the outlook uh for this year uh how are we thinking about growth uh in this particular year 46:02 46 minutes, 2 seconds uh uh organically from the R system perspective. 46:08 46 minutes, 8 seconds So like I said you know uh given that last quarter we had uh half a quarter of uh of noiggo coming in this quarter full 46:17 46 minutes, 17 seconds quarter and the adjustments to accounting policies as well as you know some amount of uh you know fixed price 46:25 46 minutes, 25 seconds uh two-ups etc that took place. I think uh the last quarter numbers do not provide a very clear uh straight line 46:33 46 minutes, 33 seconds method to to look at uh you know top line in in that manner. Good news is that all those adjustments all those 46:41 46 minutes, 41 seconds alignments to accounting policies etc have already been done. So what we are what what you're seeing as this quarter 46:47 46 minutes, 47 seconds numbers is a good baseline to understand what the combined numbers look like and like I said you know uh and maybe on a 46:56 46 minutes, 56 seconds one-on-one Nanji can provide a little more detail but uh you know overall uh we've grown and uh uh as a company uh 47:06 47 minutes, 6 seconds like I said organically this quarter was flat but uh that's again uh largely due 47:14 47 minutes, 14 seconds to reduction of days and and some fixed price true ops in Q4. We have uh we won 47:20 47 minutes, 20 seconds new business and uh our overall uh while we don't provide any forward guidance 47:26 47 minutes, 26 seconds and and flavors but very high confidence that uh both organically as well as combined entities uh we are on the right 47:35 47 minutes, 35 seconds trajectory uh for for uh you know doing what we what we promise to to our 47:43 47 minutes, 43 seconds investors to to continue to grow the organization. If you look at IIDA numbers, uh we have delivered on on the 47:50 47 minutes, 50 seconds IITas promised and uh because none of the accounting adjustments impact, you know, uh our overall AIDA and uh profit 47:59 47 minutes, 59 seconds margins and we've posted a very strong uh uh number with 12.6 million there and we continue to uh be positive about uh 48:09 48 minutes, 9 seconds capability to maintain our overall AIDA in the line. 48:14 48 minutes, 14 seconds Sure. And sir lastly uh wanted to understand in terms of uh the the uh you 48:20 48 minutes, 20 seconds know uh are are we seeing any trends where you know GCC's are uh being 48:27 48 minutes, 27 seconds established by the mid-market players as well and uh is that a risk to our client 48:34 48 minutes, 34 seconds base as of now or do you see that maybe uh uh this can be opportunity in terms of the GCC revenue that we uh might get from potential and new clients. 48:47 48 minutes, 47 seconds So, Anmul, we had launched uh our own GCC services like six quarters ago uh when we started helping mid-market 48:55 48 minutes, 55 seconds customers to establish their COE's uh create their GCC's or participate in their GCC scaleup offerings. Uh we have 49:05 49 minutes, 5 seconds uh successfully helped uh close to eight or nine organizations in various stages of their GCC formations. What we see is 49:14 49 minutes, 14 seconds that when customers decide and they want to have a GCC u you know they uh they will obviously want to do that but when 49:22 49 minutes, 22 seconds they do it with us they have a much higher chance of uh establishing a successful GCC or COE whichever name 49:30 49 minutes, 30 seconds 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 49:38 49 minutes, 38 seconds sustainable business uh 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 49:47 49 minutes, 47 seconds partners. So yes, we uh we do know that there is uh always going to be and you know at least in midm market it's a uh 49:56 49 minutes, 56 seconds it's something that every mid-market player is looking at that they will look at GCC plays but they also want experts 50:03 50 minutes, 3 seconds like us to work alongside and we are using that as an opportunity for our growth. 50:10 50 minutes, 10 seconds Understood and is and lastly one uh very industry specific question that I uh wanted to ask uh is uh you know how are 50:18 50 minutes, 18 seconds we seeing uh the token cost uh particularly right now when we are using AI models and who is bearing that cost 50:25 50 minutes, 25 seconds whether the client is building it or we are bearing it and does it differ in time and material versus outcome based contract on who bears this cost. 50:36 50 minutes, 36 seconds So token cost for output delivered to the client is usually uh in I would say in almost 100% cases born by the client 50:44 50 minutes, 44 seconds either either they u they provide us uh subscription to the frontier model that 50:51 50 minutes, 51 seconds they they are subscribed to or we would do it but we'll pass on the costs. So to that extent the token costs uh does 50:58 50 minutes, 58 seconds belong to the client. We also end up incurring uh our own token cost because of the trainings because of our own you know COE R&D development etc that we do. 51:09 51 minutes, 9 seconds uh we believe that uh our ability to deliver AI with uh most optimal token 51:17 51 minutes, 17 seconds costs is one of the differentiators because we built PHOPS models within our AI ecosystem in Optima AI and that is 51:25 51 minutes, 25 seconds 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 51:33 51 minutes, 33 seconds costs would be. we are at least able to give them a clear metering of what the costs are and how the costs um are going 51:40 51 minutes, 40 seconds to be reduced. But to your question, most of those costs when delivering to the clients belong to the clients. 51:49 51 minutes, 49 seconds Okay. Okay. Sure sir. Thanks for answering. 51:55 51 minutes, 55 seconds Thank you. We will take the next question from the line of Vun Kulkarni from Enredc. Please go ahead. 52:02 52 minutes, 2 seconds Hi. Uh good morning. Uh thanks for taking my question. Uh so my the question on DC has already been answered so I'll probably skip that. Uh some 52:11 52 minutes, 11 seconds basic questions would be uh in terms of the AI and nonAI is there a revenue split or is it too nent at this point to actually give that a split? 52:22 52 minutes, 22 seconds It is um well we do we do try and uh keep a track of how our AI revenue is developing because obviously uh with all 52:31 52 minutes, 31 seconds the investments we are making it's not u it's not uh coming from a system so uh we're not reporting it yet but just to 52:39 52 minutes, 39 seconds give you an idea approximately 29% of our revenue today comes from AI and AI enabled services 52:47 52 minutes, 47 seconds got that and um I don't know uh I I just wanted to ask you in terms of the total employee headcount uh do we report that 52:54 52 minutes, 54 seconds number because it's not there in the investor PPT and what would be the attrition rate uh at this point 53:02 53 minutes, 2 seconds so we report the total headcounts it's part of the press release you would be able to see it there we are about 5,400 employees globally 53:10 53 minutes, 10 seconds and uh attrition currently is running at uh I believe approximately 11% which is uh you know lower than the industry 53:20 53 minutes, 20 seconds sure and uh Another very basic question uh in terms of the vertical. So uh do we uh in do we have a split for that and 53:28 53 minutes, 28 seconds also are we seeing in which in which uh vertical are we seeing optimum usage of AI at this point and going forward where 53:36 53 minutes, 36 seconds are we anticipating uh this you know the the AI implementation to be more in like which which sector 53:46 53 minutes, 46 seconds um to answer the first part we do share the split again it's part of the press release uh tips which is tech internet 53:54 53 minutes, 54 seconds platforms and services is our largest vertical. It contributes about 40% plus of our revenues. Uh being the entire 54:01 54 minutes, 1 second technology product space, you know, obviously it's a very fast adopter of AI. So from our perspective, we do see a 54:08 54 minutes, 8 seconds lot of usage of AI in that space. Uh we our second third largest vertical are telecom media, entertainment and 54:16 54 minutes, 16 seconds healthcare. And again in those spaces we are seeing AI adoption happen at various paces depending on again the maturity 54:23 54 minutes, 23 seconds and size of the customer. I think the jury is still out in terms of who or which industry will lead the AI race. 54:30 54 minutes, 30 seconds But clearly you know um tech companies are definitely eating their dog food. 54:35 54 minutes, 35 seconds So, uh, tech companies will continue to lead this for some time before other industries start catching up and and have enough investments to say that 54:44 54 minutes, 44 seconds they're doing more AI than than the tech companies themselves. 54:49 54 minutes, 49 seconds Just a small correction, uh, vertical we report as part of annual report but not in the quarterly press release. 54:56 54 minutes, 56 seconds Okay. No, I stand corrected. Thanks for thanks for that information. Yeah, but it's part of our annual report. Yeah. 55:01 55 minutes, 1 second Yeah, that's but it's more or less uh you know same you know like not the same. 55:07 55 minutes, 7 seconds Okay. Yeah, that's that's what I thought. Sure. Sure. Yeah, that these are the only questions from my side. Thanks. 55:15 55 minutes, 15 seconds That should be the last question. Yeah, take the last question please. 55:20 55 minutes, 20 seconds Thank you. We will take the last question from the line of Mayang Babla from Chameleon EMC. Please go ahead. 55:29 55 minutes, 29 seconds I am audible. 55:31 55 minutes, 31 seconds Yes, yeah, thank you for taking my question. 55:34 55 minutes, 34 seconds Uh, so the question was uh around you know your AI offerings be it the Exeico AI studio or uh the Optima AI platform. 55:44 55 minutes, 44 seconds Uh could you pinpoint when you know you know which specific problem statements um are you trying to uh solve with within the enterprise architecture with this? 55:54 55 minutes, 54 seconds So u ExoAI studio is uh like I said earlier it's a people plus platform and orchestration and the platform in there 56:03 56 minutes, 3 seconds is optimi. So it's one and the same thing and if you look at our uh exco.ai website it very clearly also lays out we 56:13 56 minutes, 13 seconds are basically uh addressing three uh essential problems or addressing three narratives. We are doing uh AI for 56:22 56 minutes, 22 seconds achieving uh acceleration in SDLC the software development life cycle. This is the core bread and butter of our 56:29 56 minutes, 29 seconds business. We do engineering for a living and now we are doing engineering with AI and we are helping companies accelerate their software development life cycle 56:37 56 minutes, 37 seconds using AI. Second, we are addressing a specific component which is about doing legacy modernization. Like I've said, 56:44 56 minutes, 44 seconds it's a massive uh uh time for us and for everyone and legacy modernization, whether it is legacy codebase, whether 56:52 56 minutes, 52 seconds it is legacy data estate or legacy reporting infrastructure, we are able to modernize it using AI from anything to a 57:01 57 minutes, 1 second modern stack and do it in a manner that you know we like we love to call it. We change it from blackbox to glassbox. The 57:09 57 minutes, 9 seconds third uh playbook that we are addressing is AI for business objectives. And this is where right from customer experience 57:16 57 minutes, 16 seconds uh contact center customer service all the way to deep down deep uh business domain uh workflows which can be now 57:24 57 minutes, 24 seconds done agentically and uh for example whether it is you know insurance claims process whether it is revenue cycle management process in healthcare whether 57:33 57 minutes, 33 seconds it is KYC process in banking or it is bunch of the horizontal processes in the CFO area whether account receivables 57:40 57 minutes, 40 seconds payables you know uh the P2P match ing the three-way matching of invoices, bunch of those things which can now be 57:47 57 minutes, 47 seconds done agentically and we've built end-to-end agent ecosystems orchestrated together to accomplish these kind of uh 57:56 57 minutes, 56 seconds business objectives. So three problem statements that we are addressing SDLC modernization and business workflows. 58:04 58 minutes, 4 seconds Sure. Sure. And if you had to highlight uh you know the differentiation or mode uh this platform has versus uh platform 58:13 58 minutes, 13 seconds offerings by peer IT companies what would that one or two modes that would be for you know as your right to win versus others. 58:23 58 minutes, 23 seconds So u our right to win uh is built on the fact that this platform while we don't sell the platform this platform is 58:31 58 minutes, 31 seconds essentially providing uh reusable artifacts across all of these three uh narratives that I talked about and uh 58:41 58 minutes, 41 seconds and enables any organization to achieve enterprise ready AI outcomes within a 58:48 58 minutes, 48 seconds matter of weeks because all the essential elements we built this like a five layer take all the essential elements of security, guardrails, usage 58:56 58 minutes, 56 seconds policies, uh token optimizations, uh specific compliances, all of those 59:03 59 minutes, 3 seconds things are pre-built that can be applied directly to any enterprise in a matter 59:10 59 minutes, 10 seconds of weeks. And this is something that organizations take six months to build u with with uh expert talent also. So once 59:19 59 minutes, 19 seconds that is done and with all the reusable agents assets or everything that's there and then our AIE EV trained talent and 59:27 59 minutes, 27 seconds you know again our differentiation is that AIE is not a certification that one can buy from outside it's a proficiency based framework that we've come out with 59:36 59 minutes, 36 seconds and and our people who know how to use AI especially all this enterprise ready AI assets which can then be deployed to 59:45 59 minutes, 45 seconds a client hence delivering the real ROI of achieving outcomes within months and that's what we show on the website also 59:52 59 minutes, 52 seconds almost you know 2x productivity almost 50% reduction in turnaround time and those kind of things. So that's what 59:59 59 minutes, 59 seconds creates the mode uh for us um with our clients wherever we we're using this. 1:00:06 1 hour, 6 seconds Thank you. Thank you for that. And just last question is a data point question. 1:00:10 1 hour, 10 seconds So uh how much does uh fixed price projects and time and material contribute to revenue and how has this 1:00:17 1 hour, 17 seconds mix changed over the last one and two years? 1:00:22 1 hour, 22 seconds So um traditionally the company's revenue was largely time and material based because that's how tech companies 1:00:29 1 hour, 29 seconds usually contract and u and and there were long-term you know customers where we are building um building products or 1:00:37 1 hour, 37 seconds feature sets for them etc. But as we've changed our offerings to more of these uh transformation offerings, especially 1:00:45 1 hour, 45 seconds uh data and AIEL, our business mix has obviously moved more towards fixed price and u AI will obviously lead to more 1:00:54 1 hour, 54 seconds outcome based pricing as well. uh while these numbers are not accurate to the point but approximately speaking uh what 1:01:03 1 hour, 1 minute, 3 seconds till last year would have been approximately let's say 10% fixed price has already last year as in 2024 has already probably changed to maybe closer 1:01:12 1 hour, 1 minute, 12 seconds to 15 or 16% in 25 and we believe that it will continue to move in the favor of fixed price as we go along and as we do 1:01:20 1 hour, 1 minute, 20 seconds more and more of these transformation objectives sure any target in over here if you can 1:01:26 1 hour, 1 minute, 26 seconds guess. M no not really because uh we have to play with uh what is the business uh that we are attracting and 1:01:36 1 hour, 1 minute, 36 seconds 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 1:01:44 1 hour, 1 minute, 44 seconds are better off doing uh AI objectives on fixed price basis versus serving the legacy mandates on time and material 1:01:52 1 hour, 1 minute, 52 seconds basis so I think it'll move along with the business mix change sure thank you so Thank you. 1:02:03 1 hour, 2 minutes, 3 seconds 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. Nesh for closing comments. Thank you and over to you sir. 1:02:15 1 hour, 2 minutes, 15 seconds Oh thank you so much and uh once again uh thanks to all participants and everybody who asked questions. uh like I've always observed uh you know these 1:02:23 1 hour, 2 minutes, 23 seconds questions uh act as a as a good uh you know input to us to continue to focus on all the right areas and things that if 1:02:32 1 hour, 2 minutes, 32 seconds we have uh you know um left out or not really considered then take them into consideration and I continue to enjoy 1:02:40 1 hour, 2 minutes, 40 seconds these calls and look forward to uh you know uh seeing you all on the next investor call in in a quarter from now. 1:02:50 1 hour, 2 minutes, 50 seconds Thank you. 1:02:50 1 hour, 2 minutes, 50 seconds Thank you members of the management. On behalf of our systems, that concludes this conference. Thank you all for joining with us today and numminina disconnect your lines. Thank you. 1:03:03 1 hour, 3 minutes, 3 seconds Thank you.