Kellton Tech Solutions Limited — Q3 FY26

Kellton Tech Solutions Ltd Q3 FY2025-26 Earnings Conference Call https://www.youtube.com/watch?v=IGEXDd6jSdo Published: 3 months ago

0:00 Ladies and gentlemen, good day and welcome to the Kelton Tech Solutions Limited Q3 and 9M FI26 earnings 0:07 7 seconds conference call. As a reminder, all participant lines will be in the listen only mode and there'll be an opportunity for you to ask questions after the 0:15 15 seconds presentation concludes. Should you need assistance during the conference call, please signal an operator by pressing star and then zero on your touchstone 0:22 22 seconds phone. I would like to thank you all for participating in today's company's earnings score for the third quarter of the financial year 2026. Before we 0:31 31 seconds begin, I would like to mention a short cautionary statement. 0:35 35 seconds Some of the statements made in today's concord may be forward-looking in nature and such forward-looking statements are subject to risk and uncertainties which should cause actual results to differ from those anticipated. 0:47 47 seconds Such statements are based on management beliefs as well as assumptions made from the information currently available to the management. Audiences are cautioned 0:54 54 seconds not to place any undue reliance on these forward-looking statements in making any investment decisions. 1:01 1 minute, 1 second The purpose of today's earnings call is purely to educate and bring awareness about the company's fundamental business and a financial quarter under review. 1:10 1 minute, 10 seconds Now I would like to introduce you to the management participating with us today. 1:13 1 minute, 13 seconds We have with us Mr. Naranjin Chintam chairman and wholetime director Mr. Karanjit Singh Chief Executive Officer India 1:22 1 minute, 22 seconds and Mr. Shinavas Porturi Chief Executive Officer US. 1:27 1 minute, 27 seconds I would now like to hand the conference over to Mr. Naranjan Chintam. Thank you and over to you sir. 1:40 1 minute, 40 seconds Mr. Renjan can you hear us? I'm sorry I was muted and speaking. 1:44 1 minute, 44 seconds Thank you Mike. Uh good evening, good afternoon and good morning to all of you for joining uh the Q3 earnings call. Uh 1:52 1 minute, 52 seconds want to start off with the financial highlights and then we'll talk about operational highlights as well as customer wins and u followed by you know questions and answers right behind that. 2:02 2 minutes, 2 seconds So I want to quickly talk about our financial uh results. I know we have published this but I go over it uh just 2:09 2 minutes, 9 seconds to be to uh give you uh a quick summary of it. So I will not go bore you with all the details but I'll go with the numbers that we have. Uh the revenue we 2:18 2 minutes, 18 seconds have achieved 308 crores compared to 300 crores of last quarter. Uh which is about 2.7 uh% growth uh over uh uh last 2:28 2 minutes, 28 seconds quarter. Uh and I was about uh 39.7 crores versus 37.8 for the last quarter. 2:34 2 minutes, 34 seconds Uh so we uh we have a 5% growth there. 2:37 2 minutes, 37 seconds Uh when it comes to the pack uh we are at 25.5 crores uh versus 24 crores over last quarter again a 5.8% growth. Uh the 2:47 2 minutes, 47 seconds ibida was around 12.9% and the pat margin is 8.3% uh whereas you know the last quarter for 2:54 2 minutes, 54 seconds pat was 8%. So they continuously show improvement when it comes to uh revenue as well as the bottom line. Going back 3:01 3 minutes, 1 second to the uh 9 months one uh the previous 9 months uh uh last 9 months was 95 crores 3:09 3 minutes, 9 seconds versus 8 812 crores the last year. Uh and when it comes to IITA we are at 113 3:16 3 minutes, 16 seconds crores versus 99.5 crores and IA margin was 12.5% versus you know 12.2 for the the 3:25 3 minutes, 25 seconds previous 9 months. Again the fat margin is at 8% for the whole nine months up to now and the previous year it was 7.4%. 3:33 3 minutes, 33 seconds The diluted EPS EPS is you know 1.4 uh rupees uh versus 1.3 rupees for the 9 months. When it comes to the quarter the 3:42 3 minutes, 42 seconds EPS stood at you know 50 pisa versus 40 pisa for the last quarter. So there is an improvement there too. With that I 3:49 3 minutes, 49 seconds want to hand over uh to kanji to talk about operational highlights and the customer events. Kanjit over to you. 3:58 3 minutes, 58 seconds Okay. So, uh yeah uh good evening everyone and thank you Nanjin. Uh so I will cover both the new customer wins as 4:07 4 minutes, 7 seconds well as the operational highlights. Uh so let me first start with the client wins. So I think I have a long list. We 4:14 4 minutes, 14 seconds have about 11 clients but I'll quickly go through some of them so that you sort of get a little bit of color on color on 4:22 4 minutes, 22 seconds these client wins. Uh so the first one that I would like to mention is basically a leading end-to-end product engineering 4:31 4 minutes, 31 seconds uh it's a global technology giant and we are engaged with them on the product engineering uh for cloudnative and 4:38 4 minutes, 38 seconds crossdevice web applications and uh we are basically uh doing this on enterprisegrade services like Microsoft 4:46 4 minutes, 46 seconds and on the on the back end is all architected on uh the uh on Azure The second one this is a very 4:55 4 minutes, 55 seconds interesting one is actually a legacy modernization. So the client is basically execute we are executing an 5:02 5 minutes, 2 seconds autonomous modernization strategy to transform their monolithic ERP environment uh which is built on a 4GL 5:09 5 minutes, 9 seconds into basically a hyperscalable uh net core microservices based uh 5:16 5 minutes, 16 seconds application. So this is uh what is interesting here is that this is basically not an upgrade in the same 5:23 5 minutes, 23 seconds technology stack. We are basically moving it from one language to another. 5:28 5 minutes, 28 seconds And this language is a old generation 4GL language. 5:32 5 minutes, 32 seconds And of course there is a heavy use of AI here. In fact in here we have written our own agents uh in fact we have used 5:39 5 minutes, 39 seconds AI for development on this one. So we have created our own agents that help us. It's about 4 million lines of code. 5:46 5 minutes, 46 seconds So obviously we cannot do it manually. 5:49 5 minutes, 49 seconds Uh we are basically leveraging AI heavily and in fact the latest cloud models uh to help with this. 5:56 5 minutes, 56 seconds Uh similarly we basically we are partnering with a world leader in heavy engineering where we're helping them 6:02 6 minutes, 2 seconds deploy AIdriven orchestration um systems which will help them you know 6:09 6 minutes, 9 seconds uh streamline their complex industry for uh you know driven manufacturing workflows. Obviously there is some amount of agentic intelligence being 6:17 6 minutes, 17 seconds built into their uh manufacturing workflows and large scale engineering projects. 6:24 6 minutes, 24 seconds Similarly we have basically uh we've we're driving a large scale application modern program again for a global leader 6:32 6 minutes, 32 seconds in food services and uh basically we're trying to help them with the data engineering and the AI transformation side of things. 6:42 6 minutes, 42 seconds Similar stuff we're doing with their uh with the large one of the largest providers of private tech in India. Uh 6:50 6 minutes, 50 seconds again where they're again trying to basically modernize or modernize their platform and basically uh inject AI 6:58 6 minutes, 58 seconds orchestrated engineering into the whole thing. We're also seeing a lot of traction on the service now uh side and 7:06 7 minutes, 6 seconds uh you know we've been uh uh in the service now thing and we had an acquisition there. So we basically are engaged with at least two three clients 7:15 7 minutes, 15 seconds now that we have run where we're helping them uh so one of them where we're helping them engineering high velocity 7:22 7 minutes, 22 seconds ached source to pay uh you know uh workflows uh this is again on the service now platform for a global 7:30 7 minutes, 30 seconds healthcare provider uh we doing uh similar thing uh for its 7:37 7 minutes, 37 seconds for another American public sector our uh company. A similar thing for a 7:44 7 minutes, 44 seconds financial services uh customer uh which is a global industry leader uh in in P 7:51 7 minutes, 51 seconds in kind of deployment of their now assist generative AI platform within the service now ecosystem. 7:58 7 minutes, 58 seconds uh and in addition to that we're also uh working we just have started an engagement with one of the largest uh 8:05 8 minutes, 5 seconds telecom providers in the US where where we are helping them architect 8:10 8 minutes, 10 seconds uh you know financial u hyper precision uh by deploying a high fidelity AI ops 8:17 8 minutes, 17 seconds intelligence layer again within their service now kind of ecosystem. So these are kind of some of the customers that have win. I've not covered everyone 8:26 8 minutes, 26 seconds every one of them but uh this will give you a general sense of the kind of uh wins and the kind of work that uh uh we 8:34 8 minutes, 34 seconds are getting at this point. Uh to give to go on the operational highlights uh so I'll cover a few here. So we just 8:42 8 minutes, 42 seconds basically uh enabled uh the algorithmic uh financial systems 8:50 8 minutes, 50 seconds for a premier global uh bank by automating their mission critical payment workflows uh across multiple countries across markets. 9:01 9 minutes, 1 second Uh similarly we have basically um uh we we have also achieved the highest 9:08 9 minutes, 8 seconds level of partnership. We have achieved the Microsoft solution partner designation across 9:15 9 minutes, 15 seconds uh three areas data and AI, digital and app innovation and infrastructure resour. Uh this kind of uh places us you 9:25 9 minutes, 25 seconds know amongst a very select group of companies within the Microsoft uh partner program and our relationship 9:32 9 minutes, 32 seconds with Microsoft is growing and and we continue to sort of strengthen it and work work jointly with them. 9:39 9 minutes, 39 seconds Uh we also for one of the one of the premier and largest uh uh creative agencies we basically work with them to 9:49 9 minutes, 49 seconds to to develop an AI orchestrated creative at scale ecosystem as they call it. This basically helps them uh and 9:59 9 minutes, 59 seconds this company operates around 140 companies. What this will help them is using AI eliminate a lot of manual production bottleneck bottlenecks that 10:07 10 minutes, 7 seconds you face and basically you know um and it'll it'll kind of move them move their you know creative workflows into an 10:16 10 minutes, 16 seconds autonomous brand governed kind of uh hyperpersonalized asset generation. Uh so this will help them really scale 10:23 10 minutes, 23 seconds their outreach to their customer and time to market. 10:28 10 minutes, 28 seconds Similarly, we have developed for a global communication provider Agentic AIdriven uh you know verification fab fabric and 10:36 10 minutes, 36 seconds this has been developed on our own proprietary type platform uh which kind of helps them to address uh board level 10:44 10 minutes, 44 seconds risks and also you know things like SIM swap frauds and account takeovers and things like that. We have also been 10:52 10 minutes, 52 seconds selected by a prominent uh UN agency uh to again design and deliver a generative AI integrated application uh supporting 11:01 11 minutes, 1 second their global humanitarian program. So these are all some of the uh key operational uh projects or operational highlights uh that we achieved during this quarter. 11:14 11 minutes, 14 seconds So that's all I have. Thank you. 11:18 11 minutes, 18 seconds Thank you. Uh Lot more detail is in our earnings presentation and we welcome any questions that you might have in the 11:26 11 minutes, 26 seconds Q&A. So please do join the queue. Mike, can we open it up for Q&A? 11:32 11 minutes, 32 seconds Sure. We will now begin the question answer session. 11:36 11 minutes, 36 seconds Anyone who wishes to ask a question may press star and one on the touchtone telephone. If you wish to remove yourself from the question key, you may press star and two. Participants are 11:45 11 minutes, 45 seconds requested to use handsets while asking a question. 11:49 11 minutes, 49 seconds Ladies and gentlemen, we'll wait for a moment while the question Q assembles. 12:11 12 minutes, 11 seconds We have the first question from the line of J Prakashar from Axel Research. Please go ahead. Hi Jash. 12:19 12 minutes, 19 seconds Hi. Hi. Uh congratulation on a stable set of performance last quarter. Uh I 12:26 12 minutes, 26 seconds wanted to understand uh that currently on the ongoing scenario around the world. If you look at u all the shares 12:34 12 minutes, 34 seconds of major ID companies for example uh service now company listed elsewhere which is one company that you have 12:43 12 minutes, 43 seconds recently acquired also functions on the similar domain that is down around 50% uh over last one year and there are 12:50 12 minutes, 50 seconds fears related to AI uh taking up a lot of uh services uh going forward uh how 12:58 12 minutes, 58 seconds do you see that and uh related to data center capex which is going to come up uh very soon. Is there any opportunity 13:06 13 minutes, 6 seconds for Kelton to probably add value or uh participate in that? 13:14 13 minutes, 14 seconds So thank you for the question Jas I'll answer the first question the second question rather where you talked about the data center part of it. Yes, 13:21 13 minutes, 21 seconds absolutely right. We have deep uh expertise when it comes to data center both from setting it up our data centers 13:28 13 minutes, 28 seconds as well as you know managing and maintaining that uh data centers. So we're actually partnered with a physical 13:35 13 minutes, 35 seconds setup guy uh to cater towards one of the largest uh uh uh data centers in the world. Uh we are still in a discussion 13:44 13 minutes, 44 seconds stage. We are not at a proposal stage yet. Uh we are responding to RFPs and we're going uh and presenting. So we 13:51 13 minutes, 51 seconds believe that you know we are in the front foot when it comes to uh in the data center space setting it up as well as maintaining and operating. So right now we are at the RFP stage like I said. 14:02 14 minutes, 2 seconds Now coming to your first question about uh the software companies taking a tank including the services company right 14:09 14 minutes, 9 seconds which they're calling the SAS acopics you know that you know we don't believe that you know it's just a hype that is going around there. We don't believe 14:18 14 minutes, 18 seconds that there's going to be a big impact on this. The impact is going to be more on per seat kind of revenue that you know 14:25 14 minutes, 25 seconds people operate. This is where the back office operations that happen uh for BO related activities you know that is where we believe that there's going to 14:33 14 minutes, 33 seconds be an impact. Uh while you know people are talking about you know cloud is going to replace all the SAS platforms. 14:40 14 minutes, 40 seconds Yeah, cloud might might replace you know for the small mom and pop kind of uh places where there is a uh there is a a 14:50 14 minutes, 50 seconds requirement for a SAS platform. Uh but when it comes to enterprises right enterprises will not bet big on uh on 14:57 14 minutes, 57 seconds you know homegrown or you know uh setting it up using uh uh using uh this uh the cloud uh cowork platform. Now I 15:06 15 minutes, 6 seconds want to ask Sini to answer this because he is uh is front and center on these things. So I'll let Sini give a little bit more color onto the same on this SAS 15:16 15 minutes, 16 seconds complex and what the impact is for Kelton or Kelton like companies. Serini can you jump in and answer this question please? 15:23 15 minutes, 23 seconds Sure Nan thank you very much. Uh to reiterate what Nan has been saying, uh the the SAS focal that happened with the 15:32 15 minutes, 32 seconds drop in shares share price values of all these SAS platforms was I mean you can already see right now that that things 15:40 15 minutes, 40 seconds are improving and things are going back up. It was just a market reaction to something that uh that Antropic Claude 15:47 15 minutes, 47 seconds released right recently. It really is nothing but uh about 11 or 12 uh widgets 15:53 15 minutes, 53 seconds or plugins which are open source and that seem to do a lot of uh a lot of stuff but in reality they are nothing 16:02 16 minutes, 2 seconds but uh some workflow automation that was built about by uh by actually uh a 16:09 16 minutes, 9 seconds logical step uh going through. Uh so yes I mean what what what is being seen 16:16 16 minutes, 16 seconds right now is that you know that the the progress that is being made on the AI front is real. The pace at which it is 16:24 16 minutes, 24 seconds improving and putting solutions out there or potential solutions is there but there's nothing that is impacted right now other than the fact that 16:33 16 minutes, 33 seconds customers are expecting more efficiencies in the workflow and so in the workforce. So basically what what it 16:41 16 minutes, 41 seconds says is that in in future scale is until now scale has been associated with headcom that will change right it will 16:50 16 minutes, 50 seconds it will be more about outcomes and Kelton has always been on the on on on selling outcomes rather than selling 16:57 16 minutes, 57 seconds available hours and so on. So the impact is is going to be minimal. Yes. But the rate at which improvements will happen 17:04 17 minutes, 4 seconds and what will come out in the market will will will increase. So that is the major major difference that we see right now. And yes, Service Now has also all 17:13 17 minutes, 13 seconds of these SAS platforms whether it be Service Now, Snowflake, Microsoft, all of them have in some way, shape or form 17:21 17 minutes, 21 seconds either internally started to build their agents and their AI components within their core. And in some cases, companies 17:29 17 minutes, 29 seconds like Service Now to reacting to this have also preempted this by acquiring uh AI companies. Right? So we see that the 17:39 17 minutes, 39 seconds SAS SAS companies will improve, will do what is necessary to to compete and will will adopt AI rather than fight. So we don't see a huge impact uh either way. 17:51 17 minutes, 51 seconds Yes, the way we operate will change, efficiencies will improve, but beyond that I think there was just a market 17:58 17 minutes, 58 seconds reaction. Uh okay just a follow up to the previous question uh that uh on a 18:05 18 minutes, 5 seconds quartertoquarter basis what type of productivity increase that you are seeing per on a per employee basis you know you mentioned about efficiency per 18:12 18 minutes, 12 seconds employees will go up so I believe that so let me answer that 18:20 18 minutes, 20 seconds let me complete my question please please go ahead yes yeah uh yeah so uh and are you also looking to make your team more leaner. 18:30 18 minutes, 30 seconds Uh I think a more lean team given the productivity increase will probably shareholder value. 18:39 18 minutes, 39 seconds Okay. So let me answer uh let me answer that. You know I guess we are two two part question. Let me answer the second part. First are we expecting a linear 18:47 18 minutes, 47 seconds team? Absolutely we are expecting a linear team. But you know there's a second school of thought where they're talking about the volumes are going to increase because of the efficiency. So 18:55 18 minutes, 55 seconds we could be you know uh keeping the same theme and increasing uh I'm just picking discussion sake right we have 300 customers today that could go to 400 500 19:04 19 minutes, 4 seconds customers or it could be some people are talking about an order of magnitude too right so we are just waiting and watching because what we are predicting 19:13 19 minutes, 13 seconds today with the rate of progress of AI you know what we going to be in a month from now is completely different so at 19:21 19 minutes, 21 seconds this point our prediction is that volumes will increase uh while efficiencies are increasing. I will let 19:28 19 minutes, 28 seconds Kanji take the post answer on question on this. what are they seeing per customer but you know again per per employee I'm sorry but it all depends 19:37 19 minutes, 37 seconds right we will answer that it depends because units in our uh in our company have different kinds of efficiencies that are 19:45 19 minutes, 45 seconds come in play kj you want to take that sorry you asking something else Jay no no no 19:52 19 minutes, 52 seconds okay kj can you answer that kj yes thank you niran yeah so basically uh 19:59 19 minutes, 59 seconds see we have various engagements ments uh types with customers. So wherever which is outcome wherever we have outcome based contracts 20:08 20 minutes, 8 seconds uh you know various uh steps of the development cycle obviously we have different uh uses of uh you know AI so 20:16 20 minutes, 16 seconds like automation test today QA test cases are pretty much written uh using our own uh Kai tool similarly you know all the 20:24 20 minutes, 24 seconds documentation again gets generated by Kai tool uh the stories and stuff like that that all happens with the Kai tool on the development side also we 20:33 20 minutes, 33 seconds basically use uh you know AI is uh rolled out to all developers we we use copilot and then again within that we 20:41 20 minutes, 41 seconds can use various models but anyway to so the one where we can very clearly measure it is this outcome based 20:48 20 minutes, 48 seconds projects where we are seeing depending on the technology uh uh kind of project is it a new one is it a old one that 20:55 20 minutes, 55 seconds you're upgrading uh to on new projects we're you seeing between 20% to 30% effic efficiency gains. Uh that's that's 21:04 21 minutes, 4 seconds something that we can clearly see. Now, if you already have a a huge code base, uh then obviously it depends on where 21:11 21 minutes, 11 seconds you're working and things like that. So that's been our experience about 20 to 30% uh general gains and this is being rolled out internally to every project. 21:21 21 minutes, 21 seconds I also made a mention in my first part of my comments where we said we are doing this translation uh or basically a legacy modernization where we are 21:29 21 minutes, 29 seconds converting a 4GL language to uh let's say a modern um Microsoft.NET architecture. Now this is a big deal. 21:37 21 minutes, 37 seconds It's 4 million lines of code. Uh obviously it is sold assuming certain you know already AI embedded into it. 21:44 21 minutes, 44 seconds But I think in the manual world the customer wouldn't even have that is something which possibly the customer wouldn't have taken up that project and 21:51 21 minutes, 51 seconds even if he did uh it would have been at least 3 to 4x of of that value. So that's the kind of new work that sort of 21:59 21 minutes, 59 seconds Niranjan alluded to right. Uh so so that's kind of our our our lived experience with this. 22:07 22 minutes, 7 seconds Okay. Thank you Jay. If there's any other questions we love to answer. 22:12 22 minutes, 12 seconds Thank you. Thank you. That's it. Thank you J. Okay, next question please. 22:17 22 minutes, 17 seconds Thank you. We have the next question from the line of Rohit, an individual investor. Please go ahead. Hi Roit. Hello. 22:25 22 minutes, 25 seconds Hey. Hi team. Uh I'm Rohit from Pune, a retail investor. Congratulations on acquiring Kumori Technologies and I have 22:33 22 minutes, 33 seconds one question. How does Kumari Technologies acquisition contribute to Kelton's growth? 22:41 22 minutes, 41 seconds Sure. So, Kelton uh bet on uh three four partnerships you know for the growth 22:49 22 minutes, 49 seconds that we want to get to right uh one one of them is service now the other is Microsoft and then we have a snowflake 22:56 22 minutes, 56 seconds uh SAP we already have bet on so now when it comes to Kumori technologies right Kelton had a certain partnership 23:04 23 minutes, 4 seconds level earlier before the acquisition of Kumori uh Kumori gave us some more expertise and a much deeper expertise 23:12 23 minutes, 12 seconds when it comes to delivering using services uh using you know service now. 23:18 23 minutes, 18 seconds Now we are at a different level of partnership with with uh with uh service now and that is going to give us you 23:25 23 minutes, 25 seconds know better access to you know more customers. What Kumori has given us is uh a readymade partnership uh with 23:34 23 minutes, 34 seconds deeper uh uh I guess expertise uh and now using Kelton's uh sales arm and the 23:42 23 minutes, 42 seconds global reach we will be able to get lot more uh customers as well as you know 23:50 23 minutes, 50 seconds interactions when we're going with the with the service now you know they are now saying okay guys you have so many certifications and you are a certain 23:59 23 minutes, 59 seconds level of partnership. Our relationship has changed and we expect uh revenue growth to be there. KJ you want to answer add anything on that? 24:14 24 minutes, 14 seconds K. 24:15 24 minutes, 15 seconds Yeah sure. So basically as Nanjin said right so there is one one is the strategic uh intent. So uh we've kind of 24:23 24 minutes, 23 seconds zeroed on certain partnerships and for us we had to figure out how do we accelerate this. So what Kumori gives us 24:30 24 minutes, 30 seconds as as he as Nanjan pointed out is service now they are already have service now expertise they have uh 24:38 24 minutes, 38 seconds they're working with the service now uh ecosystem already. So we get all of that expertise and uh you know we are 24:46 24 minutes, 46 seconds combining that with our salesforce. So it kind of uh helps now to do a global outreach uh of their capabilities and 24:53 24 minutes, 53 seconds there is a lot of traction uh that we've actually been seeing very specifically on service now and take that to market. 25:01 25 minutes, 1 second So kind of and also they've sort of uh now we can actually sell to all our customers all over the world right from 25:08 25 minutes, 8 seconds the US and also APAC region Europe everywhere. So that's kind of what it is and of course we'll get case studies and 25:16 25 minutes, 16 seconds uh expertise and technical capabilities right that's that's a given so it just helps us accelerate our journey 25:25 25 minutes, 25 seconds thank you Rohit any any other question Rohit okay so can you go to the next uh 25:33 25 minutes, 33 seconds question we have the next question from the line of Pratik Dia and individual investor please go ahead Am I audible? 25:45 25 minutes, 45 seconds Yes, you are. Go ahead. 25:46 25 minutes, 46 seconds Yeah. Okay. Thanks. So, yeah, I think um uh coming back to the efficiency part. 25:52 25 minutes, 52 seconds Um so, um I understand that there have been efficiency gains with um the AI part deployment. So how do you see that 26:02 26 minutes, 2 seconds um translating into um higher margins going ahead and what if you could quantify um that would be helpful over 26:10 26 minutes, 10 seconds two years or three year period okay so it's it's difficult pratik at this point to quantify uh how it's going 26:18 26 minutes, 18 seconds to reflect on the bottom line the reason I say that is you know what since kjit has already alluded to see most of our 26:25 26 minutes, 25 seconds business is TNM time material right uh if it is an outcome based like was talking about where we have the 26:32 26 minutes, 32 seconds flexibility to use the tools and we are not uh uh dependent on the customer driving the contracts. You know some of 26:41 26 minutes, 41 seconds our customers have told us in no uncertain terms that we cannot use AI. 26:46 26 minutes, 46 seconds So we have to do the old school way of doing programming. as more and more customers are willing to accept the efficiency 26:55 26 minutes, 55 seconds that is going that AI is going to bring in and the confidentiality is protected then we can start showing more uh 27:04 27 minutes, 4 seconds productiv increases but at the same time right the customer is already demanding saying that hey you are using AI tools 27:13 27 minutes, 13 seconds pass on some of that margin to me and we have in some in mo in most cases passed on that efficiency to the customer. 27:22 27 minutes, 22 seconds Okay. So we cannot at this point say okay hey because we are using AI you know our margins are going to increase 27:29 27 minutes, 29 seconds by x amount of points which is something that we cannot do at this point but we are seeing efficiencies and like I said 27:36 27 minutes, 36 seconds the volume we can do is increasing with the same amount of stuff and we are passing on the some of the margin uh 27:44 27 minutes, 44 seconds that we are gaining to the customer. So at this point you know I cannot quantify it. 27:51 27 minutes, 51 seconds Yeah if I can just add to that absolutely. Uh see what what is happening is the way it play out is uh 27:59 27 minutes, 59 seconds yes uh you know in fixed uh in in in outcome based projects which is a certain percentage. 28:06 28 minutes, 6 seconds uh you know we could we could keep the efficiency but sooner or later the customers uh customers will the customers will demand that uh you 28:15 28 minutes, 15 seconds know they will they will ask for aggressive pricing or like I mentioned the last one right the customer wouldn't have even gone ahead with that program 28:24 28 minutes, 24 seconds because the costs were prohibitive but AI is allowing it to happen so that will say increase in the in the business one other thing that will happen even on the 28:32 28 minutes, 32 seconds TNM side and this will happen for a small time is AI skills are basically premium. So this happens with every new 28:40 28 minutes, 40 seconds wave we have seen and typically lasts only about one year or so. So like back in the day uh there were the blockchain and NFT technologies. So we could 28:48 28 minutes, 48 seconds command slightly rates right. So we would have a $10 or a $15 upside on the rate. But then quickly, you know, the 28:56 28 minutes, 56 seconds Indian IT industry is smart. Everybody learns it and uh and soon sooner or later that that advantage again comes 29:04 29 minutes, 4 seconds back to wherever it was. So that will happen a little bit. So so the ones that are up ahead in the AI, what it'll 29:11 29 minutes, 11 seconds impact is in your willability. It will help you in your competitive advantage and for a certain time maybe you can command slightly uh premium rates but 29:20 29 minutes, 20 seconds then of course everybody will chase those premium rates. That's the only thing. Oh, thank you. 29:27 29 minutes, 27 seconds That's very And uh in terms of um the contracts that um where client is asking 29:34 29 minutes, 34 seconds you to not use AI, how are you seeing the pricing um happen currently and what 29:41 29 minutes, 41 seconds percentage of your new contracts are being signed without AI? 29:48 29 minutes, 48 seconds Sure. Uh can I get the first part of your question again? 29:51 29 minutes, 51 seconds Let me let me answer that. I think I understood this. So he's the question that was asked was you know how many of 29:58 29 minutes, 58 seconds our customers are saying we cannot use AI. Okay. So majority of our customers are telling us we cannot use AI. Uh 30:05 30 minutes, 5 seconds there Pratik uh the reason for that is they're still not uh they're still not ready for AI. They see some of our 30:13 30 minutes, 13 seconds customers when you do a sales pitch also know specifically this is happening in US. They're saying hey if you're going to talk about AI please don't come to me. 30:21 30 minutes, 21 seconds Okay. because they are not ready to adopt AI into their uh into their their enterprises right and yes you know they 30:29 30 minutes, 29 seconds will change if they the market will force them to change the competitors will force them to change this is thing 30:37 30 minutes, 37 seconds you know specifically I think you know with what has happened with the stock price crash everywhere people are seeing 30:43 30 minutes, 43 seconds hey AI is getting adopted it's in uh within many many companies so they will have to do 30:52 30 minutes, 52 seconds Okay. So they don't have a choice but at this point majority of our customers because like I said most of our customers are T and M. So it is time and 31:01 31 minutes, 1 second material. When it comes to time and material they are dictating what is it that we can do or cannot do. In an outcome based we take on what they call 31:10 31 minutes, 10 seconds the fixed price contracts. Then it's based on outcome. What we deliver how much efficiency we deliver how soon we 31:17 31 minutes, 17 seconds deliver. So those are the things that are measured was this what we have used to get there right in that scenario you 31:26 31 minutes, 26 seconds know we are getting these efficiencies by using our own internal Kai tool or you know other 31:33 31 minutes, 33 seconds other cost product or open-source uh AI tools that are available in the market. 31:39 31 minutes, 39 seconds Okay, got it. So can you um can you elaborate on the pricing part for nonI contracts? How are you seeing the trends that? 31:51 31 minutes, 51 seconds No, it's just been the same. There's no change on that, right? That is not changing on the nonAI contract. It is 31:58 31 minutes, 58 seconds per per uh per let's say uh what do you call the billet or per uh engineer you know based on the seniorities that the 32:06 32 minutes, 6 seconds customer asks in the TNM contracts they say you know okay I need a 10 year experience you know Java full full stack 32:13 32 minutes, 13 seconds person and we provide that person Or they say you know hey for this project you know give me what is your 32:21 32 minutes, 21 seconds estimate who are all the people that are going to be it's a named resource there and they will drive the outcomes not we 32:29 32 minutes, 29 seconds driving the outcomes they being the customers driving the outcomes got it okay that's it from my thank you 32:38 32 minutes, 38 seconds thank you Mike any other questions thank you uh not currently sir I'll just announce for questions once Participants 32:46 32 minutes, 46 seconds who wish to ask a question may press star and one on your Touchstone telephone. 32:56 32 minutes, 56 seconds It appears we have no further questions. 32:58 32 minutes, 58 seconds I would now like to hand the conference over to Mr. Nanjen for closing comments. 33:03 33 minutes, 3 seconds Okay. Uh thank you everyone for joining this earnings call. Uh I was very excited to talk about our capabilities when it comes to this AI. Uh looking 33:12 33 minutes, 12 seconds forward to more interactions. You know if you come over to Hyderabad and or Guram please look us up. We would be happy to show and tell what all we have 33:20 33 minutes, 20 seconds been doing. Uh but please schedule that with uh uh with the team ahead so that you know our availability and the time is locked. Uh again thank you. Looking forward to talking to you soon. 33:33 33 minutes, 33 seconds Thank you on behalf of Kelton Tech Solution Limited. That concludes this conference. Thank you for joining us and you may now disconnect your lines.