Fractal Analytics Ltd — Q3 FY26

Fractal Analytics Ltd Q3 FY2025-26 Earnings Conference Call https://www.youtube.com/watch?v=-7HZHidRisI Published: 2 months ago

0:00 Ladies and gentlemen, a very good morning. My name is Enba and I'll be moderating today's session. Welcome to 0:07 7 seconds Fractal's Q3 FI26 earnings conference call. All participants will remain in the listenonly mode and there will be an 0:14 14 seconds opportunity for you to ask question after management's remarks. Please note that this call is being recorded. I will 0:21 21 seconds hand over the call to Swana Zoshi from Fractal's investor relations team. Thank you and over to you Swatlana. Thank you, 0:29 29 seconds Enba. Good morning, everyone, and thank you for joining us today for Fractal's first earnings call since our public listing last month. We'll be discussing 0:37 37 seconds our performance for the third quarter and 9 months ended December 31st, 2025. 0:43 43 seconds Our results, shareholder letter, investor presentation and fact sheet have been published on the exchanges and are available on our investor relations 0:51 51 seconds website. Joining me on the call today are Shriant Wamakani, co-founder and group CEO, Pranay Agarwal, co-founder 0:59 59 seconds and CEO, Ashwad Bhut, Chief Financial Officer, and Satish Raman, Chief Strategy Officer. Before we begin, 1:07 1 minute, 7 seconds please note that certain statements made during this call may be forward-looking in nature. These statements are based on our current expectations and are subject 1:16 1 minute, 16 seconds to risks and uncertainties that could cause actual results to differ materially. Such statements or comments are not guarantees of future performance 1:25 1 minute, 25 seconds and Fractal undertakes no obligation to update them. Please refer to the cautionary statements in our investor presentation and regulatory filings. We 1:33 1 minute, 33 seconds will start with a business update from Shriant followed by a review of the financial performance by Ashwat post which we'll open the call for questions. 1:42 1 minute, 42 seconds With that let me hand over the call to Shriant. 1:46 1 minute, 46 seconds Thank you Satlana. Hi everyone and welcome to our first earnings call. 1:51 1 minute, 51 seconds Thank you for extending your trust to Fractal through our IPO process. We are honored and grateful. It has taken us 26 1:59 1 minute, 59 seconds years of powering decisions with AI inside enterprises to reach this milestone. And yet, it marks a deeper 2:06 2 minutes, 6 seconds commitment to earning the trust of public shareholders, to serving our clients with even greater impact, to shaping the future of intelligence, and 2:14 2 minutes, 14 seconds to building an institution that will endure for the next 100 years. 2:19 2 minutes, 19 seconds Let me me start with a quick introduction to Fractal. Fractal's vision is to power every human decision in the enterprise. We are a pure play AI 2:28 2 minutes, 28 seconds company that provides large global enterprises with AI solutions. 2:33 2 minutes, 33 seconds Large organizations make thousands of decisions every day across pricing, supply chains, inventory, logistics, 2:41 2 minutes, 41 seconds product strategy, and customer experience. Most of these decisions happen in a complex environment where 2:48 2 minutes, 48 seconds data is fragmented, processor processes are manual, and the cost of error is high. Fractal builds AI that connects 2:57 2 minutes, 57 seconds directly to enterprise data and workflows, helping companies make better decisions through automation and augmentation. 3:05 3 minutes, 5 seconds Take revenue growth management as an example. Fractal helps companies understand demand, optimize pricing and 3:13 3 minutes, 13 seconds promotions, and grow their categories using AI. 3:17 3 minutes, 17 seconds These are decisions that happen daily across hundreds of SKs in markets that move constantly. Getting them right is worth billions of dollars. 3:28 3 minutes, 28 seconds Next, I'd like to highlight some of the impactful work we are doing with PepsiCo, one of our key clients. 3:35 3 minutes, 35 seconds We're collaborating with PepsiCo to bring AI into manufacturing, specifically focusing on smart packaging. 3:42 3 minutes, 42 seconds This system addresses the challenge of manually adjusting over 300 parameters on a manufacturing line, which is extremely challenging for a human operator to achieve optimized output. 3:53 3 minutes, 53 seconds The AI selfoptimizes and adjusts the packs per minute automatically, contributing to better quality of product and continuous optimization. 4:03 4 minutes, 3 seconds This initiative has delivered significant improvements in packaging efficiency leading to increased throughput, reduced waste and optimized costs. 4:14 4 minutes, 14 seconds Our ability to solve our clients most important problems originates from our consistent investments of 6 to 8% of 4:21 4 minutes, 21 seconds revenue in R&D. Our AI research investment has helped us build foundation models and B2C AI products such as one fathom R114B. 4:34 4 minutes, 34 seconds It's a large reasoning foundation model that we have open sourced on hugging face. Second where they are.ai. It's a 4:41 4 minutes, 41 seconds free healthcare companion powered by our own medical multimodel reasoning system. 4:47 4 minutes, 47 seconds And three is PI Evolve, a multi- aent digital organization to help solve machine learning problems at scale. 4:56 4 minutes, 56 seconds We're also making significant R&D investments in building and scaling the Cogentic platform, Fractal's Agentic AI 5:03 5 minutes, 3 seconds platform to help companies re-imagine their enterprise workflows with AI. 5:10 5 minutes, 10 seconds We serve a specific set of large enterprises that we call must-win clients. They meet one of these three 5:17 5 minutes, 17 seconds criteria. They're either over 10 billion in annual revenue or over 20 billion in market capitalization or serve more than 30 million end customers. 5:29 5 minutes, 29 seconds As of December 31st, 2025, we serve 127 MWC's. 5:35 5 minutes, 35 seconds Our strategic intent is to generate at least $1 billion of impact for each of our clients. 5:42 5 minutes, 42 seconds Over the years, we have steadily grown, achieving significant milestones and establishing ourselves as a leader in the enterprise AI space. We are uniquely 5:52 5 minutes, 52 seconds positioned to grow alongside the expanding AI industry. 5:56 5 minutes, 56 seconds Under the leadership of PR and our executive team, we are hoping to build the company for the next 100 years. 6:02 6 minutes, 2 seconds That said, I would now like to spend some time on our December quarter performance. 6:07 6 minutes, 7 seconds We delivered a fantastic quarter, improving on nearly every metric. 6:12 6 minutes, 12 seconds Revenue for the quarter was 8,544 million, representing 21% year-over-year 6:19 6 minutes, 19 seconds growth. We saw exceptionally strong demand from life science and healthcare segment, which delivered a revenue growth of 78% year-over-year for the 6:27 6 minutes, 27 seconds quarter. Our banking and financial services segment grew 26% year-over-year. Our largest vertical, 6:35 6 minutes, 35 seconds the CPG and retail segment, which contributes 36% of the revenue, had a relatively modest 14% year-over-year 6:42 6 minutes, 42 seconds growth in December, affected mainly by tariff and macroeconomic uncertainties. 6:48 6 minutes, 48 seconds A telecom, media, and technology segment had a degree due to two client specific issues. 6:58 6 minutes, 58 seconds Geography wise, we continue to see robust demand for our services in all markets. Our America business grew 26% year-over-year and our Europe business also grew by 26% year-over-year. 7:10 7 minutes, 10 seconds The client specific issue, one of the client specific issues I spoke about led to a year-over-year decline of 6% in APAC. 7:20 7 minutes, 20 seconds Our strong performance is a testament to the depth of our client relationships and the trust they place in us to transform every aspect of their business 7:28 7 minutes, 28 seconds with AI. This is evident from our consistently high net promoter score and the incremental business our clients 7:35 7 minutes, 35 seconds keep rewarding us with. Our NPS was 77 in the December quarter. Our net revenue 7:42 7 minutes, 42 seconds retention or NRR was 114% in Q3 and 115% for the 9-month period. Clearly 7:49 7 minutes, 49 seconds demonstrating how our clients are expanding their engagements with us on the back of impactful outcomes we continue to deliver to them. 7:58 7 minutes, 58 seconds Q Q3 2026 revenue growth of 21% was driven primarily by 14% existing client expansion and strong new client 8:06 8 minutes, 6 seconds additions contributing to 8 percentage points on revenue growth this quarter moving on to profitability 8:15 8 minutes, 15 seconds Ashwat will get into more details but I'd like to highlight just two points firstly our gross margin in Q3 was 47%. 8:24 8 minutes, 24 seconds As we accelerate revenue growth, we want to continue expanding our gross margins which are already bestin-class. 8:31 8 minutes, 31 seconds Secondly, we cross the INR 1 billion mark in quarterly profit after tax. 8:38 8 minutes, 38 seconds I'd now like to walk you through some business highlights. 8:42 8 minutes, 42 seconds Fractal won the Microsoft partner of the year 2025 award in the retail and consumer goods category. 8:48 8 minutes, 48 seconds This award recognizes partners that have delivered significant impact with AI on Microsoft cloud and AI stack over the past year. 8:58 8 minutes, 58 seconds We're excited to announce that we have secured preferred supplier status with two of the magnificent seven clients. 9:06 9 minutes, 6 seconds And lastly on the R&D front, let me share some updates. 9:10 9 minutes, 10 seconds We launched Vya 2.0 at the India AI impact summit. VIA is our verticalized foundation model for healthcare under 9:19 9 minutes, 19 seconds the India AI mission aimed at enabling population scale transformation. 9:24 9 minutes, 24 seconds VIA 2.0 is a world's first model to achieve a 50 plus score on the OpenAI health bench hard a high bar a real 9:34 9 minutes, 34 seconds world benchmark healthcare is now our fastest growing vertical with 78% quarteronquarter 9:40 9 minutes, 40 seconds growth so year-over-year growth and we extending via's capabilities across healthcare and life sciences and pharma 9:47 9 minutes, 47 seconds clients we also launched PI evolve an agentic engine for autonomous machine learning 9:56 9 minutes, 56 seconds and scientific discovery. PI Evolve ranks among the world's top performing agents on OpenAI's MLE bench, becoming 10:05 10 minutes, 5 seconds the first evaluated agent to cross 16% score. PI Evolve will be available to fractalites and clients very soon, 10:13 10 minutes, 13 seconds helping us accelerate machine learning solutions for our clients. With this I conclude my remarks and hand it over to Ashwad for providing greater color into 10:22 10 minutes, 22 seconds financials for FI20 FI26 third quarter and 9 months for FI26. 10:30 10 minutes, 30 seconds Thank you Shriant and good morning everyone. We delivered a strong quarter of profitable growth. 10:37 10 minutes, 37 seconds Our current quarter revenue from operations grew by 21% year-over-year and 7% quarter over quarter to 854 crores. 10:46 10 minutes, 46 seconds On a constant currency basis, growth was 14% year-over-year and 5% quarter over quarter. For the first 9 months of 10:55 10 minutes, 55 seconds fiscal 26, growth was 20% year-over-year and 15% on a constant currency basis. 11:02 11 minutes, 2 seconds This growth was entirely organic. Three components drove our growth. 11:08 11 minutes, 8 seconds First, growth from existing clients as reflected in net revenue retention. 11:14 11 minutes, 14 seconds second growth from new clients and third client charge. All three components are calculated on a trailing 12-month basis. 11:23 11 minutes, 23 seconds Net revenue retention or NRR reflects reflects the growth with existing clients similar to same store sales 11:30 11 minutes, 30 seconds growth in retail industry. In a revenue growth of 21% for Q326, 11:38 11 minutes, 38 seconds 14 points was from existing clients as reflected in NR of 114%. 11:43 11 minutes, 43 seconds Eight points of growth came from new clients added in the last 12 months and we had half a point of churn. We 11:52 11 minutes, 52 seconds experienced particularly strong growth by way of new client additions primarily in our healthcare and life sciences and 11:59 11 minutes, 59 seconds consumer package goods or FMCG industry verticles. 12:05 12 minutes, 5 seconds For the first 9 months of this fiscal, NRR was at 115% indicating 15 points of growth from existing clients. New 12:14 12 minutes, 14 seconds clients contributed to six points of growth and we had 1% churn. 12:20 12 minutes, 20 seconds Adding 10, 20, 30 clients, also referred to as Muswin clients, is a key growth strategy for Fractal. As of December 12:29 12 minutes, 29 seconds 2025, we are working on 127 MustFin clients, up from 113 in March 2025. 12:37 12 minutes, 37 seconds The revenue share from these clients has increased to 83% in Q3 fiscal 26 compared to 81% for fiscal 25. 12:48 12 minutes, 48 seconds We have scaled our greater than $1 million clients from 53 in March of 2025 12:54 12 minutes, 54 seconds to 58 clients as of Q3 fiscal 26 as measured by revenues on a trailing 12-month basis. The clients contributing 13:03 13 minutes, 3 seconds more than 20 million in revenues has increased from five to six during the same comparable periods. 13:11 13 minutes, 11 seconds Consistently delivering value to our clients and scaling our business with them remains our northstar. 13:18 13 minutes, 18 seconds Diving into revenue growth first by industry segments. 13:22 13 minutes, 22 seconds Growth was primarily driven by 78% year-over-year increase in healthcare and life sciences industry 13:29 13 minutes, 29 seconds followed by 26% growth in banking and financial services industry. Growth in healthcare and life sciences industry 13:36 13 minutes, 36 seconds was a result of strategic investments for building capabilities to serve our clients. 13:42 13 minutes, 42 seconds Decline in tech and media telecom industry was primarily driven by a telecom client in Australia and a technology client in the United States. 13:52 13 minutes, 52 seconds Our CPJ and retail clients faced tariff related headwinds in the first quarter of this fiscal year which impacted their 13:59 13 minutes, 59 seconds spending. Excluding CPJ and retail, our growth would have been 25% for the year overyear. 14:07 14 minutes, 7 seconds Secondly, we measure our revenue by geography based on client billing location. Client's billing location. In 14:14 14 minutes, 14 seconds Q3 of fiscal 26, America's and Europe both grew by 26% year-over-year, whereas 14:21 14 minutes, 21 seconds APAC declined by 6% owing to the same telecom client mentioned earlier. For the first 9 months of fiscal 26, Europe 14:29 14 minutes, 29 seconds has grown by 37% as we scaled our business with existing clients. To conclude, a revenue per 14:38 14 minutes, 38 seconds billable headcount increased to $85,000, representing an increase of 6% in rupee 14:44 14 minutes, 44 seconds terms and 2% in dollar terms as measured on a trailing 12-month basis. 14:51 14 minutes, 51 seconds Now, moving over to profitability, I will start with gross margins. 14:56 14 minutes, 56 seconds We define gross margin as revenue from operations less direct cost, which includes both employee benefit expenses 15:03 15 minutes, 3 seconds and other direct expenses. Our Q326 gross margin expanded by 17 bips year-over-year to 47.2%. 15:13 15 minutes, 13 seconds This comprises of 115 bips benefit arising from change in mix of engagement type moving towards outputbased 15:20 15 minutes, 20 seconds contracts, price increases and productivity improvements. The benefit was partially offset by the net impact 15:28 15 minutes, 28 seconds of annual merit increases and weaker rupee. 15:33 15 minutes, 33 seconds Gross margin for the first 9 months of fiscal 26 expanded by 110 bips year-over-year to 46.3%. 15:41 15 minutes, 41 seconds Increase in mix of outputbased contracts along with strong growth in fractal alpha contributed to this gross margin increase. Now moving to adjusted IIDA. 15:52 15 minutes, 52 seconds In Q326, adjusted EIDA was at 17.8% representing an increase of 43 bips 15:59 15 minutes, 59 seconds year-over-year. This was driven by SGNA coming down by 30 bips to 25.3% 16:06 16 minutes, 6 seconds of revenue along with gross margin expansion. 16:10 16 minutes, 10 seconds Adjusted Eida for the first 9 months of fiscal 26 was at 16% versus 16.4% in the 16:17 16 minutes, 17 seconds same period of last year. While our gross margin expanded by 110 bips, growth in investments in relationship 16:24 16 minutes, 24 seconds management for key clients and opening of new offices led to 180 bips uptake in SGNA as percentage of revenue versus last year. 16:34 16 minutes, 34 seconds Excluding the impact of R&D spend which we expense in our P&L, our adjusted EIDA would have been 22% for Q3 26 and 20% 16:44 16 minutes, 44 seconds for the first 9 months of fiscal year 26. Our current margin takes into account necessary investments to benefit 16:52 16 minutes, 52 seconds from the massive AI opportunities which lie ahead of us. 16:57 16 minutes, 57 seconds Moving to Fractal Alpha, I would like to highlight our journey of rapid growth and profitability improvement. Fractal 17:04 17 minutes, 4 seconds Alpha has grown by 51% year-over-year in the first 9 months of fiscal 26 with Asper growing at 43% and Analytics Vidya at 69%. 17:15 17 minutes, 15 seconds Gross margin for Fractal Alpha has expanded by 276 basis points year-over-year. The loss in the segment 17:23 17 minutes, 23 seconds for the same period has come down by 51% while investments into R&D and sales and marketing have continued. The losses in 17:32 17 minutes, 32 seconds fractal alpha have been coming down since fiscal 23. Our segment loss was at 54 crores in fiscal 23 which reduced to 17:41 17 minutes, 41 seconds 44 crores in fiscal 24. further reducing to 26 crores in fiscal 25 and it currently stands at 10 crores for the first 9 months of fiscal 26. 17:53 17 minutes, 53 seconds Now I would like to move on to profit after tax. Profit after tax for Q326 was at 100 crores or 11.7%. 18:04 18 minutes, 4 seconds 92 crores or 13% for the corresponding period last year. profit after tax of 100 crores in Q326 increased by 10% 18:13 18 minutes, 13 seconds year-over-year despite increased losses from associate company and lower other income on account of forex losses. In 18:21 18 minutes, 21 seconds Q326, we increased a we created a deferred tax asset of 50 crores to reflect the tax benefit from carry forward losses in the USA. 18:31 18 minutes, 31 seconds QR.AI AI is an associate company where Fractal owns 31.5%. 18:36 18 minutes, 36 seconds And as per INA as we account for the share of our profit or losses in our consolidated P&L proportionately. 18:45 18 minutes, 45 seconds Cure.ai has been facing headwind with cuts to US aid which has led to higher losses versus previous year. Our share 18:53 18 minutes, 53 seconds of losses from cure.ai stood at 19 crores or 2.2% 2% of revenue versus for 19:00 19 minutes Q326 versus 3 crores or 4% of revenue for the same period last year. In 19:07 19 minutes, 7 seconds addition to this, because of higher forex losses, other income went down from 24 crores or 3.4% of the revenue in 19:15 19 minutes, 15 seconds Q325 to 2 crores or 2% of the revenue in Q326. 19:21 19 minutes, 21 seconds Excluding the increased loss from cure.ai AI and reduction in other income. Our profit after tax would be 19:29 19 minutes, 29 seconds 138 crores versus 92 crores for the same period last year. In Q326, ESO of charges including options linked cash 19:37 19 minutes, 37 seconds bonus and retention bonus declined to 2.8% of the revenue versus 4.9% of the revenue for the same period last year. 19:47 19 minutes, 47 seconds ESOP charges including options linked cash bonus has come down from 9.9% of 19:53 19 minutes, 53 seconds revenue in fiscal 23 to 2.3% of revenue in the first 9 months of current fiscal. 20:00 20 minutes Now moving over to cash we generated 129 crores of cash from operations which was 16% higher than the same period last 20:08 20 minutes, 8 seconds year. This was primarily driven by 14 days reduction in days of sales outstanding from 92 days in the last fiscal to 78 days in the current fiscal. 20:18 20 minutes, 18 seconds We include build and unbuild trade receivables to calculate DSO. For the first 9 months of fiscal 26, cash from 20:27 20 minutes, 27 seconds operations came in at 108 crores versus 120 crores at the same time last year. 20:34 20 minutes, 34 seconds IPO related expenses to be recovered and GST refund timing impacted the cash from operations adversely by 57 crores. 20:43 20 minutes, 43 seconds Adjusting for this cash from operations for the 9 months would be 165 crores which represents 38% year-on-year 20:51 20 minutes, 51 seconds growth. As of December 31st 2025, we had cash and cash equivalents of 1816 20:58 20 minutes, 58 seconds crores. In summary, overall we had a great quarter where we delivered 21% 21:04 21 minutes, 4 seconds revenue growth, 47% gross margin, 18% adjusted eida and 100 crores of profit 21:11 21 minutes, 11 seconds after tax. With that, now we can move to your questions. Back to you, moderator. 21:18 21 minutes, 18 seconds Thank you, ladies and gentlemen. We will now move to the Q&A segment. 21:24 21 minutes, 24 seconds Participants are requested to please use the raise hand icon located at the bottom toolbar on your screen. When called upon, you will receive a prompt to unmute. 21:34 21 minutes, 34 seconds We will wait for a moment while the question ceue assembles. 21:56 21 minutes, 56 seconds Ladies and gentlemen, if you wish to ask a question, you may click on the raise hand icon. 22:34 22 minutes, 34 seconds We'll take the first question from Manish Adukia of Goldman Sachs. Please go ahead. 22:40 22 minutes, 40 seconds Hi, good morning. Thank you for taking my questions and congratulations to the entire team for the listing. Um, few questions from me. Firstly, uh since 22:47 22 minutes, 47 seconds this is your first uh earnings call, um would you be able to give any kind of uh indicative 22:54 22 minutes, 54 seconds um if not specific some kind of range of guidance in terms of what your aspirations may be from a revenue growth 23:02 23 minutes, 2 seconds perspective over the next maybe one to two years and where do you see adjusted bit of margins to for the factor AI 23:10 23 minutes, 10 seconds segment to maybe get to in the next couple of years and what the building blocks for that may look like? And that's my first question please. 23:20 23 minutes, 20 seconds Thank you Manish. Um we expect we have seen a significant AI related expansion as enterprise 23:29 23 minutes, 29 seconds adoption of AI takes off. Today enterprise adoption of AI is somewhat moderate because accuracy of the AI systems still don't consistently match 23:37 23 minutes, 37 seconds and exceed human performance in every place. Now this is changing every day and as more and more AI uh solutions 23:46 23 minutes, 46 seconds become feasible and and inexpensive in the context of large enterprises it become adoption takes off. So we do 23:54 23 minutes, 54 seconds expect that our revenues will continue to accelerate uh at a at a faster pace. 23:59 23 minutes, 59 seconds Historically uh we have grown at 10 30% year-over-year for the last 10 years. uh and even in 24:07 24 minutes, 7 seconds the last five years our growth rate CGR has been 29%. 24:11 24 minutes, 11 seconds So uh we see an an amazing opportunity in terms of continuing the kind of revenue growth that we have seen historically. Um that is number one and 24:20 24 minutes, 20 seconds in terms of margins as a public company we want to uh we we are clear that the expectations from the investors is to uh 24:27 24 minutes, 27 seconds expand our net income and our EBA margins and we are as we continue our revenue growth uh accelerate our revenue 24:35 24 minutes, 35 seconds growth. We want to make sure that our gross margins which we see as one of the most important indicators of the quality of the business we want that to expand 24:43 24 minutes, 43 seconds and then that translating into both EBITA expansion as well as uh PAT percentage expansion as well. That's 24:50 24 minutes, 50 seconds what we expect uh especially also because some of our ESOP charges and others that were earlier part of our P&L 24:57 24 minutes, 57 seconds as a percentage of revenue we expect them to decline. So overall we expect EITA margins and PAT margins to expand while uh gross margins also will expand. 25:07 25 minutes, 7 seconds So this is the uh this is the kind of um objective that we are working with accelerate revenue growth while expanding gross margin and continue to expand I beta as well as profit margins. 25:19 25 minutes, 19 seconds Thank you for that response. And my other maybe related question to that was your gross margin obviously like you mentioned best-in-class at around 47 odd 25:26 25 minutes, 26 seconds percent. Uh which is significantly higher than at least the services companies that are you know listed in 25:33 25 minutes, 33 seconds India across market cap. I mean but when we look at let's say your adjusted margin today which is maybe lower than 25:41 25 minutes, 41 seconds some of those companies is there any reason why over a longer period of time given your gross margin profile is so strong you're moving more towards output 25:50 25 minutes, 50 seconds based contracts plus there's a significant uh focus on your product business that your EBIT or EIDA margin 25:58 25 minutes, 58 seconds also should not be higher than you know a typical services company uh given your gross margin quality is significantly 26:06 26 minutes, 6 seconds higher than those companies. Would love to know hear your thoughts on that. 26:10 26 minutes, 10 seconds No, thank you. I I'll add something and then maybe I'll request Ashwat to continue to add to my answer. Number one is that yes, we expect our gross margins 26:18 26 minutes, 18 seconds are our industry best but we want to continue expanding our gross margins. 26:22 26 minutes, 22 seconds Number one. Number two is from gross margins to EBITA margins. We have SGNA as well as our R&D expenses. So like 26:30 26 minutes, 30 seconds Ashwat also pointed out we take roughly 4% of revenue 4.1% of revenue into our expenses today which drops their overall 26:39 26 minutes, 39 seconds ITA margins by four points. So when you're comparing us with other firms this four points uh have to be adjusted for because they don't have most of them 26:47 26 minutes, 47 seconds don't have any AI R&D today. Um that's that's number one. Second is that our SGNA we expect to continue to make 26:54 26 minutes, 54 seconds improvements on SGNA as a fraction of sales uh because we we see uh productivity improvements in sales as 27:02 27 minutes, 2 seconds well as G&A. We have a whole host of AIEL programs within Fractal to improve sales productivity. We launched a tool 27:09 27 minutes, 9 seconds internally called pitch dark which helps our salespeople sell uh better and prepare for meetings much more 27:17 27 minutes, 17 seconds effectively, much faster. it it drops the time from days to minutes and that we expect will help us in improving our 27:24 27 minutes, 24 seconds sales productivity overall. Secondly on G&A for example in hiring one of our big cost is the cost of hiring and the time 27:31 27 minutes, 31 seconds it takes to hire. We have implemented a solution called eeky guy within fractal which is a way in which we can 27:39 27 minutes, 39 seconds completely build the hiring process, recruitment process and matching process AIdriven. So right from uh a recruiter 27:47 27 minutes, 47 seconds agent who can create the job description to a candidate agent who can have this conversation with a candidate to a 360deree assessment which is completely 27:56 27 minutes, 56 seconds AIdriven to AI matching engine. We have automated the process of hiring within fractal which makes the entire SGNA come 28:04 28 minutes, 4 seconds down as a fraction of sales. We expect SGNA improvements as well as improvements uh on overall gross margin 28:12 28 minutes, 12 seconds leading to higher adjusted EITA margins at fractal. Uh Ashwat you want to add? 28:18 28 minutes, 18 seconds Yeah, just to reiterate some of the points as said Manish the key drivers will continue to be how we improve our 28:26 28 minutes, 26 seconds gross margins. I talked about the mix change more towards output based which come with a higher profitability uh 28:33 28 minutes, 33 seconds indicators and then also SGNA we have already reduced our SGNA as we laid out in the presentation also by almost seven 28:40 28 minutes, 40 seconds points and that continues to be the case like we have operating leverage as the revenue scales we will be able to uh 28:48 28 minutes, 48 seconds bring our SGNA down and also SGNA will also one just the pure operating leverage but also some of the internal AI tools that Shrihan talked about be it 28:57 28 minutes, 57 seconds in our hiring and recruiting side of uh things or even in something like sales. 29:03 29 minutes, 3 seconds So across both sales and marketing and uh GNA we will be able to bring our uh cost down as a percentage of revenue 29:10 29 minutes, 10 seconds while continuing to invest in R&D. So the main answer like why at times our adjusted eida looks little different 29:17 29 minutes, 17 seconds obviously there is 4.1% of R&D expense in that and second we have shown operating leverage or ability to 29:25 29 minutes, 25 seconds increase uh or reduce the SGNA as a percentage of revenue over the last 3 years uh there's no reason why we can't 29:32 29 minutes, 32 seconds continue to do that and uh our adjusted eida 3 years ago used to be 7% now it is uh last quarter was 18% so we expect that to keep uh increasing as we scale. 29:43 29 minutes, 43 seconds Thank you for clarifying that. Uh my other question was on these two client issues that you've called out in your TMT vertical, one in Australia and one 29:51 29 minutes, 51 seconds on one in the US. Are you able to provide us any more color on what kind of issues these might be and are these 30:00 30 minutes business as usual in your business or was there any kind of let's say surprise or one off here? Any color would be helpful there. 30:08 30 minutes, 8 seconds See um it's our business is dependent on client success and sometimes if a clients are having a challenge in their 30:16 30 minutes, 16 seconds own business that will reflect on us as well. So one of the clients that uh we spoke about here has been going through a restructuring inside their own 30:24 30 minutes, 24 seconds organization um and therefore that has impact us. It is not a typical uh fractal client in terms of scale. Uh and 30:33 30 minutes, 33 seconds therefore that has also been the reason for volatility on that client relationship. Typically fractal works with the 10 2030 which is 10 billion 30:42 30 minutes, 42 seconds revenue, 20 billion market cap and 30 million customers. So these are very large companies which do not usually see any volatility in their business. 30:50 30 minutes, 50 seconds They're very stable and uh very profitable and so on. This client has been an exception to that. uh that's 30:57 30 minutes, 57 seconds that in that sense and then the one in Apac I think it's been a case of uh decreasing their business with us these two happen from time to time I would not 31:06 31 minutes, 6 seconds say this is not business as usual this can happen but overall this is reflective in the overall churn number which is roughly 1% of revenue for 31:14 31 minutes, 14 seconds fractal uh in any given year so that is how we have to process that part of the uh of the exception 31:22 31 minutes, 22 seconds Mr. Lukia, may we request you to return to the queue? Thank you. 31:25 31 minutes, 25 seconds Sure, we'll do. Thanks a lot. Thanks a lot. 31:28 31 minutes, 28 seconds Thank you. We'll move to our next question. That's from Goravia of Morgan Stanley. 31:37 31 minutes, 37 seconds Uh Mr. Reteria, you may ask your question now. Am I audible? Just want to confirm. 31:46 31 minutes, 46 seconds Yes. Yes, sir. Please go ahead. 31:50 31 minutes, 50 seconds Okay. Thank you. Okay, congratulations Shriant and team for the listening. Uh I have couple of questions. My first 31:57 31 minutes, 57 seconds question is in face of changing technology landscape think uh the perception of uh fractal has changed in 32:07 32 minutes, 7 seconds front of clients. I know that you spoke about metrics like NPS and NRR which gives us some comfort. just trying to understand that uh the clients may be 32:16 32 minutes, 16 seconds also trying to uh have a list of strategic partners for providing the AI related services which may not necessarily coincide with their 32:24 32 minutes, 24 seconds incumbent uh vendors. So how's fractal perception changed in last one or two years uh in wake of the technology 32:32 32 minutes, 32 seconds landscape changing? The second question is on the engagement models. You did talk about the increase in outputbased 32:40 32 minutes, 40 seconds models. uh what are these various outcome based models that you can underwrite because of your capabilities which may not be possible for other 32:47 32 minutes, 47 seconds vendors to underwrite that and the last you talked about the R&D investments uh we are currently probably at 4% plus where do you think in the medium-term 32:56 32 minutes, 56 seconds these R&D investment should uh stabilize at and you know which on our but at the same time also gives 33:03 33 minutes, 3 seconds us some operating leverage thank you yeah So first on the perception of 33:12 33 minutes, 12 seconds clients got we have been a pure play AI firm for a very long time and what has happened on the client front is that 33:20 33 minutes, 20 seconds they need much more specialized higher quality uh vendors today than ever before as AI progress accelerates really 33:28 33 minutes, 28 seconds the ones who think of AI as also one of the levers are struggling uh they don't have AI R&D spends they don't have uh 33:36 33 minutes, 36 seconds significant capabilities and therefore generic competition tends to uh suffer in a place where significant progress is 33:43 33 minutes, 43 seconds happening on a week-by-eek basis. From a client perception standpoint, Fractals's perception remains very strong and has actually accelerated because they see 33:52 33 minutes, 52 seconds the incredible amount of uh AI products and research outputs that we produce and they see as best-in-class in the AI 34:00 34 minutes field especially in the enterprise AI space. There's no one like Fractal today. uh so they see that and that helps us in expanding our business with 34:07 34 minutes, 7 seconds them especially as they think of reimagining their workflows with AI. The biggest opportunity in AI is that every single business workflow can be 34:16 34 minutes, 16 seconds reimagined with AI and this is a thing which requires not only deep AI expertise but significant domain 34:24 34 minutes, 24 seconds expertise and the ability to navigate this enterprise architectures, enterprise landscape and so on. And that is why Fractal is a is a very very 34:32 34 minutes, 32 seconds credible one of the only one of the very few credible names in this in this space. So that's why uh we see a continued expansion with the clients and 34:40 34 minutes, 40 seconds interest. Even where people think of oh I need uh you know I have too many vendors let me consolidate vendors. 34:46 34 minutes, 46 seconds Fractal has a special place because no there's no one like a pure play AI uh vendor for most of the clients except Fractal and that's what makes them very 34:55 34 minutes, 55 seconds reliant on Fractal. So that's number one. Uh number two question, number three question was on AI R&D spends. Let me answer that. Our AI R&D spends uh we 35:05 35 minutes, 5 seconds expect to continue investing in AI R&D spend. In fact, we hope that we can continue to expand the amount of investment we make in AI R&D. This is a 35:13 35 minutes, 13 seconds significant part of our overall um credibility as a company in a in a place 35:20 35 minutes, 20 seconds where AI is changing every day. the kind of uh R&D investments that we're making helps us signal to clients the kind of 35:27 35 minutes, 27 seconds uh incredible work that we're doing and the kind of capabilities that we have. 35:30 35 minutes, 30 seconds So we expect these uh investments to continue and we expect these these investments to accelerate our revenue growth and our gross margins. So way we 35:39 35 minutes, 39 seconds are thinking of it is that as we expand revenue growth and we as we expand gross margins some of that gross margin expansion will be plowed back into 35:48 35 minutes, 48 seconds increasing the AI R&D spend. That is how we are thinking of how to build fractal for the future. Now I have forgotten your second question but maybe Ashwad you want to answer that. Yeah. 35:58 35 minutes, 58 seconds Yeah. I think the question was on the engagement type moving more towards uh outputbased uh metrics. Go that's what we said. uh yes we have some outcome 36:07 36 minutes, 7 seconds based too but that's quite limited at this stage but what we are seeing is that more versus input based where it is time uh based we see that the mix is 36:16 36 minutes, 16 seconds changing more towards the output based uh metrics and uh that that's a consistent trend that we've seen over the last uh 7 to 8 months and output 36:25 36 minutes, 25 seconds based metrics we can use our internal productivity and other tools to ensure that margins are pretty high we uh we 36:32 36 minutes, 32 seconds manage the whole project end to end and uh the margin margin uh quality of output based projects tends to be higher. So it's much more beneficial for 36:40 36 minutes, 40 seconds us. Uh and just on the credibility with the clients only one metric that I'll indicate is if you look at our scaling 36:47 36 minutes, 47 seconds uh related numbers like be the total number of MWC's clients that's expanding total of clients above 1 million is 36:54 36 minutes, 54 seconds expanding total of client total clients with about 20 million is expanding about 10 millions is expanding. So that I 37:02 37 minutes, 2 seconds think is a good way to look at uh how we are a credible AI player in front of our tools. 37:09 37 minutes, 9 seconds I'll just add to the uh outputbased etc. 37:12 37 minutes, 12 seconds We are extremely confident that output based and outcome based models are will actually expand across margins. So we 37:20 37 minutes, 20 seconds are actively uh reinitiating conversations wherever we feel like we can convert any existing relationship into more output or outcome or license 37:29 37 minutes, 29 seconds driven conversation and we also the side effect of that is that it they're all at higher margins higher gross margins than 37:35 37 minutes, 35 seconds our other business model business uh models and therefore overall this will be a gross margin uh a creative uh kind of work that we'll do. 37:49 37 minutes, 49 seconds Thank you for the detailed answers. Uh just to put my second question in context of outcome based. Uh the reason 37:56 37 minutes, 56 seconds I was asking is because not be well placed to shift the business model or engagement model to outcome 38:05 38 minutes, 5 seconds based. There will be very few companies who will be able to underride that and probably you guys are well placed around that. So I was just trying to ask that 38:14 38 minutes, 14 seconds you know uh the the capabilities do they give you readiness move to outcome based 38:21 38 minutes, 21 seconds uh because you were able to underwrite those outcomes which others are not. 38:24 38 minutes, 24 seconds That was a context of the question but thank you for the detailed answer. 38:29 38 minutes, 29 seconds Thank you Gorov. Absolutely. We have very credible uh AI capabilities, lots of AI research. Our cogentic 38:37 38 minutes, 37 seconds platform these help us in reimagining business process with AI and being confident about doing this in much shorter time. So whenever we we have an 38:45 38 minutes, 45 seconds output based or outcome based conversation we are very eager for that because it gives us an opportunity to uh expand our margins while delivering better outcomes to our clients faster. 38:55 38 minutes, 55 seconds So uh absolutely ready for this kind of a transformation across the board. 39:03 39 minutes, 3 seconds Thank you. We move to our next question that's from Kamaljit Suja of Kotuk Securities. Please go ahead. 39:13 39 minutes, 13 seconds Hey. Hi Shikhant. Hi everyone. 39:16 39 minutes, 16 seconds Congratulations on your listing. U just a couple of questions. The first one is for Shriant. uh Shriant uh you did 39:23 39 minutes, 23 seconds allude to the fact that you have grown by 30% uh in the past and uh you know in a way implying that uh the aspiration is 39:32 39 minutes, 32 seconds to grow at an elevated rate uh whereas your current growth rate is lower than what you aspire for. So what would you attribute the gap between an aspiration 39:41 39 minutes, 41 seconds with the versus the current growth rate and how do you intend to bridge the gap between the two? That's the first question. 39:48 39 minutes, 48 seconds Well, thank you Kavajit. Absolutely. Our aspiration continues to be to grow. We have even if you look at the last 10 39:56 39 minutes, 56 seconds years uh not every year we've grown at 30%. There are some years we've grown a little lower some years we've grown much 40:03 40 minutes, 3 seconds faster net of that is the 30%. And this is maintained over every 3 to 4 year period it then the growth rate is 30%. 40:11 40 minutes, 11 seconds And uh this year specifically started off with a little bit of the trade headwinds coming from uh in the CPG 40:18 40 minutes, 18 seconds vertical which as you know is one of the largest vertical for fractal. So in that segment we found that uh there was un 40:26 40 minutes, 26 seconds massive uncertainty uh in especially in April of this year when the financial year just started where uh the liberation day announcements came in and 40:34 40 minutes, 34 seconds some of the announcements came in a little before that which created uncertainties and when businesses feel uncertain they kind of wait on their 40:43 40 minutes, 43 seconds spend. So it it they tend to delay their spend. So that is one of the reasons why our growth rate was not as spectacular 40:50 40 minutes, 50 seconds as we would like it to be. If you just exclude that I think the numbers would be around 26% or so the rest of the business grew and even if you see the uh 40:58 40 minutes, 58 seconds for the 9 months we have grown 26% in in in the US and 37% in Europe for the 9 months. So there are pretty decent 41:06 41 minutes, 6 seconds numbers which just shows you that the potential of this business to grow at the historical rates is there. We have to make sure that we execute well and 41:14 41 minutes, 14 seconds obviously there are things that we may not always be able to control in the in in the way things happen but we do see 41:21 41 minutes, 21 seconds AI related expansion as a massive opportunity for fractal to continue its revenue trajectory. 41:28 41 minutes, 28 seconds That's very helpful and that's clear. Uh the second question uh uh that I had is on R&D spend u you did uh indicate that 41:36 41 minutes, 36 seconds uh you know that's an area that uh you want to double down on. Uh now at a high level we are aware of the areas uh on uh 41:44 41 minutes, 44 seconds you know where you are spending on R&D but can you flesh out in more detail where would the incremental spend be allocated on on R&D and how do we uh assess the efficacy of the spend. 41:56 41 minutes, 56 seconds Great. Now first in terms of efficacy of spends Kavajit eventually we have to expand our uh revenues faster uh so 42:04 42 minutes, 4 seconds accelerate our revenue growth as well as expand our gross margins. Eventually this is the most important indicator of AI R&D success uh that if you take a 42:12 42 minutes, 12 seconds longer term in the in the medium-term to shorter term we have to achieve benchmark results on everything that we do the way we are thinking of the AI R&D 42:21 42 minutes, 21 seconds spends is it has to either help our fractal.ai AI business expand its revenue growth. Therefore, for example, the PI evolve machine learning agent is 42:29 42 minutes, 29 seconds something that we can use across the problems that we solve today and dramatically accelerate our productivity and therefore expand our margins. So 42:37 42 minutes, 37 seconds that is one one such example. Second place we want use to use AI R&D is on our products. For example, the cogentic 42:44 42 minutes, 44 seconds platform, the Asper platform. Here we want to make sure that we're investing R&D AI R&D to build the best-in-class uh 42:52 42 minutes, 52 seconds agentic AI platforms and this is a is an incredibly big opportunity and also a opportunity where things are changing 43:00 43 minutes pretty fast. So we want to make sure that we have the best-in-class platform to help the biggest companies in the world reimagine their workflows with AI. 43:08 43 minutes, 8 seconds So that's the second place where we want to connect the AI R&D to that. The third one is a place where we are building um 43:16 43 minutes, 16 seconds AI research on let's say Vya which is a healthcare area. It has uh impact on our healthcare segment but also it is 43:24 43 minutes, 24 seconds something that we're thinking of as part of India AI mission to build a India level model that the 1.4 billion people 43:31 43 minutes, 31 seconds of this country can use. Uh if we are very successful with that and if you're able to launch with the India AI mission it could be gamechanging. uh and it 43:40 43 minutes, 40 seconds would it that feedback from that 1.4 4 billion people using could help us achieve frontier AI and uh you know India achieving frontier AI. So that's 43:49 43 minutes, 49 seconds the big dream. Uh that's the third aspect. So these are the three places where we are sort of dividing the spends. Number one expand fractal.ai and 43:57 43 minutes, 57 seconds improve the overall gross margins and revenue growth. Number two build the cogentic platform again helping companies reimagine their AI workflows. 44:05 44 minutes, 5 seconds And three is building this Vaia platform for India AI uh or India healthcare. So these are the three places where we are 44:13 44 minutes, 13 seconds uh aortioning the specs. Ashwad if you want to add to that please feel free. Yeah nothing much to add. 44:22 44 minutes, 22 seconds No that's a fantastic response Shriant just to uh uh uh you know just a final question on agentic AI platform and 44:30 44 minutes, 30 seconds that's fascinating as well. Can you let me know the uh you know of course what it seems is that you're working on building homegrown agents. So can you 44:38 44 minutes, 38 seconds just tell me the underlying models that you're using is it llama or you know any of the open source models and second is that you know in a client environment 44:46 44 minutes, 46 seconds shriant what do you think eventually will what will work you know would it be the frontier model companies agents 44:53 44 minutes, 53 seconds which uh players would use to deploy in a client environment or would clients be comfortable working uh with uh uh let's 45:00 45 minutes say the homegrown agents of players like you and if it is uh you know your agents then what is the pricing model that you 45:08 45 minutes, 8 seconds have adopted is it an all-in pricing including token costs I mean there are multiple thoughts that I have on you know agentic yes maybe just some high 45:15 45 minutes, 15 seconds level thoughts will be helpful thank you Kavaj very very good questions number one is that the way we have 45:22 45 minutes, 22 seconds thought about cogentic is that we are not competing at the model layer with open AI or uh anthropic or claude etc 45:31 45 minutes, 31 seconds one very important metric to think of is if openai launches their new model or claude launches their new model should we be excited or should we be scared? 45:40 45 minutes, 40 seconds The way we built cogentic is that we should be excited because any underlying model improvement dramatically improves cogentic's performance so cogentic is 45:48 45 minutes, 48 seconds the onlogical layer on top of these models and then an agentic layer to go and solve enterprise workflows reimagine them. So if the underlying base model 45:57 45 minutes, 57 seconds improves all of the stuff that we do on top of that automatically improves and therefore we can get better results much uh faster results. So and the way we 46:06 46 minutes, 6 seconds price this today is that we do not uh charge them for the underlying model uh usage. That is an expense that they incur directly from the underlying model 46:15 46 minutes, 15 seconds providers. They can use the fractal fathom models etc which are fine but they can use open AI is GPD5 or claude 46:23 46 minutes, 23 seconds 4.6 opus or any other underlying model that makes sense to them and the cogentic platform is the builds the ontological layers as well as the 46:31 46 minutes, 31 seconds agentic layers to help them reimagine their workflows. The way it works is that we have built a bunch of agents which are specialists in a certain 46:38 46 minutes, 38 seconds tasks. These agents have access to a whole host of machine learning tools and these machine learning tools directly connect with enterprise data sources 46:46 46 minutes, 46 seconds including SAP and etc. Therefore, when they these agents are able to access machine learning tools and access data, they're able to solve these problems. 46:55 46 minutes, 55 seconds And this is something that Fractal is uniquely positioned to do because we have deep understanding of the enterprise landscape, the problems they're solving, uh the data flows that 47:03 47 minutes, 3 seconds they have and what's happening with their business. So, that really puts Fractal in a really good position. And we charge them on a on a license basis 47:11 47 minutes, 11 seconds on a output basis uh but not on a model consumption basis because the inference token costs will be directly charged to 47:19 47 minutes, 19 seconds them through the model provider unless they're using our model. 47:23 47 minutes, 23 seconds Uh that's fascinating. Just a final question uh uh uh you know on agents how uh you know what's in an agentic system 47:31 47 minutes, 31 seconds the biggest problem is uh uh you know a compounding of errors. uh so uh you know with your agents I mean I think current 47:39 47 minutes, 39 seconds agent accuracy is also not something in which an agentic layer can work very well. So how much is the human in loop uh involvement and second if you can 47:47 47 minutes, 47 seconds just dwell upon uh you know how frequent is the agent drift problem in a client environment sorry the last part I couldn't get agent 47:56 47 minutes, 56 seconds last agent agent drift yeah drift okay got it see you're bringing up a very important point and this is one 48:03 48 minutes, 3 seconds of the reasons why um the adoption of enterprise adoption of AI is still not taken off in a very significant way when 48:12 48 minutes, 12 seconds you think of consumer Consumer AI error is okay. If you have 50% hallucination rate or 40% hallucination rate, it's 48:19 48 minutes, 19 seconds fine. It works just fine. Uh but in case of enterprise AI, we have to consistently meet and exceed human accuracy in that process. So when we're 48:27 48 minutes, 27 seconds building systems, we're not always building these systems to be 100% autonomous because that will create the drift that you spoke about create 48:34 48 minutes, 34 seconds accuracy issues etc. We build the system to be human plus machine automatically so that the agent drift or the model 48:41 48 minutes, 41 seconds error which get compounded etc those are actually solved for from the from the human input or human approvals etc that 48:48 48 minutes, 48 seconds are required. Number one number two is that we build this in such a way that as AI gets better the need for human input comes down accuracy automatically 48:56 48 minutes, 56 seconds improves. So in in processes where overrides are possible for for example humans can override any AI output but then we keep track of when is the 49:05 49 minutes, 5 seconds override working and when is the override actually a bad idea. So after after some time people start to figure out that the overrides the human overrides are not necessary. In fact 49:14 49 minutes, 14 seconds they are detrimental and therefore they increase the trust in the AI systems. 49:18 49 minutes, 18 seconds Our goal is to build trusted AI systems which take care of these kinds of issues and as underlying model improvements 49:25 49 minutes, 25 seconds happen all of this this continues to improve in the in the right direction. 49:32 49 minutes, 32 seconds Thank you. Before we take our next question, we'd like to remind participants to please limit your questions to two questions per turn. 49:40 49 minutes, 40 seconds Time permitting, you may come back in the queue for a follow-up question. 49:44 49 minutes, 44 seconds We'll take the next question from Pratesh Takar of PL Capital. Please go ahead. 49:53 49 minutes, 53 seconds Yeah, congratulations um on listing and uh on good set of numbers. U my first question is on uh on fractal alpha. 50:02 50 minutes, 2 seconds There is a sequential decline in the top line that we saw in for the three. Is it something related to cyclicality or uh 50:10 50 minutes, 10 seconds or is there any challenge in this uh or how would you put it? 50:15 50 minutes, 15 seconds Yeah, I can take that. Uh so in fractal alpha it's made up of Asper and Analytics Vidya. In analytics Vidya our 50:23 50 minutes, 23 seconds Q2 tends to be a place where we do a big uh data hack summit uh which creates 50:30 50 minutes, 30 seconds revenue um and uh generally so it's cyclical uh in nature. most of the years it tends to happen in the second quarter 50:38 50 minutes, 38 seconds and in the asper side of the business too uh like as I mentioned uh in CPG and retail with all the tariff related uh 50:48 50 minutes, 48 seconds tumult uh tantrums. So there was clients were a little bit slower uh to sign up for new contracts. So as some of the initial setup phase revenue uh came off. 51:01 51 minutes, 1 second So there was a sequential decline in ASA 2 uh which is not really a uh uh seasonal thing. What we saw in analytics 51:10 51 minutes, 10 seconds with more seasonal which we expect even next year but as per uh we did see uh uh 51:17 51 minutes, 17 seconds the new clients addition was slower in the first uh 9 months of the year that led to a small sequential decline in uh uh asper. 51:28 51 minutes, 28 seconds Okay understood. Um just wanted to understand the normal uh course of our uh our performance of our business in 51:35 51 minutes, 35 seconds H2. uh is it Q3 or Q4 tends to have more weightage in terms of um you know higher growth and better margins? Uh so this is 51:44 51 minutes, 44 seconds my first question. Secondly, when do we consider compensation revision? You also highlighted uh in your remark also you've given out uh some compensation 51:51 51 minutes, 51 seconds revision this quarter itself but uh what is our usual compensation revision during the quarter? 51:59 51 minutes, 59 seconds Yeah. uh our the historically we have done compensation revision as the 1st of April. Uh when I talked about Q3 I 52:07 52 minutes, 7 seconds talked about obviously previous year to this year uh Q3. So hence there is that impact of merit increases. Uh so it always happens in April. So the reason 52:16 52 minutes, 16 seconds you see uh the profitability being higher in second half of the year is because as we keep growing quarter on quarter like uh margins tend to keep 52:26 52 minutes, 26 seconds going up with both operating leverage as we scale further and in uh the first quarter where there is merit increase uh 52:33 52 minutes, 33 seconds the margins in that particular quarter tends to come down and then picks back up again in uh second quarter third quarter and fourth quarter that's how we 52:41 52 minutes, 41 seconds see uh and as I said like historically we always done it as a first of April but we will continue to kind of uh yeah 52:49 52 minutes, 49 seconds I don't we have a very um like set timeline for the next year right now but uh this is something that we review 52:56 52 minutes, 56 seconds every year so and we have not missed uh year uh at least in a while right now 53:04 53 minutes, 4 seconds and I just wanted to understand on Q3 or Q4 tends to be more more weightage in terms of higher growth or better margins how should we consider Q4 53:12 53 minutes, 12 seconds yeah no we uh no we don't really see any kind of budget flush kind of stuff uh which other people talk about in Q3 53:20 53 minutes, 20 seconds specifically. Uh no, we uh so there's no real seasonality in terms of quarteron quarter growth. So like uh what we 53:28 53 minutes, 28 seconds expect is to keep growing quarteron quarter at a steady pace over a period of time. So it's not uh that we expect 53:36 53 minutes, 36 seconds okay Q3 to be pretty big because a lot of people tend to spend the budgets. So those seasonal effects are very minimal for us. So it's I I can't say that 53:44 53 minutes, 44 seconds there's absolutely no impact but very very minimal for us uh in terms of growth. So our expectation is that quarteron quarter we keep expanding uh 53:53 53 minutes, 53 seconds scaling our revenues and in one quarter where there is merit increase obviously there will be impact on the margins that generally tends to be the first quarter 54:02 54 minutes, 2 seconds of the year. So as the year progresses margins keep improving. 54:06 54 minutes, 6 seconds And lastly from my side uh as we you know move into next year uh what are the lead indicators uh that we should focus 54:14 54 minutes, 14 seconds on uh if you can highlight anything in terms of PCB or execute auto that we have uh you know carried in the books u that gives us visibility for next year uh growth. 54:25 54 minutes, 25 seconds uh we look at the the mustwin clients uh that we have as on date as of the December was 127 that's continues to be 54:33 54 minutes, 33 seconds growing that's a great lead indicator and 58 clients above million uh that's also great lead indicator net revenue retention is another great lead 54:42 54 minutes, 42 seconds indicator we generally enter the year with around 2/3 of uh visibility from both order book uh and renewals and 54:52 54 minutes, 52 seconds weighted pipeline uh and we are seeing similar trends versus the previous year. 54:58 54 minutes, 58 seconds So the two/3 of the visibility into the next year. Uh we are not specifically reporting order book and TCU because business is not run like that. We are 55:06 55 minutes, 6 seconds more focused on how do we grow our net revenue retention and growth from new clients. That's where the focus is and that's what we look at as the lead 55:14 55 minutes, 14 seconds indicator for our future success. But in terms of visibility, we enter the year with almost twothird of the revenue visibility into next year. 55:23 55 minutes, 23 seconds Okay. Understood. Thank you so much and best of luck for the country. 55:28 55 minutes, 28 seconds Thank you. Our next question is from Abhishek Shindar of Incred Capital. Please go ahead. 55:35 55 minutes, 35 seconds Hi, thanks for the opportunity and congratul uh three questions. Uh the first one is 55:43 55 minutes, 43 seconds on let's say the competitive mode. So you know uh can you elaborate uh what is 55:50 55 minutes, 50 seconds our long-term defensive mode for our vertical specific models that we are trying to build to eventually kind of 55:58 55 minutes, 58 seconds you know avoid any cannibalization that's the first the second you talked about the monetization which is uh uh you know moving to a license fee uh at 56:08 56 minutes, 8 seconds points uh do is there a possibility that uh you know we may get competition from the frontier models that's The second 56:17 56 minutes, 17 seconds and the third is especially for the India mission work that we're doing uh the data sets and the compute 56:24 56 minutes, 24 seconds requirements for us are solved uh from uh uh you know from Indian providers or how do we go about okay these are my 56:33 56 minutes, 33 seconds three questions. Thank you for taking my question. 56:37 56 minutes, 37 seconds Thank you Abhishek. Uh on the third question first um for the India AI mission we will have compute coming from 56:46 56 minutes, 46 seconds the approved vendors of the India AI mission and we get a specific preferential rate on that uh H100 that 56:54 56 minutes, 54 seconds we end up using for that and the and we also get a subsidy from the government. 57:00 57 minutes They fund part of that uh negotiated rate. So that's the how the compute is set up. These are there are few providers that India AI mission has 57:09 57 minutes, 9 seconds selected and has agreed pre-aggreed negotiated rates. We get those rates in the way we use the compute for the India 57:16 57 minutes, 16 seconds AI mission related work. That is on your third question. Can you please remind me the second first question? Um 57:23 57 minutes, 23 seconds and comparative mode on the comparative mode of fractal across domains. Number one is that we have a deep understanding 57:32 57 minutes, 32 seconds of the domain. We know the enterprise workflows. We have solved these problems multiple times. For example, think of 57:40 57 minutes, 40 seconds revenue growth management. Understanding all the complexity of thousands sometimes millions of SKUs across all 57:47 57 minutes, 47 seconds the geographies and understanding how pricing promotion uh and revenue growth and strategic revenue management happens inside companies. we understand that 57:54 57 minutes, 54 seconds really really well and we are able to bring in very solid um AI models that are trained or fine-tuned on that 58:03 58 minutes, 3 seconds vertical for them which makes it very advantageous for companies to work with us and again secondly we have to make 58:10 58 minutes, 10 seconds this work inside an enterprise context which means that we have to know all the data that is available in inside the enterprise this is dark data that others 58:19 58 minutes, 19 seconds don't get to see and or proprietary data sets that the models have never seen So we see those data sets, we are able to 58:27 58 minutes, 27 seconds bring those data sets into the way we solve problems. So the entire work of Fractal is inside the enterprise data 58:34 58 minutes, 34 seconds systems, right? So we can to build models, train models for the specific context of the enterprise data. This is 58:41 58 minutes, 41 seconds a very defensible mode. Uh Fractal also has a deep design capabilities which we call as behavioral sciences capabilities 58:48 58 minutes, 48 seconds just to understand human behavior in and how humans actually make decisions. when we combine that with a deep understanding of AI models that creates 58:57 58 minutes, 57 seconds a very unique uh competence that at least we haven't seen anyone else match as of right now. So these are the things that make us very competitive in the in 59:06 59 minutes, 6 seconds the space in every vertical that we choose to operate in and we do think of it carefully in terms of when we expand in a new vertical we do that when we 59:15 59 minutes, 15 seconds know that we have something very credible or we intend to build something credible in that space. Uh the last one is on the on the competition from the 59:22 59 minutes, 22 seconds frontier models. The frontier models obviously are expanding everywhere at all at once and they have very they're 59:29 59 minutes, 29 seconds very ambitious. They also rely realize that they need partners and they need people who can build on their uh generic capabilities which are very very good. 59:39 59 minutes, 39 seconds So when we build our cogentic platform we we build an ontological layer on the on the models that per se and then help 59:48 59 minutes, 48 seconds them reimagine their workflows which is again extremely challenging for the for the open and the frontier models to directly do themselves. So if you think 59:57 59 minutes, 57 seconds about a comparison here Palunteer is doing exactly that and that's working really well for them. They're able to drive higher gross margin. We expect a 1:00:05 1 hour, 5 seconds similar way that this will be a very collaborative ecosystem. Of course, there'll be some competition too, but we 1:00:12 1 hour, 12 seconds see a huge opportunity for us to uh take underlying powerful models and build on top of that u the kind of platforms that we're building including coette. 1:00:26 1 hour, 26 seconds Thank you. 1:00:27 1 hour, 27 seconds This is Thank you very much. Um ladies and gentlemen that was a last question and uh with that we conclude the question 1:00:36 1 hour, 36 seconds and answer session. Before I hand over the call to Anjali Gur from Fractals's investor relations team for closing 1:00:43 1 hour, 43 seconds comments request Shri Khan to share his final remarks. Thank you Inba. 1:00:51 1 hour, 51 seconds We had a great December quarter with improvements across almost every metric. 1:00:56 1 hour, 56 seconds revenue growth at 21% driven by strong growth in life science and healthcare as well as banking and financial services verticals. A strong client relationships 1:01:04 1 hour, 1 minute, 4 seconds are evident from the NRR or net revenue retention of 114% for Q3 and 115% for the 9-month period. On the profitability 1:01:13 1 hour, 1 minute, 13 seconds front, we reported a best-in-class 42 47.2% gross margin and our PAT cross the 1 billion milestone. Lastly, we continue 1:01:22 1 hour, 1 minute, 22 seconds to invest heavily in R&D focused on foundational AI research as well as AI products. In addition to helping us build solid capabilities that help us 1:01:30 1 hour, 1 minute, 30 seconds solve our clients most pressing business challenges, these investments will create significant growth opportunities in the future. Looking ahead, we're very 1:01:39 1 hour, 1 minute, 39 seconds excited by the opportunities that the AI revolution is opening up for us. As a pure play AI native company that has significantly invested in AI R&D, we are 1:01:48 1 hour, 1 minute, 48 seconds very well placed to fully benefit from these opportunities, drive exponential growth and create tremendous value for our shareholders. Over to you Anjeli. 1:01:59 1 hour, 1 minute, 59 seconds Thank you Shikan. Thank you everyone for joining us on our first earnings call as a public company. This is a significant milestone for Fractal and we are excited 1:02:08 1 hour, 2 minutes, 8 seconds about the opportunities ahead. If you have any further questions, including any that we were unable to address during the call today, feel free to 1:02:16 1 hour, 2 minutes, 16 seconds reach out to us at investor relations at frackle.ai. 1:02:20 1 hour, 2 minutes, 20 seconds We look forward to seeing you again next quarter. Thank you once again and wish you a good day. 1:02:26 1 hour, 2 minutes, 26 seconds Thank you. Thank you everyone for joining us today. You may now click on the leave button to exit the meeting. Goodbye.