Good evening, ladies and gentlemen. I'm Akash, moderator for the conference call. Welcome to 1Point1 Solutions Limited Q1 FY27 Earnings Conference Call. As a reminder, all participants will be in listen-only mode, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during the conference call , please signal an operator by pressing * and 0 your touch -tone telephone. Please note this conference is being recorded. I would now like to hand over the floor to Mr. Shashank Ganesh from EY. Thank you, and over to you.

Thank you, Akash. Good evening to all the participants on the call. Good morning if you're logging in from the Western side. Before we proceed to the call, let me remind you that the discussion may contain known or unknown risks, which may affect the forward-looking statements, uncertainties, and other factors. Therefore, it must be viewed in conjunction with the business risks that could cause further result s, performance, or achievements that differ from what is expressed or implied. To take us through the results and answer your questions today, we have the senior management of 1Point1 Solutions, represented by Mr. Akash Karnik, Whole -Time Director & Chief Executive Officer – Global Business; Mr. Rajiv Desai, Co-Founder–ResolX; and Mr. Sunil Kumar Jha, Chief Financial Officer. We will start the call with a brief overview of the past quarter followed by a Q &A session. We would appreciate your cooperation in restricting yourselves with two questions to allow participants an opportunity to interact. If you have any further questions, you may join the queue and we will be happy to respond to them if time permits. With that, I would like to hand over the call to Mr. Karnik. Over to you, Akash.

Thank you, Shashank. Good evening, everyone, and thank you for joining 1Point1 Solutions Q1 FY27 Earnings Call. In today's call, we will cover the company's performance for the quarter, the strategic transformation underway across the businesses , and how our investments in AI, global delivery , and domain capabilities are opening up significantly larger market opportunities for 1Point1 Solutions. 1Point1 began 17 years ago with a simple conviction. Every customer interaction is an opportunity to create value. From a single operations floor, we've grown into a dual -listed enterprise with a global footprint, deep domain expertise, and a portfolio serving 100 plus marquee brands across banking, insurance, healthcare, telecom, aviation, automotive, and other emerging industries. Today, we are moving beyond traditional outsourcing to build 1Point1 Solutions as a global AI -powered customer experience and enterprise operations company, bringing together human expertise, Agentic AI, domain depth, and global delivery to engineer measurable outcomes. This evolution is at the heart of our strategy and defines the next phase of our growth. Over the years, we deliberately invested ahead of the curve in technology, domain capabilities, and global delivery. We recognize that AI will fundamentally reshape customer experience and enterprise operations, not just automating individual tasks, but by changing how work is designed, executed, and measured. That journey led to creation of 1Point1 Technology Labs and subsequently the launch of ResolX, our Agentic AI platform built around Resolution-as-a-Service. ResolX marks an important shift in our value proposition from managing activity to taking accountability for resolution. The next phase of customer experience will not be defined by how many interactions a company handles. It will be defined by how effectively those interactions are converted into measurable resolutions and business outcomes. As highlighted in our investor presentation, our strategy is built on dual-engine growth. First, our global human service engine , significantly strengthened this quarter by the full integration of Netcom, which deepens our presence across the Americas, and expand our ability to service enterprise through global delivery, multiple capability, domain expertise, and multi-shore operations. It also creates larger platform from which we drive organic and introduce AI-led transformation across existing and new enterprise relationships. Second, our Agentic AI engine, powered by ResolX, is a differentiated enterprise AI platform, bringing Agentic AI orchestration and domain intelligence directly into enterprise workflows focused on high-value opportunities. Together, these engines create a powerful growth model, global delivery, and human expertise complemented by Agentic AI and intelligence orchestration. More importantly, they strengthen and accelerate each other, creating greater scale, capability, and value for our customers. As automation scales, we see the opportunity to progressively shift our revenue towards higher -margin AI, orchestration, and outcome models, while human expertise moves towards more complex, judgment- led work. Our presence across multiple domains, geographies, and delivery ecosystems gives us a strong foundation to build intelligent, scalable, outcome-focused enterprise operations. We believe the next era of customer experience will be defined not by isolated AI developments, but by reconnecting intelligence that unites AI, human expertise, domain depth, and operational execution. ResolX is built precisely for this shift, embedding intelligence into real enterprise workflows and solv ing complex regulated business challenges. Technology can automate domain intelligence, enable better decisions, human expertise brings judgment and accountability. This combination lets us move beyond traditional capacity-led outsourcing towards measurable, outcome-focused enterprise operations. Our global delivery engine, domain depth, and Agentic AI capabilities position us at the intersection of customer experience and enterprise operations. We are not preparing for the next phase of market. We are building immediate. 1Point1 is hired for outcomes. On that note, I'll hand over to Mr. Rajiv Desai, Co- Founder of ResolX.

Thank you, Akash, and good evening to everyone who has joined the call. For three decades, India has thrived as the world's back office, powered by the scale and efficiency of BPM. Agentic AI is creating a fundamental shift in enterprise operations. Systems that can plan, decide, and act are moving AI beyond assistance and towards execution, orchestration, and resolution. We don't see this as a replacement of human expertise. We see it as an evolution from a cost and headcount -led model to an intelligence and outcome-led model. The sector will need deeper, more integrated roles that merge human judgment with machine efficiency. The future belongs to operating models where human contextual intelligence works alongside the speed, scale, precision of AI. That is the shift we are building with ResolX, moving enterprises beyond managing interactions towards intelligent, accountable resolutions at scale. ResolX differentiated through its Resolution-as-a-Service model, is designed to move AI beyond assistance to act, orchestrate, and deliver measurable resolutions across enterprise workflows. Resolution-as-a-Service is an operating and commercial model that orchestrates AI agents, workflows, enterprise systems, fun ctions, data, and human expertise under one accountable partner to deliver a great customer or business outcomes, m oving enterprises beyond software development to strategic operating partnership focused on measurable results. ResolX is built around an outcome -accountable model. We do not charge clients simply for a software license or agent capacity, but we take ownership of the resolution architecture end to end . From the AI layer and data extraction to back-end integration and ultimately the business outcomes themselves. This is fundamentally different value proposition. Instead of investing in disconnected tools and managing multiple vendors with no accountability for the final outcome, client gets one partner that brings intelligence, integration, and execution together , accountable for the resolution itself. We're leading the shift from conversations to resolutions by creating AI that acts, orchestrates, and resolves, not just answers. History shows that efficiency expands markets. Resolution is how we deliver them. Our integrated stack spans across voice, chat, email, social, IVR, and video, with AI embedded across the entire journey, one partner for connected intelligence across every enterprise function. More importantly, our global operating footprint gives ResolX an advantage that pure-play AI vendors cannot easily replicate, operational experience across languages, near -shore capability across the Americas, and regulated industry delivery on four continents. Each center serves not only as a delivery engine, but as a real-world environment to deploy, validate, and scale intelligent solutions. The software-to-service gap remains one of the biggest challenges for CX leaders, and ResolX bridges that gap by combining AI, integration, operational accountability, creating value to clients while strengthening our own economics. Faster resolutions reduce agent hours per interaction, improves utilization, and lowers the cost to serve, creating a dual advantage, higher value delivered to clients with stronger operating leverage for 1Point1. We're seeing encouraging early traction, 12 live deployments across seven enterprise clients spanning across insurance, aviation, banking, automotive, and digital assets, including two of India's largest life insurers. Two Central American banks, one through the Netcom BCC acquisition, a leading Indian airline, and a premium European automotive marquee. Most significantly, the nature of these engagements is changing. The market is looking beyond capacity towards AI-led measurable outcomes. 1Point1 brings global delivery, domain depth, human expertise, and enterprise accountability. Resol X brings Agentic AI, intelligent orchestration, and Resolution-as-a-Service. Together, they create a connected operating model designed to move enterprises from conversations to resolutions and deliver measurable outcomes. With that, I hand over to Mr. Sunil Kumar Jha, Chief Financial Officer, to take you through the numbers. Over to you, Sunil.

Thank you, Rajiv, sir, and good evening, everyone. Let me take you through our financial performance for Q1 FY27, a quarter that makes a steep change in the scale of company. As the first full reporting period to consolidate Netcom BCC, on a consolidated basis, revenue from operations from Q1 FY27 was INR 158.3 crore, a growth of 64.6% QoQ and 129% YoY. This growth was driven primarily by the first full quarter consolidation of Netcom, supported by growth in customer program volume across the base business. EBITDA stood at INR 39.4 crore, up 56% from INR 25.2 crore in Q4 FY26 and 91.5% YoY, at an EBITDA margin of 24.9%. Profit for the period was INR 16.3 crore, up 58.7% from INR 10.3 crore in Q4 FY27 and 72.8% YoY basis. Basic earnings per share for the quarter was 0.62 compared with 0.36 in the corresponding quarter in last year. Let me give some more clarity about the margins. The consolidated EBITDA margin of 24.9% reflects the change in delivery mix from Ne tcom consolidation and finance cost of INR 8.1 crore for the quarter, up from INR 1.9 crore a year ago, primarily reflecting acquisition -related borrowing. On a standalone basis, our core operation delivered revenue of INR 61.1 crore, up 11.6% YoY, at an EBITDA margin of 30.4%, demonstrating the continued health of the base business on which the global platform is being built. Our revenue mix is shifting toward AI orchestration and outcome -linked models. We expect margin s to improve progressively over the coming year. Q1 continued the momentum we have built over the past several quarter s. We remain confident in our ability to capture the significant market opportunity added by scaling ResolX, deepening existing customer relationships and expanding our customer base. Our growth strategy is deliberately balanced with resilient core revenue, the ramp -up of new customers and a diversified pipeline of opportunity across market and capabilities. With a healthy customer pipeline, growing enterprise demand, disciplined capital allocation, and ResolX gaining traction in live in one, we believe 1Point1 is at beginning of significant multiyear growth opportunity. Our dual-engine global delivery and Agentic AI has given us a strong foundation for scale, while disciplined capital allocation and operational execution remain central to how we grow. Our focus remains clear, sustainable, profitable growth with continued several investments in innovation, talent, and scalable global capability, translation of those investment into a stronger operating performance and long-term shareholder value. Thank you. We are now happy to take your questions.

Thank you, sir. Ladies and gentlemen, we will now begin the question-and-answer session. If you have a question, please press * and 1 on your telephone keypad, and wait for your turn to ask the question. If you would like to withdraw your request, you may do so by pressing * and 1 again. Ladies and gentlemen, if you have a question please press * and 1 on your telephone keypad. The first question comes from the line of Mr. Yogesh Patil, an Individual Investor. Please go ahead, sir.

Good evening, sir. Congratulations on a good set of number s. Sir, just want to continue on the current result, how do you see this year? I think the numbers are really good. Any kind of one-off or any kind of project completed in this quarter, or do you see this run rate will continue for full year also?

This is not a one-off number. To give you more clarity, t his is the first quarter where we've consolidated Netcom completely. We should be able to try and double our revenues this year, and that's what we are currently embarked on. We're fairly confident that we'll be able to achieve a good run-rate this year. We have a strong trajectory ahead of us, so it's not a one-off number.

I'm thinking in consolidation also, it means a pure consolidation. In the thing, one-off project consolidation.

No, this is the consolidated number.

Okay. Where do you see traction in terms of segments? We rightly highlighted insurance company and banks? Can you throw some more light on continuity of this?

The continuity of the numbers itself is coming from our purely consolidation of numbers and our acquisition that happened last year. From a growth perspective, we are very staked at the right point where our Agentic AI solutions, along with our human-based systems, will try and bring in far more results to us. These numbers will not currently have any impact from our delivery perspective. All seems to be very stable with good numbers. AI will continue to grow and start bringing in better margin numbers for us in the coming quarters.

Okay. We're also using AI. In last quarter, we started some benefit. But if I attribute to usage of AI, what could be the quantifiable amount of the productivity gains because of the AI use and makes of the employees' manpower and AI?

I'll try and answer this question with one of the examples in one of the large airlines that are currently operating out of India. We’ve been successfully being able to deploy AI to seek benefit about 30% of the employee size, and thereby bringing far more value-added services to them. As our projects start growing up QoQ, YoY, you will see the impact of AI on our revenues in the coming 12-18 months.

Okay. Sir, one hypothetical question over three to five years. How do you see yourself ? What are the geography and company sectors will contribute to growth over three to five years?

We'll be growing on India and LATAM, while the entire Americas will be able to increase revenue s purely because of the dollar arbitrage. India will also continue to grow from an AI contribution perspective. But you will see a lot of business showing up with larger volume, purely because of dollar arbitrage from the Americas. From an industry perspective, while there is focus across industries, you will see a lot of work coming through the banking industry and a little bit on insurance side, healthcare. These are some of the industries that are showing trajectory right now. You' ll also see some more trajectory coming in travel and hospitality also.

Okay. Thank you very much, and all the best.

Thank you very much.

Thank you, sir. The next question comes from the line of Tushar Sarda from Athena Investment . Please go ahead, sir.

Thank you for the opportunity, and congratulations on good headline numbers. I was just going through your presentation, could you please split the revenues between Netcom and your base business?

Netcom, right now, in this quarter, contributed roughly about 50% of the numbers that we see here.

That's on revenue – what was the split on EBITDA?

Around the same number. 50% of our revenue contributions is from Net com and likewise for EBITDA contributions.

Okay. What are the margins at Netcom?

Netcom’s margins are in a similar range of 24-25% as well.

Okay. You have now debt of INR 220 crores. What is the plan with respect to the debt? Do you plan to bring it down, raise equity? Or will you pay off from the earnings? What is the idea?

I think our cash earnings in the coming quarters is only going to increase. The cash generation is fairly positive. The debt servicing is going to become easier in the coming quarters.

Do you have more acquisition plans?

In the next three years, we intend to try and acquire another two companies that are on our radar. But this time, we're looking at companies which have Fortune 500 brands, and that can really bring us to the largest spectrum of North America. That's been the prime focus for us to look at acquisition. Our focus will be to leverage our AI to really try and make a differentiation, create an exit barrier and bring in far more value to these businesses, which we are already doing with our customers.

How much revenue is contributed by this Agentic AI in the current quarter?

We just launched our Agentic AI early in the year in May, and we've been able to successfully deploy close to about 6-7 projects across the 12 that we are currently doing. Revenue is just catching up on the scheme of events. We should be able to see a good amount of revenue showing up in a horizon for about 12-18 months or probably even slightly more.

These are Voice-based agents or chatbots?

Both. We've got voice and chatbots both, but if you want specific more questions, I'll have Rajiv give a little more insight in terms of ResolX as a product.

Thank you, Akash. To answer your question, these are not just voice and chatbots, but these are end -to- end workflows which are designed to provide the end resolution to the query that has been asked. It's not just a pure-play contact center play in terms of AI , but the entire customer experience space where AI is being used to personalize the conversations, personalize the journeys for the end customers and their outcomes. This is across voice, email, chat, and the workflows, which are deeply integrated into the ERP systems of our clients.

What I gather by listening to management commentary on other listed players, especially in the finance sector, NBFCs and banks, these voice agents, automated voice follow -ups and all that seems to be now industry standard . Everybody seems to be saying that it's far more efficient than agent calling up a customer. Where are you in terms of deployment of that technology?

We have actually gone far more ahead than that. What you are actually seeing in the market is just a replica of an IVR voice blaster. What they are doing is they're replacing the mundane voice of an IVR with a human-like voice and calling themselves as AI. What we are doing is that we are not just calling and making a sales pitch, but we are looking at completing the onboarding cycle, the service cycle, and then the entire value chain that happens after a customer acquisition for a product company. We are farther ahead and deeper into the AI Agentic ecosystem than just making outbound calls and behaving as a supplementary to a Voice Blaster that is happening there.

Okay. You already deployed all that. Has it resulted in any savings? Because I don't see margins going up because of that. Or does it lead to pricing pressure, and therefore, margins will remain same?

We've already deployed this. We have 12 live engagements which are going on across six enterprise clients. The overall deflection or absorption to human is close to about 30 -40% depending upon the use case where we've deployed this. On the margin side of things, Akash, if you want to throw some light, that will help.

Absolutely. As we said, we had just started inching our work on the AI side, and ResolX is gaining traction in the business today. The margins are showing up in a few of our projects, but from our larger scheme of events in terms of our revenue and numbers today, the numbers are too small to be brought out or to be noticeable in this stage of AI business.

Because from what I understood from NBFCs and banking is that this has been going on for a while and they all talk of very high efficiency, especially in things like collection - Automated calling is helping them a lot.

You're absolutely right . T here has been a lot of noise around AI. But most often than not, AI is misconstrued in terms of what is actually offered and what customers think they are buying.

That's my question - since you also run voice -based BPO, are you using that technology? That was my question. Not really on AI.

I'll invite Rajiv to speak a little more on the technology stack here.

To answer your question, yes we have the tech stack in-house available. That's what the ResolX platform is built on. The automated calling is essentially nothing but a dialer, spitting out calls to wherever you want them to basically action. We have our own in-house dialer, which is built on two PABX technologies that is available globally. That is also something that we've built in-house.

Okay. Thank you.

Thank you, sir. The next question comes from the line of Mr. Ram Prabhudas from Neem Tree Advisors. Please go ahead, sir.

Hi. Could you just tell me more about ResolX and the Resolution-as-a-Service offering?

Sure. Typically, what happens is that when large enterprises want to deploy or put something which is more advanced in nature, they end up buying a tool or an ecosystem in the market, and then that comes in as a bolt-on. What happens is that you are buying software, you are buying a product and then trying to integrate it in your ecosystem. All of this heavy lifting is typically done by the organization or the systems integrator who's there in between. Where ResolX differentiates is to exactly bridge the software-service gap, and we own the resolution end to end, which means that you are buying a product to envision and streamline the customer journey to a great extent. We are not selling you a product, but we are selling you a service that will actually help you bridge that gap so that you are able to get the end outcome. Because you can buy a product, but you may not know how to extract value out of it. We've developed this platform to multiply scale for a particular client, but we do the entire end-to-end orchestration to meet the end objective of our clients.

Have you had any recent deployments of ResolX with clients and how did they turn out?

Yes. We've deployed this across multiple clients. For the airline industry, we've deployed this to manage the entire customer services operations to a great extent, and we are deepening our deployment there to manage almost about 70-80% of the times why you would call up an airline. We are doing that already. Outside of that, we have deployed this for a marquee Italian bike manufacturer where their channel was more to just have a great customer engagement. We've actually turned that around and flipped that into a lead management system. Today, just by deploying that agentic ecosystem, their interaction channel is about generating 17-18% of their sales. We are now going to further integrate with their inventory management system so that customers can get to know whatever they are ordering and how they can kind of turn that into a revenue- generating model as well. Outside of this, we've deployed this across two Central American banks as well, where we are addressing, the peaks that are coming through because of the taxation season in terms of how to file and extract the maximum redemption from a tax standpoint. All of their queries, close to about 98% of those queries are being managed by the ResolX platform. We've also deployed this for digital signatures validation for a Central American bank, where almost about 57% of the queries are today managed by the Resol X platform. Outside of this, we have also deployed this in the insurance side of things in India, where the entire onboarding and welcome calling, including validation of what you subscribed for, is done using the platform. We are looking forward to scale this up significantly across all Indian languages and almost about 7-8 products that insurance company has. We are looking at significantly deploying these bots, we will be deploying approximately 40 -plus bots across these permutation and combinations just for the insurance company.

All right. Thank you so much. That's really interesting.

Thank you, sir. Ladies and gentlemen, if you have a question please press * and 1 on your telephone keypad. The next question is from the line of Mr. Nachiket Kale from Juggernaut Ventures. Please go ahead, sir.

Yes, hi. Good evening team. Congratulations on the excellent delivery as well as your guidance, and thanks for your opportunity. Some clarification , could you help me understand what is this 1Point1 Singapore acquisition into another entity and the whole subsidiary structure there?

Sure. I'll take this answer for you. Last year, we acquired a Singapore-based company, primarily to really set a platform for us to engage and build on our AI stack. That same AI stack, we relaunched it earlier in this year by the name Resol X. This company that we acquired in 2025 was only platform, but it did not really have stacks to really cater towards industries. We further reinvested in that along with various sets of capability and domain expertise that we had , and brought it to life. Now this was kind of a reverse engineering that we currently go to the market with. The strategy was very clear. While everybody in the market is offering AI or bot-based resolution, they are mostly dependent on third-party products with very limited control and limited ability to bring value to the customers. That's why we created this entire ecosystem to really support our own map. We are not only supporting our existing partners and businesses, we are also taking Resol X to a stage where it has been independently sold as a product in line for captive and other GCC markets as well. It enhanced our time to delivery and solutions. We always had an AI stack with us, but it required a little more platform building and other support. We found the right match to really propel this thing in the AI head, and that's where we integrated both to take the journey ahead.

Okay. Do we already have any ongoing revenues-generating business in Singapore?

No, n ot in Singapore, but we have some in Middle East. We have some businesses in Europe, some businesses in LATAM. We are also providing solutions on AI-based activities in India to multiple industries right now. While the volumes are currently very small, we are very positive and bullish that it will pick up in about 12-18 months to a sizable number.

Okay. Got it. Next question would be for Mr. Rajiv. Following our previous interaction, it's great to see the progress on the ResolX platform. Just a fundamental question as to how does the velocity of this business build over the medium term of two to three years? Because, as you say, with Resolution-as-a-Service your approach might result in a fundamental shift in the revenue generation model. Is it fair to assume that as time progresses, the platform itself will become so good that the type of queries and number of queries which will be sold and delivered will go down? How does the revenue-generating structures stay in place as efficiency improves in the future? Initially, the volume of things you get to solve will be very high. But as the process improves and once the query is solved, ideally, if it just repeats, okay. But maybe the repetition itself will stop going ahead. So what would be your opinion on that?

Sure. That's a fantastic one. I'd like to throw some light in terms of how this platform is going to evolve over a period of time, right? There are two aspects to answer this question. The first one is what happens when you have resolved a query for a particular type. Now , the reason why someone reaches out to a product company is because he's not able to self-serve. Or if he's able to self-serve, it is too tedious for him to find out how to get it done on his or her end. You have to fit the upstream and downstream both at a product level if it is a product company. Now our objective is to build around and wire the customer journey in a way that without changing your back-end systems, you are still able to provide and orchestrate the journey, which is a simpler math for anyone to do rather than trying to build the back end and try to resolve that particular defect. Whatever gets resolved using the Agentic AI platform is repetition, which means that we have already solved for it once, and we've understood the workflow. Now 100 customers, 200 customers can keep going through that journey, and it will get resolved on its own. Now in every resolution that happens using that , without having to change the back-end systems is a revenue that gets generated for us. In a large institution, changing a back end or an ERP or doing something is a mammoth task. Their existing IT teams are filled with so much work that they do not have time for advancements because they are continuously chasing on new developments that need to be done or new launches that need to be done. That is where it kind of answers itself. The second part is how we are looking at the platform to evolve. Today, what you're seeing is four enablers on the Resol X platform, and these are small pieces of the jigsaw. Eventually, what we envision to do is build this as an entire CX platform, which means right from the time of creating a requisition to onboard something, screening of that particular candidate, onboarding of that candidate, training that candidate, assess ment of that candidate, servicing of that using human in the loop, generating insights, doing quality monitoring, doing exception management, and then finally resolving it end to end using the analytics layer. That is how this platform is going to evolve over the next 12-24 months, which means that this is going to be a single platform that will help agents and Agen tic to coexist in a space where 60-70% of their task is done by Agentic. The remaining 20-30% is managed by agents in the contact center, making it a holistic ecosystem and a one-stop solution rather than taking piecemeal solutions from everywhere in the market.

Okay. Understood.

Right now, what we are doing is using these four enablers we are getting a foot in the door in terms of trying to solve for a problem that a client has. The strategy is very clear from a land -and-expand standpoint. Once you have a proven customer on p articular activity, the trust is built, and then you can expand on top of that. The biggest barrier to for a lot of companies is to have enterprise clients. Over the past two to three months, what we've been able to do is get seven large enterprise clients. Now for us, expanding that and eating away or cannibalizing over the competition, which has the larger pie of business, is going to help us clear the growth from here on. Then it is replicable because the platform is ours. The reason that we built it at a microservices level is we are using the clients to build a forward deployed engineering team for us. I have already built a center of excellence. For insurance, welcome calling onboarding, I already have built a center of ex cellence. Now all I need to do is keep on adding clients for me to duplicate and expand.

Okay. On the insurance front the governing body IRDAI has made the Bima Central platform. There was a lot of friction for the companies to get on the Bima Central platform and go paperless. Is that an ecosystem we are involved in? Because I imagine that there'll be a lot of queries. Of course, quantifiably, you can deliver a lot of outcome there.

Absolutely spot on. All our services are based on an API-led microservices layer, and this will enable us to bring it to life in terms of a paperless environment. Today, what we are doing on the welcome calling and the clearing of cases, we have superseded what a human can already deliver. In days to come, we will be able to benchmark this brilliantly. This is going to be one of the biggest use cases in the industry, especially in the insurance side, on how can Agentic AI be successful and help steer for those insurance companies.

Okay. Is it safe to assume that you are at the forefront of this and there's not much significant competition, or are there other companies involved?

You can fairly say that, and we would believe so because we are the ones who are owning the end-to-end outcome. The other companies are selling isolated modules - when you don't own anything and you provide isolated features, I don't think there are many buyers. Customers today will pay for something that provides them a solution without having to spend any effort on it. That's a sweet spot for us.

Right. Absolutely. Your customer will always be the insurance companies and not the IRDA Bima Central right?

That is correct. We can integrate directly to Bima Central as well, but that is the route we have taken . We first want to garner around the likes of large organizations that are out there. Once we've done that is when we will go one step deeper in terms of integrating with the actual ERP systems of the core systems or insurance.

Thank you. That was very insightful . Just one small question. On the ESOP front, what is the amount of ESOP to be issued, vesting period, and what's the cost which will be incurred?

In our company, ESOP policy has already uploaded on website. Vesting period is one year. We have defined some levels, after L5 level, we are issuing ESOP. Once they complete a year, they have the right to vest their option. We are issuing ESOP at the current market price, not at a discount. If you talk about the costing part, then cost to company is zero.

Okay. Thank you so much for the answers. I'll get back to you. Thanks.

Thank you, sir. The next question comes from the line of Mr. Arjun Tambe from Aurrevia Crest . Please go ahead, sir.

Yeah. Most of my questions have been answered. Thank you for that. I just wanted to know the blended cost of debt for the company. What plans does the company have to deleverage the books?

If you talk about the debt, our company is actually debt-free. We have only taken exposure of debt in acquisition of Netcom, and their effective cost of around 9%. As Akash sir explained earlier, our company has a strong cash flow position, and we have planned out our debt repayment schedule.

All right. What are the current active deal pipeline for 2027? What is our conversion rate for that?

I'll take that, Sunil. Currently, we are hovering around a good 10-12% of our conversion. We have an active pipeline across all cohorts. We are doing and pursuing deals across LATAM America, North America, India, and with growing numbers with Netcom.

All right. Just one more question, if I may. When we are evaluating a prospective acquisition target, what key metrics drive your decision-making?

We are first look making sure that our target company is EPS accretive. Secondly, we are looking at right now North America as a market, so we need someone who has got customers that can really enhance and really move us in the North America region.

All right. Just a follow -up on that. On average, how many quarters do you anticipate it will take for the new acquired entity to become margin incrementally accretive?

It's already there from day one. It has already started showing up.

Okay. Thank you so much.

Thank you.

Thank you, sir. Ladies and gentlemen, if you have any questions, please press *and 1 on your telephone keypad. The next question comes from the line of Mr. Malay Sameer from Breakthroughs. Please go ahead, sir.

Thank you for letting me ask a question. My first question is what is the entry barrier for competition to come up to a level and start matching our service levels?

Hi, Akash. I'll take that question. Today, what we are doing is we are owning the client end to end. Today, if you talk about any other company, they offer bits and pieces of a service. For a BPO who's out there, they are providing manpower to the client. Then they are taking AI or AI as a platform from a different service provider. Then they have to integrate. They have to own the resolution. If there is an SI or a tech stack that needs to be put in, they will bring in a third vendor to make this happen. In this entire journey of what they are trying to do, there are so many stomachs to feed, and it becomes impossible for them to kind of, one, meet the rates, second, the quality and own the entire end -to-end outcome for the client. So that becomes as the biggest barrier from a competition standpoint. Today, we are a one -stop shop for providing end -to-end resolution across manpower, AI and technology stack across domains where we have a presence . That is our strongest point and the entry barrier to a lot of customers because you will have multiple necks to choke if something needs to be done in coordination and collaboration. That is where we kind of come in very handy to our clients in terms of owning it end to end.

I greatly appreciate that. Now the second question is, are we the only one giving this service in India? Are we the best who's offering this kind of service in this domain?

As per what I last remember, none of the BPOs have their own Agentic AI tech stack. They are still trying to build it on their own or taking these services from a third -party outsourced vendor who's providing these services. Today, I can say that we are the only ones who exist in India who have the domain plus tech stack plus Agentic AI capabilities, which is truly born within the organization.

All right. Obviously, you've shared before as well that from the headcount hours to the resolution, it's a very good vector to shift to, and I accept that. My question is how do you monetize it? Because when you are just counting headcounts and the hours, it's very simple to make the math work. But when you talk of resolution, it goes into a subjective domain. How do you monetize it?

It's a bit complicated when you think of it, but it's also very simple. Say, for example, what is the cost of resolution to get a query addressed? Is someone trying to get an answer over a chat, so you consume some time on chat? The query did not get resolved on the chat. You had to move to a different channel. The same customer went ahead and made a phone call to a contact center to get a resolution. You need to add what time was spent on the chat and the te ch stack to kind of bring it to life, plus the time that it was spent on the telephone and the agent cost to kind of do it end to end. That gives us a cost of current resolution for the time. Today, what happens is that if I have Agentic AI deployed on chat, I own the end-to-end outcome, which means the 5-minute conversation can become a 2-minute conversation because I'm not shifting him from one channel to another channel. It is still time and motion driven, but the way you calculate it is what makes things look differently.

Okay. I understand. Now suppose we are catering to the airline industry and then we move into a new industry, say, hotels. What is the kind of investments and effort that will go into flipping or rather adding hotels to your base?

Sure. Today, our deployed engineering team, which means a domain expert, is only deployed when I have it at the back of a client. Because we've been in this business for over a decade and we've been servicing these industries, we understand each of these domains at the back of our hand because we are managing almost 85-95% of an operations for a client. We understand the domain. We understand the workflows. We understand what the breakage points are and how do we own it end to end. Today, if I have aviation as a sector where I have deployed this, I also understand how it operates. But if you take a sector like insurance, do I invest in a person or a team who studies insurance end to end, and then look out for clients outside in the market? The answer is no. I draw parallels of what I have been able to deliver here and see what best proposition can I create for an insurance company? After I have won the client, I will go and deploy an expert, or we already have the expertise in house to kind of go and deploy that model. That becomes a huge differentiator for us because o ur R&D cost now subsequently reduces. Otherwise, you are keeping on building products without having a revenue coming on top of that, if I was able to answer.

Yes. Thank you. Now as we keep learning from our AI models for a particular industry, say for aviation as you said, and if you get another airline in the same industry, then your learnings would come very handy, and you could very easily ramp up the business, without too much of an investment into it.

Partially correct. I'll tell you why is it partially correct because what happens is that workflows are replicable, which means the customer journey of an airline is not going to change, right? When you book a ticket, you have journey. You have a refund journey. You have a web check -in journey. The workflows are completely end to end. Second, we are not in the business of creating LLMs, which is your Large Language Models. What we are in the business is on what sits on top of an LLM. Today, LLMs are commoditized. But what sits on top of an LLM is what we come as differentiator now. The model can differentiate from a journey perspective - what LLM, SLM to use, they are already optimized for what we want to use, and we already know what was best in which scenario. Hence, the replication becomes fairly simple for us. But we are not in the business of learning from our clients' data. We would not want to do that because that's complete conflict of interest. It's an IP of a particular client, which should remain as encrypted as secured for them.

I appreciate that. And my last question. Can you give us a ny color on how soon will you ramp up within the industry that you are already catering to in the next three quarters?

Once we've deployed a center of excellence, we obviously want to market it more. We want to create use cases around it, and we are constantly creating case studies to kind of garner around same industry, same clients. We've got insurance. We had one. We got the second one right after that. Now we are looking at expanding our horizon within lines of businesses within that insurance company. Once we've done that and once we've had the sizable numbers, I think it becomes fairly easy because the proof of the pudding already exists. We have results that are already out there that talk about our capability and capacity to kind of expand. Once we've acquired a client, now, obviously, there are limited number of airlines that operate in the country, but we are taking that offering not just on the domestic market, but also to the international side of things right now. Similarly, for insurance, there's a huge population that we need to cater within the Indian boundaries itself. Anywhere between three odd quarters or maybe two and a half quarters is when we should be able to kind of get the next one in. But there is enough and more work once you land into an enterprise client to kind of keep evolving your service lines.

There's only just one passing thought, which I want to touch upon. If business ramps up rather quickly, would you run out of capacity? If you do that, would you just need to hire some humans while your software and Agentic AI continues to stay afloat? Or would you need to ramp up that as well?

I think at the back of a business, scaling up is never an issue. I don't think we'll be running out of capacity. What we are trying to do is we are trying to create more space or more room in an account by adding more Agentic AI into the ecosystem so that the Pareto still applies. 80% of the queries are generated by 20% of the people and stuff like that. We are trying to scale up that capacity on Agentic AI, which creates room for adding more work, will require human intervention for complex sort of environments.

Thank you so much. All the best.

Thank you so much, sir. There are no further questions. Now I hand over the floor to the management for closing comments.

Thank you, everybody, for your time and attention, and we'll see you soon in the coming quarter results. Thanks a ton. Thank you.

Thank you, sir. Ladies and gentlemen, this concludes your conference for today on behalf of 1Point1 Solutions Limited. We thank you for your participation. You may disconnect your lines now. Thank you, and have a pleasant evening. Note - This document has been edited to improve readability