Ladies and gentlemen, good day, and welcome to the NIIT Limited Q1 FY 2027 earnings conference call. As a reminder, all participant lines will be in the listen-only mode, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during this conference call, please signal an operator by pressing star then zero on your touch-tone phone. Please note that this conference is being recorded. I now hand the conference over to Mr. Vijay Thadani, Vice Chairman and Managing Director of NIIT Limited. Thank you, and over to you, sir.
Thank you. Good afternoon. Actually, good evening, and welcome to NIIT Limited's quarter one FY 2027 earnings call. As usual, we thank you for your interest in NIIT Limited as well as the time that you're spending today with us amongst, in the middle of a busy result season and for joining the call and giving us your support and suggestions. Today's agenda is to discuss with you the quarter one FY 2027 performance highlights. Second, what is shaping FY 2027 and the actions that we are taking, our priorities, and outlook. I'm happy to share with you as a start that we are starting off FY 2027 on a strong note, definitely stronger than the same period last year, and I think it is increasingly becoming stronger as we go forward, w ith both enterprise as well as consumer go-to-market engines showing growth in quarter one.
While technology continued to grow well from AI-led investments in skilling, we also have growth from banking, financial services, and others. Order intake continued to remain strong, vindicating our investments in the new AI programs as well as our go-to-market initiatives. On the profitability front, our EBITDA is moving in the right direction with our operating costs growing slower than our revenue. Just to remind that certain parts of the business have been in an investment cycle, and in quarter one, those investments are normally higher than other quarters. With that, I'll hand you over to Pankaj Jathar, our CEO, to take you through the quarter one performance in detail, and then we'll open it up for question and answer. Pankaj.
Thank you, Vijay, and good afternoon, everyone. I will cover the Q1 performance first, the revenue order intake and business trends, and then step back to talk about our priorities for the rest of FY 2027. Note that our business has seasonality, so we look at year-on-year trends rather than quarter-on-quarter. Revenue for Q1 FY 2027 came in at INR 957 million, which is up 14% year-on-year. Within that, enterprise revenue was at INR 618 million, which is up 8% year-on-year. This was driven by Enterprise Tech training, which grew 16% year-on-year to INR 498 million, which was as an outcome of our strategy to focus on upskilling and reskilling lateral job roles even as fresher onboarding and training remained volatile.
On the consumer side, the consumer revenue was at INR 339 million, which was up 27% year-on-year. Within that, consumer tech continued to see momentum, growing 15% year-on-year to INR 182 million. Our direct-to-college strategy is creating a pipeline of job-ready talent, which university clients are increasingly valuing. The recovery that we see in consumer business from BFSI and others in Q4 saw further pickup in volumes in Q1 as fresher hiring picked up pace at partner banks. The strong growth in the consumer business has led to a shift in the enterprise-to-consumer revenue mix from 68: 32 in the same period last year to 65: 35 in Q1 this year. Viewed from a product lens, technology continued to grow well, clocking revenue of INR 680 million, up 16% year-on-year.
Revenue from BFSI and other programs was at INR 277 million, which is up 9% year-on-year, driven by strong fresher hiring, even as lateral training continued to be under pressure. Order intake in Q1 was at INR 953 million. I now invite Sanjeev, our Chief Financial Officer, to provide an update on the financials. Over to you, Sanjeev.
Thanks, Pankaj. While I take you through our financial results. EBITDA for Q1 was negative at INR 14 million. This is a significant improvement from the - INR 63 million in Q1 of last year. This is driven by improved productivity and operating leverage while we continue to invest in GTM capacity and new AI offerings. As Vijay mentioned in his opening remarks, while our new top line grew by 16%, our operating expenses grew 7%, putting us back on the path to positive EBITDA margin. Below EBITDA, depreciation was at INR 96 million in Q1. Net other income was INR 180 million. This is primarily comprising of treasury income of INR 125 million and other miscellaneous income of INR 24 million.
That is offset by net finance cost of INR 3 million, and t here are some exceptional expenses of INR 15 million, primarily because of the legacy tax matter that has now been concluded in NIIT's favor . Some part of the cost is pertaining to the scheme of arrangement for amalgamation of RPS and IFBI into NIIT Limited. This resulted in a PAT of INR 81 million for the quarter, which is up 85% YoY, and EPS of INR 0.60, that is up 84% on YoY basis. Coming to balance sheet and cash flows. Cash and cash equivalents remain strong at INR 7,231 million, underpinning our ability to invest through the cycle. CapEx was INR 68 million for the quarter. We are past the peak on capital investment in platform in the current investment cycle, and we expect capital expenditure to moderate from here.
DSO was at 53 days in Q1, which is same as last quarter. Employee count at the end of Q1 was 866, which is down 65 on QoQ basis, and 19 number of people on YoY basis. Now, back to Pankaj.
Thank you, Sanjeev. Let me talk about what we are doing right now and through the rest of FY 2027. We will be accelerating what is working. On the tech training front, AI and new logos is working. We are continuing to scale AI programs and workflow offerings, which showed strong growth in FY 2026, and that's where we see demand signals being the healthiest. We are continuing to expand coverage of GCCs and India enterprise companies and positioning reskilling around role evolution, particularly AI-enabled role redesign through outcome-led programs. On the BFSI side, we have been recovering. That's the plan. Our strategy of diversifying beyond the top four private banks to a broader set of financial service players, including NBFCs and insurance companies, is progressing well. In Q1 FY 2027, NIIT moved beyond its banking anchor to activate four new solution lines across insurance, NBFC, wealth, and GenAI. These are not pilots.
These are live commercial engagements with more than 15 clients outside of traditional bank induction kind of programs, which is generating new revenue for us. As we accelerate this transformation, we hope to further reduce concentration risk and drive growth through the cycles. In terms of the road ahead, our investment thesis is showing up in new logos, digital engagement, order intake, and a pipeline that's being chased. We are seeing improved consumption of our differentiated outcome-oriented offerings across the technology landscape, with working professionals and job seekers both contributing to growth. In BFSI, the picture is two-speed right now. Onboarding demands showing early signs of recovery while upskilling and L&D budgets at large private banks remain constrained. We are positioned to capture the onboarding recovery and are actively broadening the customer base and shifting the program mix to be less dependent on L&D cycles of any individual customer.
With merger of RPS Consulting and IFBI into NIIT, we have strengthened our offerings to address the reskilling and retooling agenda, including deep transformative programs for existing talent. The AI opportunity. AI represents one of the most significant demand opportunities in front of us, and it is happening now, not at some point in the future. AI is now embedded across a larger share of our portfolio, and revenue from AI programs has grown 9% of total revenue. Our AI story is becoming sharply defined, and nowhere is this more visible than in our work with GSIs and GCCs. AI-augmented engineering teams are already running 40%-70% smaller than their conventional equivalents. One engagement we are aware of compressed a planned 150-person team down to 42.
Across GSIs broadly, analysis suggests that more than half of current task content roles face displacement over the next 36 months in ways that have already begun. GSIs and GCCs are positioning themselves as the change agents for their clients' AI transformation. The transformation they are driving externally will need to be mirrored internally. A number of current roles are becoming redundant and must transition into new AI-era ones, and that creates a three-part talent opportunity for us. Reskilling existing employees whose roles are evolving, retooling staff displaced by productivity gains into new AI-era roles, and onboarding new early career talent into roles that require accelerated outcome-based programs rather than traditional induction. In-house L&D teams will struggle to scale at the pace this transformation demands, and the existing response, internal AI academies built around course completion and certification, is structurally inadequate. Training is moving from skilling to capability orchestration.
Completion rates do not prove judgment under uncertainty, AI output verification, or agentic workflow design. That is precisely the opportunity for NIIT. During the quarter, we deepened our AI curriculum with the launch of training programs for forward-deployed engineers, site reliability engineers, AI auditors, and also the AI Prism. These complement our established offerings in AI engineering and agentic AI, and together, they address the full life cycle of enterprise AI adoption, building, deploying, operating, and governing AI solutions at scale. What distinguishes these programs is their design philosophy. Applied use case-led learning journeys built around higher value AI-augmented roles that enterprises are actively hiring and upskilling for. Beyond broad AI fluency and GenAI capability building, we are now winning specific need-based client engagements covering AI economics, CapEx planning, token optimization, and AI audit, a reas where the demand signal is sharp and client willingness to invest is high.
A structurally similar dynamic is playing out across BFSI and India enterprise companies, and our AI programs are well-positioned to serve that opportunity. On the early career side, iamneo directly addresses the onboarding opportunities. Through its university partnerships and college to corporate bridge, iamneo enables early career talents to take on roles that previously required years of experience. Our Synthetic Work platform and the Architect on Graduation product are purpose-built for exactly this transition. Let me quickly take you through the guidance for Q2 FY 2027. We expect double-digit revenue growth year-on-year in Q2 FY 2027. On margins, we expect near breakeven at the EBITDA level in Q2, positioning us for positive margins in the second half of the year. We expect stronger revenue growth, improving margin, and continued order intake momentum for FY 2027 as compared to FY 2026.
Medium to long term, the structural opportunity in skilling remains substantial, and we are fully committed to our strategic objectives. With that, Vijay, I hand it back to you.
Thank you, Pankaj. Just summarizing, we have started the FY 2027 with a robust growth, a strong order book, broader customer base, and a clear sense of what and where are we winning. We are responding to the areas of pressure by widening the demand base, accelerating the parts of the portfolio that are working, especially technology and AI, and maintaining cost discipline while continuing targeted investments. Our investment cycle continues, however, o ur focus has more become on AI and AI programs and usage of AI in every program that we are serving our customers with. What gives us confidence is that the portfolio is becoming more resilient, strengthening of our product portfolio for working professionals, rollout of new AI programs, go-to-market expansion, and the iamneo initiative are all showing early results.
We remain confident of the longer-term structural growth opportunity and are committed to making the investments needed to capture that opportunity. In addition to investing in new programs and stronger go-to-market initiatives, we continue to follow a disciplined approach to evaluating inorganic opportunities that enhance capabilities, channels, and/or intellectual property, and which offer a clear path to returns and cash return. I want to pause here and open this line for questions, and then we can take the discussion forward. Operator?
Thank you very much. We will now begin with the question-and-answer session. Anyone who wishes to ask a question may press star and then one on their touch-tone telephone. If you wish to remove yourself from the question queue, you may press star and then two. Participants, you are requested to use handsets while asking a question. Ladies and gentlemen, we will wait for a moment while the question queue assembles. A reminder to all, you may press star and then one to ask a question. We have the first question from the line of Harsh Yadav from Dolat Capital Market Private Limited. Please go ahead.
Hi. A very good evening to you. Am I audible?
Sorry to interrupt, Harsh. You're not audible. Please use your handset for the speak.
Hi. A very good evening to you. Am I audible now?
Yes.
You're audible.
Very audible.
Yeah.
All right. My first question is, basically, in the presentation, you highlighted that AI-led programs now contribute about 9% of overall revenue. Given that enterprise clients are compressing the traditional team sizes, how are pricing realizations and ARPU trending for AI-led capability building compared to legacy IT training?
You said first question. Is there another question? Then, you can ask.
Yes, there are a few more questions I have.
Why don't you answer one?
Okay, let me answer this one.
All right. Yeah.
The direction you're hinting at is true. AI-led training does have a higher realization than traditional training. But batch sizes will tend to be smaller for AI-led training than the more traditional training, e specially for some of the advanced concepts like agentic AI, et cetera. Th ere is a going-in requirement of knowing how to code, knowing Python, so those e ntry criteria need to be met. So, the average realization will be higher but typically batch sizes would end up being a little smaller.
Okay. My next question is, consumer posted a robust growth of 27% year-over-year, even though your total enrollment saw a quarter-over-quarter dip by around 150,000. Could you provide some color on the split between early career and work pro learners this quarter?
Sure. We used to track early career work pro, but those lines have become so fuzzy that w hen we are talking of consumer, consumers also have work pros built into them. So, we are not, at this point of time, breaking that. Sufficient to say that the early career part, if we were to take iamneo's offerings, for example, they service a large number of universities, and those will fall in the early career part of the business, and I think that part has done well. Overall, the mix in early career is increasing, but not.
Okay.
At the level at which we would have expected, given that the hiring is very, very muted.
Yeah. Just to follow up on that, as we have seen that top five IT services firms continue to curtail their freshers hiring, so w ithin consumer, has growth primarily been driven by experienced working professionals that are upskilling in AI? Also, I just wanted to know how StackRoute and TPaaS are performing in this environment.
Sorry, I heard the first part, which I'll answer. The second part I'll ask you to repeat, if you don't mind.
Okay.
Now, let me further subdivide early career into two parts. One is freshers and the other is two to four years experience. Early careers actually includes the two to three years experience, and not four. Two to three. We do zero to three. Yeah, two to three years experience. I think that segment, because people are reskilling themselves, like our agentic AI programs. For example, the pull for those is higher because the current people who have been hired or are working in organizations need to reskill themselves very quickly, A, to retain their jobs and B, to find growth opportunities. I think that's where the real push is. The freshers is largely driven by the onboarding requirement of corporate, which has not started yet.
But then, when we look at IT hiring, we look at the top 10 or top 20 IT services companies, but there are a large number of startups and other companies which are also in the hiring game, and GCCs, w here the numbers are not individually at very large level, but there are very large number of companies. So, I think there is a momentum which is building up there.
Okay. All right. My second part of this question was actually, I just wanted to know how StackRoute and TPaaS are performing in this environment.
Okay. I think, maybe Pankaj would like to talk about all those terminologies have now got changed.
Okay.
After we merged RPS and IFBI into NIIT. So, he is now giving you the numbers. Numbers are still the same, but I think that the businesses have got combined, simplified, and I think that's also reflective in how we have managed our costs. But maybe, Pankaj, you talk about bits and RPS.
Yeah. So, we've combined RPS and the StackRoute entities, and we call that the Enterprise Technology Learning Solutions. That is the Enterprise Tech that I spoke about.
They are both now housed under NIIT, and therefore, you don't have those available separately.
Yeah. We've actually integrated those teams, so it's not that we can separate out either. It's actually integrated into one team.
Okay.
To answer your question on how they're performing in this environment, they are performing very well. We are seeing the robust growth on the tech side. The numbers that I spoke of as Enterprise Tech is actually those two teams combined together, and a few other tiny contributions. But that's the number.
All right.
So, the business performs actually well. The other side is where we've combined our banking, TPaaS, and s ervice and excellence training, all that into BFSI and industry performance solutions, so IPS as acronym. That has also performed well in this quarter. So, both these significant components of our business have performed well in the quarter gone by.
Okay. I just have a very qualitative question. Just wanted to shoot it. I've been noticing with the advent of a lot of IIT and IIM offerings with respect to online certifications, degree programs, especially in this AI agentic applications, FDE, et cetera, so h ow do we position ourselves in this environment, and what are we doing to create like an edge in terms of program structure or an implementation point of view with these upcoming courses and programs from so many different educational institutions within the country and also outside, especially targeted to working professionals?
You want to answer that?
Yeah. I will. Just give me one second to pull together exactly what he asked for. So, you are right, there is a lot of different programs that are coming in, which makes it difficult for a customer to actually understand what they're getting for, right? You have programs which promise agentic AI training from 10 hours up to 600 hours, and therefore, a customer will find it difficult to compare those two things and understand what they should get into. What we are doing is, of course, trying to provide as much information as we can on the consumer side. On the corporate side, of course, there are differentiators that we bring to the table, especially outcome orientation, right? One of the things that we talk to customers about on the enterprise side of the business is on delivering outcomes through our training programs rather than completion, right?
Therefore, it's not that we will just track how many attended, how many completed. We will work with customers to track outcomes of the programs we deliver. Those are the areas that we are able to differentiate how we provide this training. But you are right, it is becoming a very competitive market, and p eople are using buzzwords like FDE, et cetera, to bring new offerings, and it's up to us to keep educating our customers and providing the differentiation we need to.
Okay. Thank you.
Let me add one line. I think we at least believe that in the new world that we are in, it is the capability which counts rather than the credential. We are not running after credentials. We are running after building capability, and I think that success is very visible in our enterprise offering. Our enterprise offerings are showing a clear differentiation because we are able to demonstrate outcomes in terms of capability, which leads to productivity and effectiveness of the workforce. So, people are preferring that rather than allowing a credential program, rather than adopting a credential-based program. On the consumer side, that awareness is not yet there. But wherever we have access, we would like to focus on that part, because I think the long term lies not in credentialing, but in building capability, which can be demonstrated. And employers will now hire for capability and not the credential.
Yeah. Okay. I agree, actually. Thank you so very much. These were my questions. Yeah.
Thank you very much.
Thank you. We will take the next question from the line of Aman Prakash, an individual investor. Please go ahead.
Hi. Thank you for taking my question. My question is to Pankaj. You mentioned about outcome-based learning, right? I want to understand more about this, because you're right, you know that, I mean, if you use AI, it is in the end, the outcome that counts, right? If you take this into account, then the umbrella of opportunity is far bigger. It is not just IT companies, right? Eventually, it might percolate down to like other sectors as well. So, I want to know more about how you're going about this outcome-based learning right now, and what are the plans for the future? Thank you.
Aman, actually, forever, NIIT's been talking about delivering outcomes through learning, right? It's not just now in the AI era that we are talking about outcome-based learning. We've always believed that there's no point in doing a learning program unless we are able to deliver and demonstrate that outcome. That belief continues in how we approach training, and we build a fit-for-usage kind of training program. So, depending on who it is and what it is being made for, we create training programs that will deliver specific outcomes. We are working across the organization, right? At the entry level, we deliver boot camp-oriented programs to help new joiners become productive from day one. We deliver that count as an outcome. At the more senior level, we deliver architecture programs which help seasoned architects become even better at their job, at managing large teams and delivering outcomes.
We also do some leadership training programs where the final outcome is a change in behavior. The way we do this is by tracking before and after training-related metrics and working with our customers to track the outcomes of our training. Vijay, is there something you want to add?
I guess outcome depends, as Pankaj rightly pointed out, o utcome depends on what is the outcome that you came for. We are firm believers of the fact that getting a job is not the problem. Getting the job is the real challenge. When people join a course, they're not joining it for a job. A job you can get, but the job which is consistent with the investment that you made in that course, and that, you will get only if you demonstrate that capability in terms of being able to do and create a live application. I think there are enough and more ways by which employers test you for whether you have that capability, hackathon being one of them. Hackathons is becoming a very, very standard way by which people hire, especially tech professionals.
So, if you are able to build and solve that problem that is given in the hackathon, then you have a reason. I'm giving you that as an example. An agentic AI, for example, program, a person who's doing, he may have an agent or a bunch of agents that he has to create to solve a workflow problem in his organization. In which case, was he able to do that? In this program, by the end of the program, you could actually have an early part or an early version of that agent ready for deployment. I think that is not something which any credential-based program typically offers.
Okay. All right. Thank you for the response. Just one last question regarding this outcome-based, right? One is the outcome at the personal or the individual level, right? But we see in India a lot of these legacy companies, right, which eventually will have to or will move towards AI. So then, there is, because a big part of our business, I think it's more than 60% is now B2B enterprise level, so i s there a thing, let's say, an organization approaches NIIT and then the outcome-based AI, like, how do you say, learning or the transformation can happen, anything of that sort, like, is going on or is it in the pipeline?
I gave you some examples of an early career person, but in organizations who are deploying, for example, GSIs or GCCs, they have specific initiatives happening where their people have to be billable. How long are the people billable after they join that organization is an outcome that is very important to them. We would like them to be billable in day one, R1. If we are able to deliver that, then the organization would prefer that. I think that's also an example. How do their realizations improve? How do their deliverables improve? Although, actually in an enterprise program, in a running enterprise, when you introduce AI, outcomes are more easily definable.
Okay. Yeah. Correct. Thank you. That's all from my side, and all the best.
Thank you.
Thank you, Aman.
Thank you. Before we take the next question, a reminder to all the participants, you may press star and one to ask a question. We have the next question from the line of Ganesh Shetty, an individual investor. Please go ahead.
Good evening, sir, and thank you very much for taking my question. My question is regarding integration of StackRoute, NIIT enterprise business, and also, RPS Consulting. After this integration of these businesses, whether we have fine-tuned our go-to market strategy and whether this will also result in easier processes for the company and market improvement, c an you please throw some light on this, sir?
Sure. Thanks, Ganesh, for taking the time to join the conference and for the question. In one word, yes. Integrating StackRoute and RPS together improves our go-to market. They are both very complementary offerings in many ways. One used to do OEM-specific training, the other builds long-term solutions for customers based on what they want specifically. Both of those are complementary offerings, and that makes our go-to market that much stronger. They also had a reasonably complementary customer basis. One was GSI heavy, the other GCC heavy. That also helps us build a stronger market presence for that business. Definitely, the integration has improved our ability to go to market with their offerings. In terms of easier process, et cetera, that's an ongoing work that we've been doing, which is to simplify parts of the organization and simplify things on how we work.
Yes, this integration of course helps us simplify some of those things, but it's an ongoing NIIT-wide initiative anyway that we are working on to improve our ways of working and simplifying things. I hope that answers your question.
Yeah.
Net-net, I think, yeah, what Pankaj is trying to say is that the combination has got integrated in the last few months, right? Even though, o fficially, it has happened from 1st of July, but it has been in the works before that. I think the combination has got going, as you can see from the Enterprise Tech results also, and I think we'll see more efficiency and better performance as we go forward. Obviously, the tailwind of the environment is also helping.
Yeah. My second question is a continuation of earlier respondent. We are now serving mostly BFSI and technology sector, and as AI is now entering all the sectors and is a part of national progress, are we targeting any other sectors for giving them AI-related training, or we are preparing ourselves to market ourselves as an AI leader in training to access other sectors, auto or anything like that, industrial, where we can showcase our AI capabilities and make them AI-based or AI competent? Can you throw some light on this, sir?
Sure, Ganesh. We are actually already recognized as a leader in AI training. While, yes, you're right, the largest part of our business comes from these two areas, but we are working with customers in the auto, telecom, India enterprise side, and some of the work we are doing also involves AI. In fact, we've developed some interesting new AI-based tools, which we are deploying with some of the customers from these industries and helping them improve their capability on sales, on service, et cetera. We are working with customers beyond these two sectors as well, and specifically with AI as the main thrust of our offering in these areas.
Okay, sir. My third question is regarding the opportunity in university sector. There are hundreds of universities, deemed universities in India, but they are lacking, I think, AI compatibility. We are having iamneo as a special division where we can easily collaborate with institutions or universities, apart from placement services for giving them content for AI training for in-house capability. Are we trying for these types of businesses right now? Is there anything like that in our pipeline, sir?
Iamneo is focused on universities business, and they will continue to expand in that area, and w e will build our presence through the iamneo go-to-market that we have. AI is, of course, a large part of iamneo's tool set as well. They launched a couple of new offerings in the last quarter, which are very AI-centric for the university segment, and we are seeing good traction from that also. Vijay, anything you want to add to that for the university segment?
No, I think, yes, you are absolutely right. The universities are very hungry to add AI in their curriculum. However, I think different universities have different level of commitment for that. The solution that we are offering from iamneo is a very, very superior solution and would be suitable only for maybe top 500 or so. Then, we are looking at solutions which the other universities would like to have. For example, engineering colleges, the level of AI solutions that they need are very different, or curriculum that they need is very different from what, let's say, a commerce or a liberal arts university would look at, or a science university would look at. I think defining a curriculum which is for each segment is the next issue. AI is not a magic wand by itself. AI has to be used in specific situation, in a specific manner for best results, and that's what I think our focus is.
Sir, can I ask one more question, if time permits?
Sure. Yes, Ganesh.
The macro has been very challenging for last entire year, coming back to our own business, whether we can see that whether the macros have improved from the last quarter or it has deteriorated this quarter, or whether we are in a same mode and there is no improvement in macros and the business is as is, sir? That's all from me, sir. Thank you very much.
Sir, I think you understand macros better than we do. We all get swayed by the macros, by statements of one leader or the other, and by some actions. I think the situation, in fact, I would tend to feel the situation remains the same. There are days when it looks about to be very, very brighten up a lot, but there are days when it just goes back to, and n owadays, the current days that we are going through are not pointing in the right direction. I think we have to look at the opportunities ahead of us rather than we get concerned by the macros a lot. Of course, we have to be conscious of that.
For us, the AI opportunity and the role that AI has to play in education, AI has to play in the fundamental business of some of the organizations, is an opportunity which will exist irrespective of the macros. We are focused on that, and I think that is delivering us results. There are parts of the business which are very dependent on how environment works. We will remain open to that. How do we just spread our risk that we do not get caught in any one particular direction is, I think, the challenge that we are all working on. We are also opening doors for newer segments that we have not serviced, and we are also looking at inorganic growth, which I mentioned already.
Thank you very much, sir, and all the best. Thank you.
Thank you.
Thank you very much. Ladies and gentlemen, that was the last question, and w ith that, concludes the question-and-answer session. I now hand the conference back to the management for the closing comments. Thank you, and over to you, sir.
Okay. Thank you very much for joining us this afternoon or this evening for this session. This is the first time we have switched to the timing of the call to be such. We would love to receive your feedback on how you found it in terms of convenience and, of course, on content. Your questions always educate us and open new windows or doors in our mind of the opportunities ahead of us. We remain grateful to you for giving us your time, for your support, and for your guidance from time to time. Thank you very much and wishing you the best.
Thank you, members of the management. On behalf of NIIT Limited, we conclude this conference. Thank you everyone for joining with us today, and you may now disconnect your lines. Thank you.
Thank you.