Thank you, and good afternoon, everyone, and welcome to the Q4 and FY26 earnings call of E2E Networks Limited. We have on the call Mr.

Tarun Dua, Managing Director of E2E Networks, and Mr. Nitin Jain, CFO of E2E Networks.

We must remind you that the discussion in today's call may include certain forward-looking statements and must be, therefore, viewed in conjunction with the risk that the company may face. I will now request Mr.

Tarun to take us through the financial and business updates, subsequent to which we can open the floor for Q&A. Thank you, and over to you, sir.

Hi, everyone. Hi to all our team members, all our investors, and we hope that you have had a good last financial year.

I'll do a brief coverage of all the progress we have made during the last quarter and last year, and then I will hand it over to Nitin to talk about the financial highlights for this quarter and the overall year, and then we'll open the floor for questions. In this year, we have a lot of milestones as a company that as a team we have achieved.

We have been able to use our TIR platform for large-scale GPU clusters, and we have helped LLM teams operate training on large clusters over the TIR platform. With this, we have demonstrated a full-stack capability of operating both bare-metal and container-based large-scale deployments for NVIDIA-powered GPU infrastructure at a bigger scale.

We have not only demonstrated that we have the ability to operate the infrastructure, but also successfully monetized the infrastructure at a much larger scale than we had proven last year. This is a testament to the strengthening of our technology and talent, which has been used to build very deep in-house capabilities across the entire five layers of the stack.

We have done major software improvements to improve the reliability, performance, and scalability of our GPU infrastructure in the last many quarters. Going forward, we feel that we have been saying this a lot that the future is all AI, this is a decadal story.

Now, given how the market all across the world are reacting to the AI infrastructure usage being increased very, very drastically. I think we have been validated in kind of putting up speculative GPU infrastructure.

Where the world is divided between haves and have-nots, we are the haves in terms of having access to speculative GPU capacity where the capacity is running out everywhere. That allows us to kind of continue our growth.

With regard to where we see medium-term and long-term kind of growing in terms of the world shifting to GPUs from the CPUs, from rule-driven software to AI-driven software, we continue to explore how we can build more infrastructure under our management. Where we have explored equity, where we have explored debt, now we are also exploring a variety of private credit, asset-light models to kind of bring in rapid expansion to our GPU capabilities.

We have consistently met the industry benchmarks for performance for inference or training or GPU deployments under our management. We expect our Cluster 1 B200 1024 to go live somewhere in the mid-May.

In a couple of months, we are expecting to kind of be able to deploy another cluster of 1024. This has already been planned.

Then we are very strongly positioned to capture significant uptick in the Blackwell generation of GPUs, apart from continuing to run very, very strongly on the Hopper generation. Apart from this, we continue to build a plan around B300, GB300, and Vera Rubin deployments.

We will continue to keep increasing the GPUs under our management and under our direct deployment both through partnerships, through direct acquisition, and by exploring various financing models that can help us secure more GPUs. We continue to focus on that.

We continue to focus on our end-to-end project management capabilities to deliver AI infrastructure to AI services and AI product companies, AI digital natives, enterprises in the BFSI and other sectors. We'll continue to work towards that.

Okay. I think that pretty much covers it.

This has been a good year and a good quarter. Pretty much our strategy has been validated over last many quarters, where we significantly continue to add to our technology heft in terms of having deep-tech talent in-house to be able to do stuff.

We gave a certain guidance in terms of where we would be by the end of this quarter, a couple of quarters back. I think we have more or less met and achieved that target, and we hope to continue to do better in the future.

Given that the market is growing very, very positively and it's a broad trend, there can be again, like we have mentioned in the past, that there are crests and troughs, but ultimately, this is a market where the GPU utilization is going up, the demand for tokens is through the roof, India being a country of more than a billion people on phones. Of course, even if they were not on the phone, there is a inherent ability to treat every possible piece of information that is going in and out of people, in and out of machines, in and out of enterprise systems to be described in the form of tokens.

Tokens can be representing voice, text, any other form of data, whether invisible spectrum, inaudible spectrum, audible voice, inaudible sound waves, ultrasound or whatever. Everything is tokenized data for AI, and I think India as a country generates a lot of data.

We continue to believe very, very strongly in the long-term India story of AI factories being built here and India becoming the AI factory of the world. Now, with that, I would like to kind of hand over for more numbers-driven financial highlights talk to Nitin, and then we'll open it up for question and answers.

Nitin, over to you.

Thank you, Tarun. Good evening, everyone.

Thank you for joining us today. I will walk you through our financial performance for the fourth quarter and full-year for FY26.

Q4 FY26 again witnessed a good quarter for E2E Networks. We have demonstrated our ability to scale AI infrastructure rapidly, achieve high utilization across GPU clusters, and convert capacity into strong revenue growth.

Most importantly, we have been able to drive our EBITDA margin in Q4. Let me start with the quarterly highlights for the Q4.

Revenue stood at ₹956 million, which is up 186% year-on-year and 37% quarter-on-quarter. EBITDA stood at ₹581 million, with EBITDA margin expanding up to 60.7%.

Profit before tax turned positive at ₹86 million compared to a loss of ₹75 million in Q3. PAT stands at ₹64 million.

This performance reflects ₹120 million swing in profitability sequentially, driven by operating leverage and of strong execution. EBITDA margin expanded by 413 basis points sequentially.

At the same time, depreciation increased to ₹513 million in Q4, reflecting ongoing infrastructure investments. Despite this, we achieved positive EBIT and positive PBT.

For the full year FY2026, revenue stands at ₹2,456 million, which is up 50% year-on-year. EBITDA crossed ₹1,263 million, which is up 30.6%.

However, we reported a PAT loss of ₹156 million, which is driven entirely by the depreciation on our GPU infrastructure investments. Our core business remains strongly cash-positive, operationally profitable at EBITDA level.

As utilization continues to ramp up, revenue will progressively outpace depreciation, improving reported profitability. To conclude, Q4 demonstrates our infrastructure investments are translating into revenue, and we are firmly on a path for growth.

Thank you for your time. Now, I would open the floor for the questions.

Hi. Thanks for the opportunity.

Sir, first question is regarding the asset-light model that we are looking out for with L&T. Could you throw some light how will the asset-light partnership fructify, what sort of arrangement we have?

Of course, we have a MoU with L&T to monetize the GPU infrastructure that they are building. Now that is still in exploratory stage.

As the GPUs get deployed and we start working to monetization, as we know more and more, we will talk more and more about that. That being said, that this is not a exclusive arrangement, we will continue to operate at an arm's length with L&T, and we will continue to explore other partnerships of similar or different nature as well.

There is a long gap between say pure debt versus pure equity. There are number of structured possibilities in terms of figuring out that how to finance the GPU in partnership with a lot of different types of partners with differing objectives.

We'll continue to explore all those partnerships. As and when we kind of reach a conclusion on any particular partnership, we'll obviously keep everyone informed.

Sure, but will it be margin accretive or because the CapEx is going to be on another partner?

It's too early to say, Bhavya, how would the numbers look like. Obviously, it's very, very early to say how those things would look like.

Unless the structure is finalized, see, obviously, we all work for a profit, [laughter] we'll not do anything which doesn't earn us a profit. That being said, how to put numbers to that is not something we can do today.

Got it, sir. On the MRR, would you like to guide for the next year because you've been doing this CapEx from your own pocket also this year?

If you can-- We'll continue to kind of focus on growth just the same as rest of the market is growing, we want to be very, very growth-focused. That being said, that I think it would not do justice to do a MRR guidance for one year in the future.

I think the future is changing very, very rapidly week-on-week. It is obviously impossible to give a week-on-week guidance on MRR, and it would be better to kind of watch it quarter-on-quarter than kind of predicting four quarters in advance.

If you can just throw some light on the asset turns for the CapEx that we are doing. At least some sort of understanding we can get in terms of CapEx.

Like

I think we want to get the framing away from things like asset turns. Essentially, like don't look at us as a asset monetization business.

Look at us as a technology business. Like I think there was like a recent conversation like around the tokens becoming more valuable.

Same set of tokens that were being generated by say open-source AI or closed-source AI like what used to produce like say X amount of value, we are increasingly seeing that like as the accuracy, efficiency, capabilities of AI increases, then the generated tokens also become more valuable for businesses who have figured out how to utilize those tokens in their business. Which means that like kind of like setting us setting up ourselves or looking at the value of our outcomes based on the size of our assets doesn't do justice to the business.

Ultimately, we want to get away from saying that, okay, this infrastructure produces only X amount of value. We will continue to explore options for how to produce more value from the same infrastructure by figuring out like where the tokens are more valuable.

Got it. Fair enough.

Sir. That is from my end.

I'll get back in the queue. Thank you so much.

Thanks, Bhavya.

Hi. Thanks for the opportunity, and congrats.

Am I audible?

Yes. Please go ahead.

Hello? Yeah.

Yeah. We procured the Blackwell way back in early quarter, and now the test is not live, what's the reason behind the delay?

Are we facing some kind of procurement issues or something from the NVIDIA or?

Global supply chains have been impacted somewhat. The delays are always for want of a horseshoe nail.

Kind of we have been working very diligently towards making sure that everything is planned out and everything gets delivered on time. Then you can't control every single component, and sometimes some components can be the most critical ones from the point of view of getting the entire deployment done.

We are targeting the first deployment to go live before mid of May. Keeping our fingers crossed over there.

Got it, sir. This quarter the demand has been strong globally, and people saying that all the GPUs are sold out including the old ones.

How are we seeing the spending in the domestic market? Are we also experiencing the same or is it a different situation in India?

Okay. I don't think I have understood your question, but let me try to answer what I have understood.

See, obviously, it has turned into a much better market than it was a couple of quarters back, especially for people who have the GPU infrastructure in place. That being said, that as a company, as an Indian company, we are very, very focused on India-first.

Wherever we get an opportunity to support Indian companies, we definitely like to do that. Now, with that in mind, basically, we always prioritize India-first, and then we are also happy to support the global infrastructure needs today.

I hope the answer is in the right direction towards what you were asking.

Yes. Definitely I was just trying to ask demand has been strong globally that the GPUs got sold out.

We are seeing demand both India as well as globally. It is strong both ways, and we definitely try to prioritize India, so.

Then wherever the demand comes from, eventually, we are happy to fulfill it.

Got it. One last question from my side, that employee cost increased this quarter.

If you could give some color on that, what's the key drivers behind the size?

See, as we grow, we kind of start figuring out more and more interesting problems that need to be solved in this space. Obviously, our goal is to go towards what you call higher-value tokens, and that obviously requires the application of quite a high level of talent.

As we obviously grow, the base effect would still be there, so. On the other hand, we want to maintain a balance of not losing out on future opportunities because we didn't invest today on what was required 12 months later or 18 months later or 2 years later.

Got it. One last thing, if you could also provide the GPU utilization level state if possible for this quarter?

See, broadly, across our entire infrastructure, not just GPUs, I think we are looking at 80% plus utilization. Certainly, across the quarter, now I would say only in the March month, we are looking at 80% plus kind of utilization, certainly less than 85%.

There is elasticity in terms of basically how we can increase the utilization further over there.

Got it, sir. I'll get back in the queue.

Thank you so much,

and congratulations for the good set of numbers. Thanks, Keshav.

Hi. Thanks for the opportunity.

Hi, Tarun. Just wanted to get a breakup of what is our MRR breakup currently?

Can you give a split between IndiaAI Mission, enterprise, and also split between what would the GPU contribution of that MRR be as compared to CPU? Yeah.

See, I think broadly the way things are progressing, in another couple of quarters, I think GPU contribution would be closer to 85%-90% over coming quarters. That being said, all these numbers are fairly dynamic.

In the sense that they vary very, very rapidly from a week to another week. The sample size today is fairly small.

What's the split is something that we don't want to worry about today. As we grow the cluster sizes to a much larger number, then it would start making sense to kind of talk about, okay, Hoppers we've got a couple of thousand of them, then Blackwells we've got a couple of thousand of them.

That's the point at which it would start making sense to say, okay, what's happening on Hoppers, what's happening on Blackwells. Today, the entire universe of GPUs, CPUs, storage, all of that stuff that we have is fairly, fairly small to kind of put a very, very strong split around those numbers today.

Fair enough, sir. Could you just give a MRR split between the IndiaAI Mission and our enterprise or our SME clients?

Just trying to get a idea of what kind of visibility do we have in that ₹374 million MRR? Also just to add on to that, before that, our MRR for the previous 2 months if we average it, it would come to a ₹290 million kind of MRR.

Just trying to understand the spike that came in the last month, what was the reason for that spike? Also how sustainable is this 374?

It's broadly an increase in overall utilization that has led to the increase in the spike in the March month. From the perspective of overall split, yeah, basically the overall government business across this quarter has not exceeded more than say 35%-40%.

All right. Sir, is there some particular reason for that because ideally IndiaAI Mission was supposed to start in the month of Jan.

We are in March as of this quarter's reported numbers, what kind of ramp-up are we seeing in that? Just any kind of timelines and what kind of revenues in terms of MRRs do we expect from that?

The way we have always looked at IndiaAI Mission is that like we said that we are supporting India, we are supporting IndiaAI Mission, we are supporting Indian companies, and we definitely give a preference to all those workloads. That being said, whatever capacity is not uptaken, we are not trying to kind of force anyone to uptake any capacity from us.

We are very, very happy to sell it to outside the scope of either the AI Mission or the government workloads. We have enough customers across multiple segments to kind of solely rely on one revenue driver growth.

That being said, we continue to work very closely with the AI Mission for the coming generations of GPUs as well, and we are hopeful that we will continue to collaborate, continue to work together, continue to solve problems. Sir,

just trying to understand that IndiaAI Mission was almost all our Hopper and Hopper series GPUs were given to IndiaAI Mission. Seeing 80% utilization, but IndiaAI Mission--

No, we have not scaled up to that extent. Majorly whatever was the scale required by the allottees of AI Mission, we have provided that scale, but we have not insisted on them having to increase their scale without having the need for that.

We are quite okay with that.

In terms of our revenue currently, what kind of clients are we currently catering to and what's the pipeline? You said mid-May we expect Blackwell to get deployed.

Do we have any firm orders?

Again, this is a very, very small base. There are GPU customers everywhere in the world.

There are GPU customers in India. There are GPU customers outside India.

Every possible segment that you can think of, whether it is enterprise, whether it is BFSI, whether it is education, everyone needs GPUs. It's practically basically almost first-come, first-served today.

The nature and profile and putting a stat on, okay, this much of our business comes from here, this much of our business comes from there is kind of very, very premature. I think we need to grow the base of GPUs to a couple of tens of thousands before these numbers start to make sense.

Today at a very, very small base, none of these numbers would make sense to kind of track and then kind of say that, okay, what's the kind of numbers this quarter, it will change next quarter.

Sir, what did you try to say that until we don't build a huge base of GPUs, our MRRs will be lumpy in nature? Is that what you're trying to iterate at?

No, I think the demand has secularly changed in the GPU world. From the era in which the lumpiness was there because our base was even smaller, I think we have come a long way over there.

That being said, the lumpiness will continue to decrease as we continue to build more and more volume of GPUs under our management. Sir,

out of this ₹374 million, what exactly would be long-term MRRs that at least you're seeing the visibility for the next 8 to 10 months or a year or so?

We have a balance of basically thinking about, okay, what needs to be 6 months, 1 year, month-on-month, which is preemptible. We are doing kind of a whole series of them.

It's a week-on-week effort to kind of figure out that, okay, what is the capacity you want to sell hourly, what is the capacity you want to sell weekly preemptible, what is the capacity you want to sell monthly, what is the capacity you want to sell yearly. That being said, wherever larger clusters are involved, we try to do at least 6 months to 1 year visibility with our customers.

Increasingly for even larger customers, we are trying to look at even longer visibility to at least 2 years to even going up to 3 years. That being said, our view is that as tokens become more expensive to generate and kind of they generate more value for people, it is better to kind of not put all the eggs in the long-term basket, but have a judicious mix in very short-term contracts and medium-term contracts and some degree of long-term contracts.

Got it, sir. Got it.

Just one last thing, sir. In terms of the Blackwell that we expect to get deployed in May, can you give any idea in terms of who will be the customer?

Will it be enterprise, IndiaAI Mission, and SME? When would that customer's revenue start to come in?

Will it be in May or will there be a lag?

We will announce that after closing that particular deal instead of saying anything speculative today.

Fair enough, sir. Fair enough.

Thank you. That's it from my side.

Hi team.

Good evening. Sir, I have one question.

As you said, company is building up the asset using--

Am I audible now?

Sir, I wanted to say that as company is planning to build assets using debt as well as equity, and subsequently intend to go for the asset-light model also. Will this change our business model?

Means instead of providing hardware, we would be providing more of service and we offering our TIR platforms? Will this lead to change in our revenue model?

Think of this as a expansion of the number of business models without shutting down any of the existing business models. We will continue to own, continue to operate GPUs, we'll continue to acquire new GPUs.

We will continue to expand the partnerships to kind of bring increasing number of GPUs under our management, available through our TIR platform with operates at multiple layers where it is a choice of the customers what layers they want to buy. Kind of nothing is changing from the point of view that, okay, we are not going to do this or we're not going to do that.

We are simply saying that we are going to do additional number of things to expand the universe of our thinking to do a lot more than what we are doing today.

Sir, it will be an ideally additional line of revenue, you mean to say?

Absolutely.

Absolutely. Sir.

That's all my query, sir. Thank you.

Thank you.

Am I audible, sir?

Okay. Thank you very much, sir, for this opportunity.

Sir, just wanted to understand now at a March MRR of ₹37.4 crores, what is our capacity utilization and on what capacity?

This is closer to overall capacity utilization of around 80% in the March month.

On a capacity base of 2,900?

This is CPU, GPU, storage, all capacities put together. The utilization is closer to 80%.

Closer to 80%.

Yes.

I think we have around 2,050 lined up in next what, 6 to 12 months?

2,048 plus some spares that we are planning to deploy this financial year, starting from May where the first lot of 1024 is expected to go live.

By FY27 end, we would be targeting around 6,000 of capacity?

I wouldn't want to place a limiting number over there, but [laughter] you could say that that's the minimum number. Ha,

at least that. Understood.

That's what is already visible, so that's what we already spoken about, yeah. Fine,

understood. You mentioned around 80%-85% utilization by March.

You're talking about by March '27 of this expanded capacity? How so-- No, no,

no. This is the previous month, March.

Achha, achha. Previous March only.

Understood. My second question is on your fixed assets.

We have got around ₹1,500 crores odd of gross fixed asset, right? Last 2 years CapEx has been around close to that only.

This entire is a depreciable asset? Would that be a fair assumption?

I would let Nitin put a perspective on that.

This block is the depreciable asset, which constitutes of the new B200, which is currently displayed as CWIP.

Correct, correct. What is the amortization schedule for this?

Is it 3 to 4 years maybe?

6 years.

6 years. Understood.

What would be FY27 CapEx target?

Like we said we are already planning to deploy 2,048 B200, so that is already in place as far as our known plans are concerned. That being said, that we are not limiting ourselves to those plans, we continue to deploy capital under various business models judiciously to expand the GPU footprint fairly rapidly.

Correct.

Any number you have? I think FY26 was close to ₹600-₹700 crores.

A look-back is more important than putting a number in prediction.

Understood. That would be it from my side.

I wish you all the best. Thank you.

Thank you.

Hi, Tarun.

Hi, Varun. Hi.

My question is on GPU rental prices, and are we seeing pressure on them? I ask this from two aspects.

The first aspect is the technology is advancing rapidly. We see the Rubin architecture has been disclosed by NVIDIA, which is much more cost-efficient for inference compared to even your Blackwell architecture.

Number two is the competition that's been ramping up across domestic competitors, right? Are we witnessing any sort of pressure on GPU rentals right now, or do you foresee that in the near term?

See, I think broadly the trend today is that there are not enough GPUs in the world that people want to buy and deploy. That's the current trend.

Now, whether this trend remains for how long is hard to predict. The broad secular trend has been there that basically there are AI believers and there were AI non-believers.

I think the proportion of non-believers is slowly dwindling. It's quite clear that we are barely scratching the surface in terms of utilization of AI.

We have looked at so many of our customers, so many of the organizations we work with, including our very own. Where we say that, okay, is it the case that our AI utilization is to an extent that we want it today?

The answer for ourselves that we increasingly get is no, no, this is going to be more like 10x, 20x, 50x of where we are today in terms of how we are utilizing AI. AI is not coming out of the IT budget.

AI is essentially coming out of your budget for the capabilities that you're building for the business. That being said, that I don't think the demand environment in the foreseeable future is going to be changing negatively for long periods of time.

I don't think that's going to be the case from the visibility we have today. We don't see that there is any negative pressure on the pricing today.

In fact, there are I think good set of tailwinds which are slowly inching up the prices rather than a decrease in pricing.

Got you. From a demand standpoint, we aren't seeing any sort of negative.

From a technology advancement standpoint, let's say if the Rubin architecture comes in live in this year and it should, would that pressure--

There is a lot of workloads that will go into production where they will continue to operate on the targeted architecture. Typically, it's what you call a funnel kind of a growth where the next layer of the funnel is bigger than the previous layer of the funnel.

Which means that the demand for existing GPUs will continue to remain very, very strong. Demand for even the Ampere series has remained strong, Hopper series has remained strong.

Tarun, I understand the demand has remained strong, but let's say 2 years ago the GPU enterprise is for Hopper H200s, are they same today or they are lower 30%-40% lower than what they were quoting at 2 years ago? See,

I think taking the case of 2 years ago is slightly anomalous from the point of view that I think that was one particular year in which the GPU demand went from say 1 to 10. I think that capability-driven shortages where the capability to print that many GPUs had to be built very rapidly.

That created I think a local maxima of pricing. Broadly, we are seeing that there is stability in the pricing for GPUs over an extended periods of time.

Typically, we feel that it is possible to kind definitely use and utilize the GPUs over a 7-8-year period. We don't think that the GPUs are a 2-year story or a 3-year story and then kind of there is something available at a much lower cost and you are able to shift.

Those shifting costs are very reasonable. That's not the case.

Your entire test-debug cycle for doing AI on a new chipset is a whole other set of expenses that you don't want to do if your job is getting done by a GPU which is available at a very reasonable price.

Got you. Now, my second question is at the beginning of the call, you touched upon how you've significantly improved your software architecture.

If you could just highlight a brief example of how you've done that? You iterated that you're now trying to capture high-value tokens.

Is there some sort of example that you could showcase? No,

this is broadly from the point of view is that the tokens themselves today are more valuable. It's just a point of choosing the right set of tokens that people are going to utilize.

It's not kind of a strategy statement to go and capture one particular set of high-value tokens today. It's a broad futuristic outlook that, look, ultimately, we have to go and figure out which are the high-value tokens.

Now, that being said, from a platform improvement perspective, we have been working on things which are required by people running training on larger clusters, people who are running inference, how to support them, people who want to build rapidly the pipelines reliably across larger number of GPUs, and understanding of what is it that the AI data scientists do from a been there, done that perspective. We have made improvements in all those areas for productization of our TIR stack.

Right. Just as an extension to this question, see, we're very well positioned to capture the sovereign AI tailwind, and my understanding is that BFSI companies would be a key client base over there.

Is there any sort of strategic development that you could share where you're partnering with some sort of SaaS companies or other software companies and trying to offer a bundle of software plus compute? Is there something you could help us with?

Yes. As we do something, we'll definitely share that with everyone over here.

As things happen, we'll do a look-back and say that, okay, this is what we've done.

Okay. There's nothing that you can share in terms of your thought process over here?

See, we continue to drown in opportunities. [laughter] What we capitalize on, we will come and inform the market.

All right. Thank you so much.

Thank you.

Hi, Abhishek.

Hi, sir. Thanks for the opportunity, and congrats on a great set of numbers.

My first question is about the guidance commentary. If we summarize your comments on the demand, it appears to be really strong.

We have a visibility of 2,048 GPUs. Then we said that we don't want to get fixated on the guidance.

Just trying to understand that the purpose here was not to get fixated on the numbers rather than any worries in your mind about the current macro. Is the understanding right?

We are not worried about whatever numbers we give whether we will be able to meet them or not. I think we don't want to give a underwhelming numbers without first exploring over week after week over 52 weeks what we are capable of doing.

It will become sort of a limiter for us ourselves to say that, okay, we are only to meet this number. [laughter] That's why we are not putting a number today.

Perfect. That's very helpful, sir.

The second question is on the pricing. Contrary to the prior question, the recent articles are suggesting that the GPU spot rates for April have gone up substantially higher.

For an H100, the prices are up anywhere by 25% to 30%. Can you just--

We are seeing that. We are looking at that.

That being said, we obviously try to capture some of that, but then that being said, we are also trying to support the Indian companies and India as a country. There we want to have a balance between long-term and short-term.

Short-term of course, we want to make more money, and long-term of course, we want to work with the kind of customers who will sustain and grow on our infrastructure over a long period of time.

Perfect. Sir, just last one data point from Nitin sir.

The depreciation for the next quarter should be up by around ₹25 crores a quarter, right? Is that assumption right?

I'll let Nitin answer the questions around the depreciation. Nitin, over to you.

Sorry, could you repeat again?

Sir, the depreciation for the next quarter should go up incrementally by ₹25 crores a quarter. Is the assumption right?

Why do you expect that

because-- Because of the B200 cluster.

B200 cluster would be that we are seeing the timeline of mid-May. That's why there would be a increase in the depreciation, but not to that significant effect that what you are telling now.

Okay. Perfect, sir.

That is very helpful. Thank you for taking my question, and best wishes for the next year.

Thank you, Abhishek.

Hi.

Hi, Neilji. Haanji.

Yeah. Hi, sir.

Thank you for the opportunity. Sir, my first question is building on this participant's question.

If the capacity utilization

Is it better now?

Yeah. The first question is basically building on participant's question.

You said the 80% utilization that we're talking about, I'm assuming this is excluding the new B200s clusters.

Yes, that is excluding the B200s, obviously.

Yeah. When we talk about the 80% utilization, with respect to the remaining capacity available, have we kept this aside for POCs or demand is still ramping up in that sense?

No, demand is still ramping up over there. It's all parts of different parts of the capacity.

They all work in different combinations. An ideal utilization number it depends on basically where do you end up.

That's not a limiting factor on the MRR from a very straight-line perspective. For instance, the same particular piece of hardware could under different circumstances be billed at wildly varying rates.

What is my assumption--

These are all averages, essentially. These are all important from a look-back perspective.

This is our assumption on that, look, we are doing what is sort of an 80% capability. Now, 80 could be 80, 80 could be maybe 85, 80 could be even 75, maybe even 70.

Understood. Sir, with respect to the demand scenario in B200s, have we closed any IndiaAI Mission?

We have not closed any deals on the Blackwell capacity which is going up as yet. Obviously, once we close the deals, we will kind of inform everyone over here.

Sir,

is the reason ramp-up or is the reason that we are still closing POCs or testing?

There is a lot of interest in the Blackwell capacity that we are building. Kind of we are working with multiple customers to figure out what sort of problems they need us to solve for them and what is it that they're looking at from us.

We obviously want to work with the customers that are best placed to utilize what we have to offer.

Thanks, sir. That's it.

Hello. Hi, sir.

Thank you for the opportunity. Congratulations on a set of good numbers.

Thank you, Hardik.

Just wanted to push on a question asked by the previous participant. I think so majority of the investor group just wants to know whether the revenue uptick is due to any lumpy nature or are you seeing any sustainable growth in the long run because in the last December and March we suddenly dropped the numbers.

We stated that the startups were no longer wanting our ecosystem, right? We just want to know from a long-term perspective or at least from a--

Let me try to answer that question as best as possible. See, the lumpiness is a part of the nature of the business.

The lumpiness will keep going down as we keep increasing our GPU base. Now, that being said, we are currently seeing the kind of customers who are buying these GPUs have sustainable long-term workloads.

These are not of the short-term nature for most part. We do expect to have sustainability for these workloads over the medium term.

I don't think there is going to be a massive amount of lumpiness in the near term. Medium term, of course, as the number of GPUs grows, I think the effects of lumpiness would be far more muted than it has shown up in the past in the early days of us building the capacity.

Right, right. The second question from my side was to understand again on this part itself that what percentage of revenue are we allocating to a long-term MRR for the long-term contracts so that our MRR--

It's of a dynamic nature, basically it is not possible to predict

from a-- We're not predicting. I'm just saying that from a

No, no, we're not setting any hard lines over there. See, we are not setting any hard lines over there.

There are I think far more number of variables to consider than it would be possible to describe over here that what to pick up when in terms of customer interest. I don't think I would be able to give a very fair, fixed answer to that question.

We are definitely interested in having some percentage of long-term contracts. What that percentage will come out to be is we need to look at on a look-back basis when the size and scale of the GPU installation is sufficient.

I think in the short term, there is no clear-cut answer to that.

All right. Just a small data point, if I can.

What percentage of revenue did come from customers outside India versus domestic demand for the last quarter?

I'll let Nitin take a stab at this question.

The international revenue for the last quarter is roughly around 35 odd percent, 35% to 37% is the international customer revenue.

Okay. Thank you.

That's really helpful. Appreciate the time.

Hi. Hi, Srinivas.

Hi, sir. Am I audible?

Yes,

yes, loud and clear.

Yeah. Sir, what percentage of Q4 revenue came from inference workload versus training and what would be the future split-up of this mix directionally, sir?

I think there is a lot of confusion about what consists of inference revenue versus training revenue. I think these are not super hard lines.

Sometimes the same set of GPUs are used by the customers for kind of bursting up the inference workloads when the inference workloads are high, and then at a time when the inference workloads are low, they get converted to training. The workload management is far more flexible today to kind of point to, okay, what percentage of inference, what percentage of training today.

I think again, at a much larger scale, these numbers would become clearer. Today of course it's hardly possible to kind of super differentiate between, okay, who is using that 1 GPU, 4 GPU, 8 GPU, 16 GPU cluster either for training or for inference.

That being said, majority of revenue is still closer to training than to inference.

Sir. We said 6,000 GPUs by FY27 at least minimum, right?

What would be the upside, sir? Could you deploy 8,000 on upside, 8,000 to 10,000?

I don't want to put any numbers right now. So, [laughter] let's look at those numbers as a look-back over coming period of time, rather than putting out a number today.

Okay. Thank you, and best of luck.

Thank you very much.

Hi.

Hi, Rohan. Hi, thank you for the opportunity and congrats on a good set of results.

My first question was so you said that there's a variety in terms of your current MRR being short term, medium term, slightly long term. Could you provide some directional commentary on how much of that MRR is 6 months plus or 1 year plus?

I think one is we are still on a very small base of GPUs. Kind of we are not doing any hard split in terms of where we want to be or where we are today.

It's fairly dynamic and rapidly changing, both with new capacity coming up online. All these numbers are subject to very rapid and very wide amount of change.

These do not add to any understanding for anyone today.

If there is a 20% to 25% increase in the spot price, then capacity that is contracted out for 6 months or 1 year will not be in a position to take advantage of any increase in realization, right? I think it would be somewhat beneficial for someone looking at it from the outside to get a sense of some amount of revenue of exposure to increased realizations.

That's a very granular set of understanding that you're seeking on a very small size of the infrastructure installation base compared to the global peers. I think we would like to avoid this conversation for today.

As we grow in size, then we kind of talk more about that, okay, now these numbers actually mean something and they are making sense to someone on the street. Today these numbers would not make much sense.

Sure. Fair enough.

Then my second question was so you talked about higher-value tokens. Could you provide some color on which industries are sort of taking advantage of higher-value tokens from your vantage point?

Not really. I think it's more closer home than that in terms of, okay, what's a higher-value token.

Asking a question, okay, what is closer to a search query is a reasonably low-value token. Someone using the tokens to solve a specific problem that is paying the bills for a company is a completely different value conception for those tokens.

Answering a basic transactional support query is a reasonably low-value token. Being able to answer a more complicated query or being able to confirm a more complicated transaction with a customer on call is a higher-value token.

There are infinite number of variations of how people use AI, and the key is to find those customers who are utilizing the higher-value tokens where they are not worried about, okay, what's my ultimate per hour GPU price, but what's the cost of my solving a particular problem and generating a higher ROI. Again, we are not directly involved all the time in identification of higher-value tokens and kind of being able to categorize in a very, very static manner that, oh, we should go and sell to this customer, they'll probably pay higher for this particular GPU.

It's a broad industry trend where we are seeing increasingly the demand coming from customers who are not price-sensitive because of their ability to generate or consume higher-value tokens through a combination of their own software or proprietary or open-source software that is available extant in the market today.

In that case, what is E2E's role in this high-value tokenization? That would just be an outcome of if the person who is renting a GPU or taking on GPU capacity is able to extract higher value, then he is willing to pay more, right?

The price discovery is just take care of who is generating high-value token. I wanted to hear on how E2E is sort of working towards higher-- See,

how you are able to quickly get to that point of being able to generate and utilize those tokens for your business, it's fundamentally how to build on various parts of the software and hardware stack to make it available quicker, I think that's where the role is played by E2E.

Understood. Okay.

Fair enough. That is from my side.

Thank you, Tarun.

Thank you.

Thank you to all our investors, all our team members, all our customers, all our ecosystem partners for all the support you have all extended to E2E Networks over last many years. It's been a overwhelming amount of love for us that we are seeing in the community and overall community.

We wish you all a great day ahead, and thank you for patiently listening to our call. We would like to kind of once more thank everyone and end this call.

Thank you.