Hi
This $2million dollar per MW number was given to us by Management. I just connected the dot with 30cr And 2MW LT data centre.
Maybe that 30cr from LT is coming for another reason.
LT 2000cr spending on AWS. This number is also given by management. And 2000cr includes everything thing from cloud to AiCompute.
Incremental workload is expected to shift to LT data centre which will benefit E2E from software perceptive. LT is actually shifting some of it’s workload project by project. As you may know AWS charge hefty fees for downloading data outside AWS. So,That is actually huge problem for clients to move out from AWS to LT data centre. But LT is working on commercial with clients how they can get the workloads.
This calculation would hold if the hardware assets were the future. If the management has shared the truth with @HiteshTinna, then a lot of this cash would go towards sales team and marketing (i.e expenses), so wouldn’t reflect on the balance sheet.
Well if you meet Management in person. They will share the glimpse of what they are doing or planning with LT. Even When management came in Pune In AI for Finance event they were very vocal about what they are doing on software side.
I have got the info because i went with a family office who participated in pref round.
I would again say you try to meet management in person you will get the best info.
I see a lot of good news and big projections for e2e in this vp channel some of which e2e promoters themselves have not made public.
Although everything looks good, it seems there are lot of moving parts.
Things became more interesting because l&t is also involved. This entire partnership seems like l&t will benefit more than e2e.
In fact most of the partnership are like that where the acquiring company gets the most benefit.
DeepSeek released an overview of their Inference System - and it’s full of interesting bits!
Over a typical 24 hour period:
Input Tokens: 608B (56.3% cache hit rate)
Output Tokens: 168B at 20–22 tokens/s
Throughput: ~73.7k tokens/s (prefill) and ~14.8k tokens/s (decode) per H800 node
Cost: $87,072 daily (278 peak nodes, 226.75 average nodes)
Theoretical Revenue: $562,027 daily (545% margin)
Cache Efficiency: 56.3% on-disk KV cache hit rate
(in short : deepseek is opensource + is pulling profits on nvidia cheap gpu’s) not sure, hence can someone in this industry give a clear context on it. would be helpful thanks.
L&T deal happened in Nov, so they would have known about E2E’s software pivot. But they still chose to value co. at almost USD 1bn. This signals their confidence in E2E’s software and future prospects.
Hyperscalers are in completely different league and not necessarily in direct competition with E2E. E2E’s value proposition is significantly lower costs, so enterprises can at least move part of their cloud workloads to E2E’s cloud.
Jio anyway would be an infra provider, E2E is up the value chain.
Key here is whether E2E can crack large enterprise customers, because that would open a large market. Getting L&T’s business would be a good start.
Let’s track company’s performance for the next couple to years. IT companies in the past have become huge and I hope E2E can also become a large cap company as the promoter looks hungry for success and the giant like LnT can provide the required support. AI in India is still at a nascent stages and it’s a high time we become innovators rather than copying the technologies built by developed nations. Nvidia was trading around 40 cents a decade back and it has touched an all time high of 153 USD. Noone would have imagined the growth of GPUs a decade back. Big money is made when there are lot of uncertainties and hope we are in touch with each other if the company become bigger in future:smiley:
While first point being true regarding comparison to NVIDIA. You cannot claim that E2E simply buys GPUs and sells in India. They have a software system, they need to take of the client experience as well. This is what can give them an edge going forward.
I am not drawing any comparisons. I am just saying that no one is capable enough to predict the growth of the companies. Did anyone predict the growth of nvidia, titan, bajaj finance etc We must track the company’s performance for the next couple of years and if you think AI is a real threat and most of the jobs should be vanished in next 10 years then we should not ignore AI/IT companies. Growth is not linear for the small cap companies and most of the wealth is created when things are uncertain. People were jumping to buy at 26K and now there is fear everywhere. This is how phycology works in the market. Fundamentally sound companies will always bounce back and in my opinion E2E seems to have bright future. Rest time will tell everything. Are you invested in a company?
Thanks Hitesh for giving this thread a new life, negativity due to market fall have also made this forum in not right direction but now it seems a good discussion will happen now. Also many investors on the concall miss the opportunity to grill the promoters and find the real biz information. Many ask about financials and target which is being denied by them in past and that too all the times management just say no to any forward looking statement.
I was on the con call last time but didnt get my turn. It was frustrating to hear a lot about deal and about biz. People should ask more about their plan for next couple of years and not everything on current situation.
I have been told that E2E is not able to cater to customers who become big and move out of their network. Also i want to know that do big companies have their cloud services with multiple service so that they do not have downtime if anythung happen to one service provider?
Dua ji has been vocal about asset turnover , we should also ask him on this line of asset turn.
Lets see how employee cost comes in play when E2E goes on softawre development mode.
Hi Ravish
Rightly said in concall many ask questions from management just on financial and wants what will be the asset t/o, capex, future demand, etc. Rarely anyone ask about future prospects what company is planning for next leg of growth. But At one point i feel Analyst community is also not wrong as they more inclined towards Financials. And understanding IT and Pharma sector is not easy.
Yes, Big companies do have multi cloud.
But one thing is there management should shares some of their plans in concall for investors confidence. And Analysts should also not stick with every number that management says, Because situation itself is changing every day and management has to change its course based on industry.
Based on my experience, capturing market share from major hyperscalers such as AWS, Azure, GCP, and OCI is extremely challenging.
Rackspace, once a pioneer in the cloud industry, was outcompeted by these deep-pocketed players, which ultimately led to its bankruptcy. Later, Rackspace was acquired by Apollo Group, they become private cloud provider and re-listed on the NYSE in 2020 appx at $20 per share. However, its stock is now trading at less than $3.
E2E may benefit from strict data locality, or if the government implements policies encouraging its entities to opt for local providers. Otherwise competing with big hyperscalers would be difficult for E2E.
So, we should be little vigilant over here.
Disc: have small tracking position (very small)
Big Hyperscalers setting up data centers in India ( for more detail refer Cloud Infrastructure Map)2%20Zones-,eu%2Dfrankfurt,asia%2Dsouth2)
I asked ai about the market share data among the ai infrastructure provider in india, and got reply like this
As of March 07, 2025, specific market share data for AI infrastructure providers in India—such as IndiaAI Mission, Krutrim Cloud, Jio Platforms, E2E Networks, Yotta Infrastructure, AWS, Azure, and Google Cloud—is not comprehensively available in public sources with precise percentages for this exact date. However, I can provide an informed analysis based on available trends, recent developments, and contextual insights to estimate their competitive positioning in the Indian AI infrastructure market.
IndiaAI Mission
Positioning: Not a traditional commercial player, IndiaAI Mission is a government-backed initiative aimed at democratizing AI compute access. It doesn’t compete for market share in the conventional sense but influences the ecosystem by providing subsidized access to over 18,000 GPUs (e.g., ₹67 per GPU hour). This makes it a dominant force for startups, academia, and MSMEs, potentially capturing a significant portion of the “affordable compute” segment.
Estimated Influence: Likely serves 40-50% of the subsidized, non-commercial AI compute demand (e.g., research and small-scale projects), based on its scale and government backing, though this isn’t direct market share in revenue terms.
Krutrim Cloud
Positioning: A rising Indian player emphasizing low-cost AI cloud services, Krutrim claims to offer some of the “lowest pricing in the world” (per X posts). It’s targeting developers and startups with localized infrastructure and models like DeepSeek hosted in India.
Estimated Market Share: Likely small but growing, perhaps 2-5% of the commercial AI infrastructure market in India. Its focus on affordability and domestic hosting gives it an edge among early-stage Indian AI firms, though it lacks the scale of hyperscalers or government initiatives.
Jio Platforms
Positioning: Leveraging its telecom dominance and cloud ambitions (e.g., Jio Brain, Cloud AI PC), Jio is expanding into AI infrastructure. It’s part of the IndiaAI Mission empanelment, offering 208 NVIDIA H200 and 104 AMD MI300X GPUs, suggesting a hybrid commercial-subsidized role.
Estimated Market Share: Potentially 5-10% of the AI infrastructure market, given its vast customer base (over 400 million telecom users) and investments in hyperscale data centers. Its market share could grow as its AI offerings mature, especially if pricing remains aggressive.
E2E Networks
Positioning: A homegrown cloud provider specializing in GPU instances (e.g., NVIDIA A100s), E2E targets Indian startups and enterprises. It’s empaneled under IndiaAI Mission, contributing to the 10,000+ GPU pool.
Estimated Market Share: Likely 3-7%, focusing on niche, cost-sensitive commercial clients. Its localized operations and competitive pricing give it a foothold, though it’s smaller than global hyperscalers or Jio.
Yotta Infrastructure
Positioning: A major private player with hyperscale data centers, Yotta dominates IndiaAI Mission’s GPU supply (9,216 GPUs, including 8,192 NVIDIA H100s). It’s positioning itself as a sovereign cloud leader for both government and enterprise use.
Estimated Market Share: Potentially 10-15% of the commercial AI infrastructure market, bolstered by its IndiaAI role. Its scale and focus on high-end GPUs make it a leader among Indian private providers, though it competes with global hyperscalers for enterprise clients.
Global Hyperscalers (AWS, Azure, Google Cloud)
Positioning: These giants dominate globally and have a strong presence in India, offering extensive AI infrastructure (e.g., AWS Inferentia, NVIDIA GPUs). AWS, through managed service providers, contributes 1,200 low-end GPUs to IndiaAI Mission, while Azure and Google Cloud lead in enterprise adoption.
Estimated Market Share: Collectively, they likely hold 60-70% of the commercial AI infrastructure market in India. AWS is often cited as the leader (30-35% individually), followed by Azure (20-25%) and Google Cloud (10-15%), based on global trends and India’s public cloud market data (e.g., IDC estimates public cloud at $17.8 billion by 2027, with hyperscalers taking the lion’s share).
Market Share Estimation (Commercial AI Infrastructure, Revenue-Based)
Here’s a rough breakdown based on scale, offerings, and market trends as of March 07, 2025:
AWS: 30-35%
Azure: 20-25%
Google Cloud: 10-15%
Yotta Infrastructure: 10-15%
Jio Platforms: 5-10%
E2E Networks: 3-7%
Krutrim Cloud: 2-5%
Others (e.g., Tata Communications, CtrlS): 5-10%
Key Insights
Hyperscalers Dominate Revenue: AWS, Azure, and Google Cloud lead due to enterprise adoption, global brand trust, and extensive service ecosystems, despite higher costs ($1–$5+ per GPU hour).
Indian Players Gain Traction: Yotta, Jio, and E2E benefit from localization, government partnerships (e.g., IndiaAI Mission), and competitive pricing, carving out niches in the startup and SME segments.
IndiaAI’s Unique Role: It skews the market by offering subsidized compute, reducing reliance on commercial providers for certain users, but doesn’t directly compete in revenue terms.
Data Gaps: Exact GPU counts, revenue figures, and client adoption rates aren’t fully public, so these estimates blend reported capacities (e.g., Yotta’s 9,216 GPUs) with industry growth projections (e.g., AI infrastructure market reaching $82.23 billion globally in 2025 per Mordor Intelligence).
Thanks for sharing the information. It would be better if we do have some estimates so that growth can be predicted for the coming years. I know E2E has the potential and now the backing of LnT. AI is the future and I am glad that government has also realised that and taking some initiative. In my opinion we are at a nascent stage of AI developments and infrastructure and it will take time to implement the things. Any estimates on the top and bottomline would be highly appreciated
