E2E Networks Ltd

- E2E Networks is seeing a robust pipeline of demand for cloud GPUs, driven by increased inquiries and trials with larger customers. - The sales cycles for large enterprise customers are long and unpredictable, often requiring multiple quarters for conversion. - Currently, the company has a number of proof-of-concept (POC) and trial engagements with large customers, many waiting for new GPU capacity to be fully deployed and tested. - The company has decided to expand rapidly by building a 2048 GPU cluster immediately instead of incremental smaller builds, reflecting confidence in strong demand. - Although exact orderbook or pending order figures are not disclosed, the management expresses confidence that over a 4 to 5 quarter cycle, they can achieve a Monthly Recurring Revenue (MRR) target of INR 35-40 crores. - The focus is on long-term contracts and converting trial customers into larger scale users over time.

- The company plans to fund incremental capex primarily through debt, leveraging cash flows generated. - Tarun Dua mentioned they have successfully arranged capital in the past via debt and will continue to be aggressive in raising required capital either through debt. - There is no specific mention of any immediate or planned equity fundraising. - The focus appears to be on using debt to fund expansion such as adding 6,000+ GPUs over the next 2 years. - Given robust deal pipelines and strong growth outlook, they have confidence in accessing necessary funding via debt instruments.

- The company currently has a capital work in progress of INR626 crores, primarily for the deployment of 2048 H200 GPUs procured around end of March, which are going live soon in Delhi NCR and Chennai data center (Q1 FY26). - They plan to scale up GPU capacity from 3,700 GPUs currently to about 10,000 GPUs over the next 2-3 years, adding approximately 6,000+ GPUs, investing roughly INR2,500-3,000 crores based on a cost of around INR45 lakh per GPU. - Capex deployment is tied to demand cycles, with plans to invest in newer architectures such as Hopper and Blackwell. At least 2,000 GPUs per generation are targeted. - Funding for incremental capex will come from cash flows and debt arrangements. - The company is focused on rapidly expanding capacity to cater to large customer POCs and the IndiaAI Mission opportunity. - The expansion aims to support targeted MRR growth to INR35-40 crores by March 2026.

- Targeting to grow Monthly Recurring Revenue (MRR) from INR 11 crores (March 2025) to INR 35-40 crores by March 2026. - Long sales cycles with larger customers expected to convert over 4-6 quarters, leading to more predictable revenue. - Robust pipeline of cloud GPU demand; capacity expanded by 2,048 GPUs recently to support growth. - Aim to add around 6,000+ GPUs over next 2 years, increasing total capacity to approximately 10,000 GPUs. - Long-term goal of 3x MRR growth over next two years via larger, contracted business vs. hourly/monthly usage. - AI Mission and Sovereign Cloud businesses are expected to contribute significantly, with AI Mission alone targeting INR 3,500 crores in annual revenue potential, aiming to capture 10-20% of that. - Strategic partnership with L&T to drive enterprise and international client acquisitions, accelerating growth. - Improving marketing and sales efforts to convert a larger number of trials into paid contracts.

- The company aims to triple its Monthly Recurring Revenue (MRR) from ₹11 crores in March 2025 to around ₹35-40 crores by March 2026. - EBITDA margin for Q4 FY25 stood at 40%, down from 60%, but the goal is to return to steady-state 60% EBITDA margins, including in new verticals like AI Mission and Sovereign Cloud. - PAT margin for FY25 was 29%, with an 85% increase in diluted EPS (27.2 from previous year). EPS grew from 2.4 in Q4 FY24 to 8 in Q4 FY25. - Fiscal year revenue grew 74% YoY to ₹1640 million; EBITDA grew 102% YoY to ₹967 million. - The firm anticipates strong growth supported by ramp-up in GPU capacity from current 3,700 to approx. 10,000 GPUs in 2-3 years, targeting larger enterprise customers. - Conversion cycles are long but expected to stabilize over 4-5 quarters with increasing customer scale leading to higher utilization and revenues. - Long-term vision includes capturing a multi-decades growth opportunity in AI/ML cloud infrastructure and sovereign cloud markets.