E2E Networks hits 5% upper circuit, swings to black in Q1
Shares of AI-focused cloud hyperscaler E2E Networks surged 5% to hit the upper circuit at Rs 469 on Wednesday, marking a new 52-week high, after the company reported a net profit of Rs 44 crore in Q1FY27, compared with a net loss of Rs 28 crore in the year-ago quarter.
The company’s revenue from operations came in at Rs 157 crore for the quarter under review, registering a growth of 334% from Rs 36 crore in the corresponding quarter of the previous financial year, E2E said in a regulatory filing.
Margins shot up a massive 4,610 basis points YoY to 75.2% from 29.1% in the year-ago period. EBITDA stood at Rs 118 crore, up 1,023% from Rs 10.5 crore, E2E’s investor presentation showed.
Also read: Did this L&T-backed AI stock actually crash 90% in one day? Here's all you need to know
E2E Networks said its B200 cluster was successfully deployed on the TIR platform and began contributing to revenue within its first quarter. The company also scaled its GPU infrastructure to approximately 5,100 GPUs and incorporated Sovcloud Technologies Limited as a wholly owned subsidiary.
The company is operating large GPU clusters on the TIR platform, with a focus on achieving industry benchmarks for NCCL and Model FLOPs Utilisation (MFU). It is also investing in organisational capabilities by strengthening its teams, while cluster performance is being driven through full-stack optimisations across multiple layers.
What lies ahead?
According to the company's investor presentation, AI infrastructure is increasingly being viewed by governments and enterprises as a strategic national asset rather than a procurable utility. Against this backdrop, E2E Networks said India's planned 8 GW-plus data-centre build-out is bringing sovereign computing capacity closer to scale, positioning the company as a domestic provider of AI infrastructure.
The company added that the AI infrastructure market remains structurally undersupplied as demand for GPUs for AI training and inference continues to exceed hyperscale capacity, driving investment towards specialised neocloud providers globally. Oppenheimer Research estimates the global sovereign AI infrastructure opportunity at $1.5 trillion this decade, while McKinsey estimates that $6.7 trillion in global data-centre capital expenditure will be required by 2030, with around 70% driven by AI.
India is also building sovereign AI capacity at scale. According to Knight Frank India, the country's total data-centre pipeline stands at 8.33 GW, more than five times the approximately 1.6 GW of live capacity today. Around $30 billion of investment is underpinning India's data-centre capacity expansion, while the IndiaAI Mission has more than 38,000 GPUs. Mumbai and Chennai are emerging as key centres for AI capacity, with data-centre pipelines of 3.75 GW and 1.36 GW, respectively.
The company’s revenue from operations came in at Rs 157 crore for the quarter under review, registering a growth of 334% from Rs 36 crore in the corresponding quarter of the previous financial year, E2E said in a regulatory filing.
Margins shot up a massive 4,610 basis points YoY to 75.2% from 29.1% in the year-ago period. EBITDA stood at Rs 118 crore, up 1,023% from Rs 10.5 crore, E2E’s investor presentation showed.
Also read: Did this L&T-backed AI stock actually crash 90% in one day? Here's all you need to know
E2E Networks said its B200 cluster was successfully deployed on the TIR platform and began contributing to revenue within its first quarter. The company also scaled its GPU infrastructure to approximately 5,100 GPUs and incorporated Sovcloud Technologies Limited as a wholly owned subsidiary.
The company is operating large GPU clusters on the TIR platform, with a focus on achieving industry benchmarks for NCCL and Model FLOPs Utilisation (MFU). It is also investing in organisational capabilities by strengthening its teams, while cluster performance is being driven through full-stack optimisations across multiple layers.
What lies ahead?
The company added that the AI infrastructure market remains structurally undersupplied as demand for GPUs for AI training and inference continues to exceed hyperscale capacity, driving investment towards specialised neocloud providers globally. Oppenheimer Research estimates the global sovereign AI infrastructure opportunity at $1.5 trillion this decade, while McKinsey estimates that $6.7 trillion in global data-centre capital expenditure will be required by 2030, with around 70% driven by AI.
India is also building sovereign AI capacity at scale. According to Knight Frank India, the country's total data-centre pipeline stands at 8.33 GW, more than five times the approximately 1.6 GW of live capacity today. Around $30 billion of investment is underpinning India's data-centre capacity expansion, while the IndiaAI Mission has more than 38,000 GPUs. Mumbai and Chennai are emerging as key centres for AI capacity, with data-centre pipelines of 3.75 GW and 1.36 GW, respectively.
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