Synopsis: Shares of this AI cloud infrastructure company hit the 5 percent upper circuit after Q1 FY27 revenue jumped 334 percent YoY and net profit surged 582 percent QoQ.
The share of this company, which specializes in high-performance GPU cloud computing, public cloud, and machine learning infrastructure, gained investor focus after posting robust Q1 numbers.
With a market capitalization of Rs 9,181 crore, E2E Networks Ltd’s share on Tuesday made a day high of Rs 446.65 per share, up by 5 percent, hitting upper circuit from its previous day’s close of Rs 425.40 per share. The share of the company gave a return of 85.29 percent over the last year.
Result Overview
QoQ View: Revenue from operations increased to Rs 156.75 crore in Q1 FY27 compared to Rs 95.64 crore in Q4 FY26, registering a growth of 63.91 percent QoQ. Profit before tax rose sharply to Rs 58.62 crore in Q1 FY27 from Rs 8.55 crore in Q4 FY26, marking a growth of 585.61 percent QoQ.
Net profit also increased to Rs 43.88 crore in Q1 FY27 compared to Rs 6.43 crore in Q4 FY26, reflecting a growth of 582.43 percent QoQ. Earnings per share (EPS) improved to Rs 2.14 per share in Q1 FY27 from Rs 0.32 per share in Q4 FY26, representing a growth of 568.75 percent QoQ.
YoY View: Revenue from operations increased to Rs 156.75 crore in Q1 FY27 from Rs 36.11 crore in Q1 FY26, registering a growth of 334.10 percent YoY. The company reported a profit before tax of Rs 58.62 crore in Q1 FY27 compared to a loss before tax of Rs 3.75 crore in Q1 FY26, marking a significant turnaround.
Net profit also stood at Rs 43.88 crore in Q1 FY27 against a net loss of Rs 3.66 crore in Q1 FY26, reflecting a strong turnaround in profitability. Earnings per share (EPS) improved to Rs 2.14 per share in Q1 FY27 from a negative Rs 0.14 per share in Q1 FY26.
Key Q1 Highlights
Strong revenue and profitability growth: The company reported revenue from operations of Rs 156.75 crore in Q1 FY27, up 334.1 percent YoY and 63.9 percent QoQ, driven by the commercial launch of its B200 GPU cluster, better utilisation of flagship GPUs, and continued growth of its TIR AI/ML platform. EBITDA stood at Rs 117.9 crore with a strong EBITDA margin of 75.2 percent, expanding by 1,446 basis points QoQ and 4,609 basis points YoY. Profit before tax rose to Rs 58.62 crore, while net profit came in at Rs 43.88 crore with a PAT margin of 28 percent.
B200 cluster boosts AI cloud business: During the quarter, the company successfully deployed its B200 GPU cluster on the TIR platform, with the new infrastructure contributing to revenue in its very first quarter. This helped the company deliver Q1 FY27 EBITDA equivalent to about 93 percent of its total EBITDA reported in the whole of FY26.
Expanded GPU infrastructure and new subsidiary: The company increased its AI infrastructure to around 5,100 GPUs to support rising demand for AI and machine learning workloads. It also incorporated Sovcloud Technologies Limited as a wholly owned subsidiary to strengthen its business and support future expansion.
Focus on operational excellence and growth: The company continued improving the performance of its large GPU clusters through full-stack optimisation across multiple technology layers while targeting industry-leading benchmarks for NCCL and Model FLOPs Utilization (MFU). It also invested in strengthening its workforce and completed a 10:1 stock split along with its direct listing on the BSE Mainboard during the quarter.
Management Comment
The management said Q1 FY27 was another strong quarter for the company, with revenue growing 4.3 times YoY, EBITDA margin expanding to 75.2 percent, and profit before tax reaching Rs 58.62 crore. It added that the B200 GPU cluster became operational during the quarter, while utilisation across its GPU fleet remained strong due to robust demand from the AI ecosystem. The company said it will continue to focus on expanding its capacity in a disciplined manner throughout the rest of FY27.
About the Company
E2E Networks Ltd is an Indian AI-focused hyperscale cloud provider founded in 2009, specializing in high-performance GPU cloud computing, public cloud, and machine learning infrastructure. You can explore their official portal at E2E Networks or check employee insights on AmbitionBox Overview.
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