E2E Networks Share Price hits 10% Upper Circuit on ₹177 Crore Order from MeitY’s IndiaAI Mission

E2E Networks Limited has announced a major development under Regulation 30 of SEBI (LODR) Regulations, 2015. The company received an order from IndiaAI Mission, an Independent Business Division within Digital India Corporation under the Ministry of Electronics and Information Technology, for the immediate allocation of high-performance GPU resources. This marks a pivotal step in India’s ambition to build indigenous AI capabilities.

GPU Allocation for Building a Foundational AI Model

According to the official intimation, E2E Networks will provide H100 SXM and H200 SXM GPU resources with an Infiniband (IB) network on a single fabric. The allocation spans 360 days, amounting to 1,29,94,560 GPU hours in total. The overall contract is valued at approximately ₹177 crore.

These GPUs are being allocated specifically to Gnani AI for the development of India’s foundational AI model, reinforcing the country’s efforts to establish leadership in artificial intelligence infrastructure and research.

Strengthening India’s AI Ecosystem

This engagement not only highlights the trust placed in E2E Networks but it also elevates its positioning within India’s AI infrastructure ecosystem. With GPU resources being an important component for training advanced AI models, the allocation is expected to accelerate the progress of India’s AI initiatives under the IndiaAI Mission.

The company has confirmed that the order is purely domestic, not a related party transaction, and it does not involve any promoter or group company interest.

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E2E Networks Share Price Performance 

As of September 03, 2025, at 11:31 AM E2E Networks share price is trading at ₹2,643.40 per share, locked at an upper circuit limit of 10% above the previous day's closing price.

Conclusion

By securing this strategic allocation, E2E Networks is contributing to India’s long-term vision of building robust AI capabilities. The contract reflects both the company’s growing importance in the AI infrastructure space and the government’s focus on fostering technological self-reliance.

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