India AI Mission Empanels Yotta To Accelerate AI Adoption With Advanced GPU, Cloud Services

Yotta Data Services has been empanelled under the India AI Mission to provide advanced GPU capacity, artificial intelligence platforms, and sovereign cloud infrastructure to accelerate AI-driven innovation in India.

The AI and cloud services provider will offer more than 50% of advanced GPU compute capacity for the Government of India initiative, which will soon be available via the upcoming India AI Mission portal.

With over 9,216 advanced GPUs, committed to the India AI Mission (and to be made available in phases), including 8,192 Nvidia H100 GPUs and 1,024 L40S GPUs, Yotta’s Shakti Cloud will deliver ultra-low latency, high-performance AI compute power to government entities, startups, and enterprises. The offerings include AI Labs for students, AI workspaces, GPU-as-a-Service, and API endpoints for AI models. All these services are available from Yotta’s NM1 data centre. 

Yotta will support the India AI Innovation Centre’s latest initiative to develop indigenous foundational models. With its hyperscale data centres and AI-ready cloud infrastructure, the company offers high-performance computing capabilities for training large multimodal models, large language models, and small language models.

By offering access to GPU and TPU clusters, the company removes the need for heavy upfront investments in hardware, enabling Indian researchers, startups, and entrepreneurs to accelerate AI development. Moreover, its indigenous data hosting solutions allow AI models to be trained on locally stored datasets, adhering to data sovereignty regulations. 

Yotta has also empanelled the services of its partners, Microsoft Azure AI, Sarvam AI, and Hanooman AI with the India AI Mission to accelerate AI advancements within India’s sovereign cloud. These partnerships will enhance AI accessibility, foster talent development, and allow organisations to leverage AI tools within India’s sovereign cloud ecosystem. 

The initiative will place financial resources directly in the hands of researchers, startups, and enterprises that require GPU access for training and deploying AI models. This enables them to pay for AI services provided by the private sector, fostering a competitive and sustainable AI ecosystem.