Nvidia embeds itself at the heart of India’s sovereign AI push

Once recognized mainly for its graphics processing units, Nvidia has now positioned itself as a critical player in the burgeoning artificial intelligence sector, with India emerging as a pivotal market in this growth trajectory. As the Indian government accelerates its IndiaAI Mission to establish a robust domestic AI framework, Nvidia is embedding itself throughout the nation's AI ecosystem, encompassing everything from local computing infrastructure and indigenous large language models to enterprise-level implementations led by major IT service firms. Nvidia's chips and software solutions have become the preferred choice for hyperscalers, startups, and governmental bodies globally, and this trend is mirrored in India, where both public and private sectors are investing significantly in building local AI capabilities. "AI is becoming as essential as electricity or the internet was in earlier times. Consider AI as a five-layer cake, starting with energy, followed by chips, infrastructure, model development, and finally, applications. Each layer has its own unique ecosystem, and we are collaborating with India's tech leaders at every level of this stack," explained Vishal Dhupar, Managing Director for South Asia at Nvidia. A central aspect of India's AI strategy focuses on minimizing dependence on foreign cloud services for critical operations. Nvidia aims to be the technological backbone of this initiative through strategic partnerships with domestic cloud providers. The company is collaborating with Indian firms like Yotta, Larsen & Toubro (L&T), and E2E Networks to establish large-scale sovereign computing capabilities. Notably, Yotta is enhancing its Shakti Cloud with over 20,000 Nvidia Blackwell Ultra GPUs, positioning it as one of the largest AI computing platforms within India. Concurrently, E2E Networks is constructing a GPU cluster based on Nvidia's Blackwell architecture at L&T’s Vyoma Data Center in Chennai, integrating Nvidia HGX B200 systems, AI Enterprise software, and access to Nemotron models. These initiatives are set to facilitate advanced AI training and inference operations domestically, addressing the vital needs for data sovereignty and national security. Nvidia's impact extends well beyond hardware. The company’s ecosystem encompasses chips, software frameworks, datasets, and models, thereby enabling developers to transition seamlessly from infrastructure to applications. As the development of AI models becomes increasingly central to national capabilities, Indian startups and government-affiliated projects are leveraging Nvidia’s open Nemotron models and NeMo tools. For example, Sarvam.ai is constructing a comprehensive generative AI platform for India, utilizing NeMo Curator to compile high-quality multilingual datasets alongside selected Nemotron resources. According to Nvidia, these foundational models have been pre-trained from scratch across a range of sizes, from 3 billion to 100 billion parameters, using the NeMo framework and Megatron-LM, followed by post-training on H100 GPUs through collaborations with cloud partners, including Yotta. Additionally, the government-supported BharatGen consortium has developed a 17-billion-parameter mixture-of-experts model using NeMo for both pre-training and post-training phases, while the AI company Chariot is working on an 8-billion-parameter real-time text-to-speech model specifically designed to cater to India’s diverse languages. "We recently launched Nvidia Nemotron-3 Nano, an exceptionally efficient language model, and I’m excited to announce that larger versions, Super and Ultra, will be available soon," Dhupar stated. India’s global system integrators, which have long been the backbone of the country's technology exports, are also capitalizing on Nvidia’s enterprise software, datasets, and models to offer AI solutions globally. "India is crucial in how enterprise AI is constructed and scaled worldwide. Many of the largest AI systems are developed and deployed by global system integrators based in India, catering to international clients at an immense scale," Dhupar remarked. Firms such as Infosys, Tech Mahindra, Persistent Systems, and Wipro are employing Nvidia AI Enterprise to implement AI agents across various industries, including finance, telecommunications, healthcare, and drug discovery. For instance, Infosys has developed a 2.5-billion-parameter coding model using the NeMo framework, integrating it into its Topaz platform to support agent development, code generation, and software engineering processes, trained on curated code datasets. Nvidia's expanding role in infrastructure, model development, and enterprise deployment signifies that the company is evolving beyond just being a hardware supplier in India’s AI landscape. It is increasingly becoming a fundamental layer in shaping the construction, training, and deployment of artificial intelligence for both domestic initiatives and international markets.