Nvidia is deepening its roots in India, announcing a sweeping set of deals with cloud providers, venture capital firms, research institutions, and AI startups as the country positions itself as a major player in the global artificial intelligence race. The announcements cam e We dnesday during India’s AI Impact Summit in New Delhi, a gathering of world leaders and top tech executives aimed at shaping the future of AI. Nvidia CEO Jensen Huang had been expected to attend but pulled out due to what the company described as “unforeseen circumstances.” Nvidia said it is working with five venture capital firms, Peak XV, Z47, Elevation Capital, Nexus Venture Partners, and Accel India, to find and back AI startups at various stages of growth. The company said more than 4,000 Indian AI startups have already joined its global Inception program, which helps young companies build products, grow, and reach customers. The push aligns with India’s growing startup market, where venture investors have been pouring money into tech companies, drawn by a strong IPO market that has been delivering solid returns. As reported by Cryptopolitan, Nvidia is also a founding member of $2 billion India Deep Tech Alliance to mentor emerging AI firms across the country. _*]:min-w-0 gap-3"> Yotta to build Asia’s largest AI hub in a $2 billion deal In one of the biggest deals announced, Indian data center company Yotta Data Services said it will build one of Asia’s largest AI computing hubs using Nvidia’s latest Blackwell Ultra chips . The project will cost more than $2 billion in total. As part of the deal, Nvidia will set up one of Asia-Pacific’s largest DGX Cloud clusters inside Yotta’s infrastructure under a four-year agreement worth over $1 billion. The facility, branded as Shakti Cloud, will run on more than 20,000 Nvidia Blackwell Ultra GPUs and is expected to go live by August. It will be located at Yotta’s campus near New Delhi, with extra capacity coming from its site in Mumbai. Yotta is part of Indian billionaire Niranjan Hiranandani’s real estate group and already operates three data center campuses across India. Nvidia also said it is working with other Indian cloud providers, including Larsen and Toubro and E2E Networks, to deliver AI computing infrastructure across the country. The investments are part of a broader boom in AI spending in India. div]:bg-bg-000/50 [&_pre>div]:border-0.5 [&_pre>div]:border-border-400 [&_.ignore-pre-bg>div]:bg-transparent [&_.standard-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.standard-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8 [&_.progressive-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.progressive-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8"> _*]:min-w-0 gap-3 standard-markdown"> Nvidia’s Nemotron models take aim at India’s language barrier The stakes go well beyond business. The 2026 International AI Safety Report found that while more than half the population uses AI in some countries, adoption rates across much of Africa, Asia, and Latin America likely remain below 10%. India sits squarely in that gap. Part of the problem is language. The world’s biggest AI chatbots do not work in all of India’s 22 official languages, let alone the hundreds of dialects spoken across the country. ChatGPT and Claude currently support around half of them. Google’s Gemini supports nine. “Without tech that understands and speaks these languages, millions are excluded from the digital revolution, especially in education, governance, healthcare, and banking,” Professor Pushpak Bhattacharyya from IIT Mumbai told the BBC last summer. India’s government has recognized the problem and is trying to fix it through its AI Mission , but progress has been slow. That’s where Nvidia emerges as a key driver. The company is also helping Indian companies build AI systems using its Nemotron family of models, which organizations can use to develop chatbots, voice assistants, and AI agents. The models can be trained on India-specific data and support the country’s more than 22 officially recognized languages. Several Indian companies are already using the technology. BharatGen, backed by the Indian government, has built a 17-billion-parameter AI model. Gnani.ai is using it to build a speech model for Indian languages and has cut its inference costs by 15 times, now handling more than 10 million calls per day. The National Payments Corporation of India is exploring using it to support its digital payment systems. Sarvam.ai has trained models across three sizes: 3 billion, 30 billion, and 100 billion parameters, covering 22 Indian languages. As of September last year, India’s government had approved $18 billion worth of semiconductor projects as it works to build a domestic chip supply chain. Prime Minister Narendra Modi’s administration has set a goal of turning India into a global technology superpower. Get seen where it counts. Advertise in Cryptopolitan Research and reach crypto’s sharpest investors and builders.
