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Sarvam, India's full-stack sovereign AI company, has raised $234 million in the first close of its $300 million Series B at a post-money valuation of $1.5 billion, marking one of the largest funding rounds for an Indian AI startup.
According to the company's press release, HCLTech and Bessemer Venture Partners invested in the round, with continued support from existing investors Khosla Ventures and Peak XV Partners. The funding will accelerate Sarvam's work across the AI stack: training and inference infrastructure, frontier model research, and enterprise/government deployments. The company said the investment will fund "continued research on training its next frontier model for agentic, coding, and cybersecurity use-cases, as well as access to compute at scale to expand its forward-deployed motion across key verticals." Sarvam positioned the round as a bet on research-led innovation for India's scale. "We are clear that research-led innovation to create AI that works at India's scale is a very large opportunity. That means models that understand our voices, read our documents, and serve intelligence at a cost every enterprise and government can afford," said Pratyush Kumar, Co-founder, Sarvam. "Building on this template, we are innovating on a full-stack offering for enterprises to own and operate their own sovereign AI." HCLTech is investing $150 million as the lead strategic investor. C Vijayakumar, CEO & MD, HCLTech, said the partnership aims to build a globally competitive ecosystem: "Our investment in Sarvam marks a significant step toward building India's trusted and globally competitive AI ecosystem. By bringing together Sarvam's research in AI models with HCLTech's global presence, we are creating a differentiated full-stack AI platform for enterprises and governments, strengthening our ability to deliver secure, scalable, and responsible AI solutions." Sarvam's models are already shipping at scale. The company released Sarvam 105B, which "matches or outperforms larger reasoning models on knowledge, reasoning, and agentic benchmarks," and Sarvam 30B optimized for the edge. Its Vision model is digitizing over 35 million pages of insurance and land records, while speech models transcribe "over half a million hours of audio each month." Usage is scaling fast. Sarvam's conversational platform now handles over 2 million interactions daily, doubling in two months. Its inference platform processes 10 million API calls daily, tripling in three months. At population scale, multilingual voice agents collected data from 17 million farmers for the Ministry of Agriculture and supported low-cost policy renewals for 45 million policyholders of a leading insurer. In a post on X, Kumar underlined the mission: "Country of India scale cannot rent intelligence. We have to build it ourselves. We are assembling the team, the compute, and the deployment engine to make this happen." (ANI)
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