AI NewsPeak XV raises $1.3B, doubles down on AI as global VC rivalry in India heats up

Peak XV raises $1.3B, doubles down on AI as global VC rivalry in India heats up

12:21 AM IST · February 21, 2026

Peak XVannounced on Friday that it has raised $1.3 billion across new India and Asia-focused funds. The firm, which now manages more than $10 billion in assets, is sharpening its focus on artificial intelligence and cross-border bets amid intensifying competition for deals in the region. The capital will be deployed across its India seed and venture funds as well as its APAC vehicle. A majority is earmarked for India, with the firm expecting to invest the pool over the next two to three years, managing director Shailendra Singh said in an interview on Friday. Peak XVsplit from Sequoia Capital in 2023, in an effort to separate the India-focused portions of Sequoia’s portfolio. The firm now counts more than 450 portfolio companies across fintech, software, and consumer internet, spanning seed to growth stages. The firm’s new fundraise comes as New Delhi hosts theAI Impact Summit, drawing major technology players including OpenAI, Anthropic, and Google. At the event,General Catalyst outlined plans to invest $5 billionin the country over the next five years, sharply increasing its earlier commitment to the market. Singh said Peak XV is not trying to match rivals dollar-for-dollar, emphasizing that the firm’s priority is generating strong returns rather than maximizing assets under management. The firm will continue to size its funds based on where it sees the best opportunity to deliver “high-performing funds,” he said. He added that Peak XV is still building its presence in the U.S. and is selective about where it competes. “In the U.S. market, we are an underdog — and that’s great,” Singh said, adding that the firm is focusing on areas where its experience in software, developer tools, and fintech gives it an edge. The latest fundraise follows a period of leadership changes at Peak XV, including therecent departuresof senior partner Ashish Agrawal and investors Ishaan Mittal and Tejeshwi Sharma. Singh told TechCrunch the firm retains significant experience on its leadership team, noting that five of its seven managing partners have been with Peak XV for more than a decade. The broader Peak XV team includes more than 30 full-time investors, with about a dozen leading investments across its markets. Peak XV has returned more than $7 billion in cash to investors since inception, Singh said, adding that 35 of its portfolio companies have gone public. He declined to specify distributions since the firm’s split from Sequoia Capital. In September 2024, TechCrunch reported that the firm hadreturned about $1.2 billionin the year. Ahead of the current raise, Peak XV’s prior fund wassized at $2.85 billionin late 2021, before the firm split from Sequoia Capital. That figure was later reduced to about $2.4 billion as part of what Singh described as a disciplined approach to capital. The earlier pool included Peak XV’s India growth strategy, and Singh said the firm does not plan to raise a new growth fund until more of that dry powder is deployed. Singh expects to deploy the new capital primarily into AI, fintech, and consumer startups, while also seeing emerging opportunities in deep tech. The firm has made more than 80 investments in AI startups to date. He added that the U.S.-India ties are becoming increasingly important as more founders in the region build for global markets.

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Adaption aims big with AutoScientist, an AI tool that helps models train themselves

For years, AI researchers have anticipated the moment when AI systems will be able to improve themselves better than humans could. With investors pouring money into a new generation of research-driven AI labs, there are more resources than ever available to pursue the goal. Now, one of those neolabs has taken a major step towards making it real. On Wednesday,Adaptionintroduced a new product calledAutoScientistthat helps models learn specific capabilities quickly by using an automated approach to conventional fine-tuning. The techniques are applicable to a wide range of fields, but the Adaptation team is particularly focused on the potential for speeding up and easing the process of training and fine-tuning a frontier-level AI model. According to co-founder and CEO Sara Hooker, who previously worked as VP of AI research at Cohere, AutoScientist represents a new way to approach the AI training process. “What’s super exciting about it is that it co-optimizes both the data and the model, and learns the best way to basically learn any capability,” Hooker told TechCrunch. “It suggests we can finally allow for successful frontier AI trainings outside of these labs” AutoScientist builds on the company’s existing data offering,Adaptive Data, which aims to make it easier to build high-quality datasets over time. AutoScientist, meanwhile, is designed to turn those continuously improving datasets into continuously improving AI models. “Our view at Adaption is that the whole stack should be completely adaptable, and should basically optimize on the fly to whatever task you have,” Hooker says. Of course, that approach will only be as good as the results. In its launch materials, Adaption boasts that AutoScientist has more than doubled win-rates across different models — impressive numbers, but difficult to put into context. Since the system is built to adapt models to specific tasks, conventional benchmarks like SWE-Bench or ARC-AGI aren’t applicable. Still, Adaption is confident that users will see the difference once they try AutoScientist out — so confident that the lab is making the tool free to use for the first 30 days after its release. “The same way that code generation unlocked a lot of tasks, this is going to unlock a lot of innovation at the frontier of different fields,” Hooker says.

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