Fundamentum launches Fund III, a Rs 2,200 crore growth-stage technology fund with a Rs 400 crore greenshoe option, anchored by Nandan Nilekani as a major investor and led by Sanjeev Aggarwal with Prateek Jain, Mayank Kachhwaha, and Sanjay Chaturvedi as general partners.

The fund aims to serve India’s next 400 million internet users with products and user experiences tailored to non-metro, urban-adjacent audiences.

Exit options are broadening beyond IPOs, with growth-stage liquidity through large private equity, global institutions, and secondary transactions.

In consumer tech, AI is expected to disrupt content and generation, with Kuku FM as an example, and AI to transform interactions with commerce via edge devices.

Fund I and Fund II have deployed 17 investments across consumer internet, Bharat-focused apps, fintech, B2B commerce, and enterprise tech, including Kuku, Spinny, PharmEasy, Stable Money, Wishlink, and AppsForBharat.

Fund III will emphasize India-first product development and regionalisation, leveraging AI and targeting expansion into similar emerging markets rather than reliance on Western markets.

AI thesis prioritizes India-specific narrow language models and leveraging AI in IT services and AI-first business processing for growth.

Aggarwal envisions India as a forward deployed engineer factory for the world, training and exporting models with strong local industry support.

Fintech thesis centers on using mature digital public infrastructure like UPI and account aggregators to broaden access to wealth management and insurance, aiming to reach up to 400 million new users.

Aggarwal notes that recent high IPO valuations pressured post-listing performance and calls for more disciplined pricing and valuation practices.

Nilekani emphasizes building enduring institutions, while Aggarwal supports entrepreneurs through scale-up journeys beyond capital.

Fundamentum will maintain an operator-led approach with board seats and hands-on support on fundraising, leadership hiring, org design, and expansion, while focusing on AI applications for Indian use cases rather than foundational AI models.