'Deeptech does take a J curve,' Lightspeed’s Hemant Mohapatra on the strategy behind deeptech funding

India’s deeptech funding conversation is shifting away from how much capital is available to who it is backing, and for how long. As startups in deeptech bear long gestation cycles and heavy upfront costs, investors are rethinking a model built around deployment targets and sector allocations.

At the core of this rethink is the recognition that deep tech cannot be funded like consumer internet or SaaS. Unlike businesses that show early revenue traction, deeptech companies often spend years building technology before commercial outcomes are visible. As Hemant Mohapatra, Partner at Lightspeed India Partners explained, “Deeptech does take a deep J curve," speaking on the sidelines of India Ascends 2026.

That J-curve, marked by zero revenue and sustained burn, is forcing funds to focus less on capital availability and more on founder conviction. Rather than announcing dedicated pools for emerging sectors, investors are increasingly backing individuals who are starting companies irrespective of market cycles. “Just because you got capital available doesn't mean founders are going to choose to start a company,” Mohapatra said. “The right kind of founders just start companies because they want to start a company. The capital will chase them.”

This approach has implications for how deeptech funding is structured going forward. With growth-stage capital slowing across the ecosystem, startups with long development timelines are vulnerable if early backers cannot stay the course. Funds that can support companies across multiple stages — rather than relying on external growth investors — are emerging as key enablers in this cycle.

Founder quality has also become central to investment decisions. Technical depth alone is no longer enough to sustain belief through years of uncertainty. “It's not like an engineer. That's not enough,” Mohapatra noted, highlighting the importance of founders who can build markets, raise capital and convince customers to adopt unproven technologies.

The shift is also visible in where capital is flowing. AI investments, which until two years ago were concentrated in infrastructure and foundation layers, are now increasingly focused on applications.

As deep tech matures, funding models are becoming more selective and more patient. The next phase is unlikely to be defined by larger cheques or broader mandates, but by conviction capital, backing founders capable of carrying belief through the deepest part of the curve, long before revenues arrive.