India’s Deeptech Boom Has a Problem: $11.4 Billion Raised, But Who’s Funding the Beginning?

India’s deeptech companies have attracted $11.4 billion in private-equity and venture-capital funding across 957 deals since 2015, according to the Indian Venture and Alternate Capital Association’s Bharat DeepTech Report 2026. The IVCA Bharat DeepTech Report 2026 funding figures also point to an India deeptech early-stage funding gap.

The report identifies 2025 as the sector’s biggest funding year yet. Investors deployed $2.96 billion across 189 deals, [Fortune India reported](https://www.fortuneindia.com/startups-news/indias-deeptech-funding-hits-record-high-as-capital-shifts-to-frontier-technologies-report/154284), as capital flowed toward frontier fields including artificial intelligence and semiconductors.

The figures point to a growing role for deeptech in India’s venture market, but they also highlight a persistent shortage of money for technologies at the earliest stages of development. IVCA found that only 15% of surveyed deeptech funds invest at technology-readiness levels, or TRLs, 1 through 3. Those stages generally encompass foundational research and the work needed to establish an initial proof of concept.

Investor participation increases substantially once a technology has moved beyond that early phase. According to [Press News India’s coverage of the IVCA report](https://www.pninews.com/amp/india-deeptech-investments-hit-11-4-billion-2025-marks-record-year-bharat-deeptech-report-2026-by-ivca/), about 60% of funds invest at TRLs 4 to 6, when technical concepts are being tested and validated. Some 69% invest at TRLs 7 to 9, the stages more closely associated with deployment, productisation and commercial use.

That pattern creates a financing challenge for startups built around scientific advances rather than conventional software products. Companies developing new materials, biotechnology, semiconductor systems or AI infrastructure can require extended research, specialist equipment and technical validation before they can show the traction typically sought by commercial investors.

For AI-focused deeptech companies, the distinction can be especially important. Building applications on existing models may be comparatively fast, while ventures creating new hardware, core models, data infrastructure or specialized systems can face longer development cycles and heavier capital needs. The IVCA findings suggest that investors are more likely to finance such businesses after they have cleared an initial technical threshold.

The early-stage shortfall is not the sector’s only capital constraint. [Outlook Business reported](https://www.outlookbusiness.com/news/indias-deeptech-funding-crosses-11-bn-as-investors-turn-to-ai-semiconductors) that the study also identified gaps in growth-stage financing and exits. That means founders may encounter pressure both while translating laboratory research into a demonstrable technology and later, when seeking capital to expand operations.

India’s 2025 funding total nevertheless indicates sustained private-market interest in technologies with longer-term commercial potential. The next question for the sector is whether more of that capital reaches researchers and startups before their technologies have been substantially de-risked.