India’s startup ecosystem raised nearly $11 billion in 2025, but investors wrote far fewer checks and grew more selective about where they took risk, underscoring how the world’s third most-funded startup market is diverging from the AI-fueled capital concentration seen in the U.S.

The selective approach was most evident in deal-making. The number of startup funding rounds fell by nearly 39% from a year earlier, to 1,518 deals, according to Tracxn. Total funding slipped more modestly — down just over 17% to $10.5 billion.

That pullback was not uniform. Seed-stage funding fell sharply to $1.1 billion in 2025, down 30% from 2024, as investors cut back on more experimental bets. Late-stage funding also cooled, slipping to $5.5 billion, a 26% decline from last year, amid tougher scrutiny of scale, profitability, and exit prospects. However, early-stage funding proved more resilient, rising to $3.9 billion, up 7% year-over-year.

**Image Credits:**Tracxn

“The capital deployment focus has increased towards early-stage startups,” said Neha Singh, co-founder of Tracxn, pointing to growing confidence in founders who can demonstrate stronger product–market fit, revenue visibility and unit economics in a tighter funding environment.

The AI quest

Nowhere was that recalibration clearer than in AI, as AI startups in India raised just over $643 million across 100 deals in 2025, a modest 4.1% increase from a year earlier, per Tracxn data shared with TechCrunch. The capital was mainly spread across early and early-growth stages. Early-stage AI funding totaled $273.3 million, while late-stage rounds raised $260 million, reflecting investor preference for application-led businesses over capital-intensive model development.

This was in sharp contrast to the U.S., where AI funding in 2025 surged past $121 billion across 765 rounds, per Tracxn, a 141% jump from 2024, and was overwhelmingly dominated by late-stage deals.

“We don’t yet have an AI-first company in India, which is $40–$50 million of revenue, if not $100 million, in a year’s time frame, and that is globally happening,” said Prayank Swaroop, a partner at Accel.

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India, Swaroop told TechCrunch, lacks large foundational model companies and will take time to build the research depth, talent pipeline, and patient capital needed to compete at that layer — making application-led AI and adjacent deep-tech areas a more realistic focus in the near term.

This pragmatism has shaped where investors are placing longer-term bets outside core AI. Venture capital is increasingly flowing into manufacturing and deep-tech sectors. These are some of the areas where India faces less global capital competition and has clear advantages in talent, cost structures, and customer access.