Of the estimated 2,900 AI businesses in the country, 605 have received US$ 6.57 billion in venture capital and private equity investments, says Tracxn data.

The biggest challenge for early-stage startups is moving from a promising pilot to a paying customer

- Aksheshkumar Ajaykumar Shah, Founder and CEO, Cogniify.ai

The government too has committed about ₹10,372 crore to the IndiaAI Mission, providing support with computing power, startup financing, and application development.

But computing and early-stage capital won’t be enough to help these AI startups commercialise. 

The question is what happens after a prototype is ready. Who will deploy it, pay for it, and help the company scale?

“The biggest challenge for early-stage startups is moving from a promising pilot to a paying customer,” Aksheshkumar Ajaykumar Shah, Founder and CEO, Cogniify.ai, which helps businesses apply AI in their operations, told The Secretariat.

The shift may prove to be the next big hurdle for the country’s fledgling AI ecosystem.

“AI startups in India are not short on ideas. The real funding gap starts when you try to take a working prototype into real-world production,” cautioned Rajat Srivastava, Founder, CEO and CPO, Df-OS.

Institutional Support

India has started building institutional support.

By June, the IndiaAI Mission had crossed 45,000 graphics processing unit (GPUs) of shared computing power. By August, 237 projects had used subsidised AI computing amounting to 93.18 lakh GPU hours.

AI startups in India are not short on ideas. The real funding gap starts when you try to take a working prototype into real-world production

- Rajat Srivastava, Founder, CEO and CPO, Df-OS.

India’s strategy has been to link AI advancement to real-life public sector challenges. 

The IndiaAI Application Development Initiative aims to facilitate the development, scaling and deployment of AI solutions in key industries. The government also says its startup financing pillar is designed to fill the funding void, from prototyping to commercialisation.

Some movement from development to deployment does exist. 

In August, the IndiaAI initiative developed 62 AI prototypes and deployed 20 AI solutions in public sector institutions. The Mission also identified 762 AI use cases across 62 ministries and departments.

Such moves do allow startups to test their technology against real problems, but the entire challenge of commercialisation cannot be addressed through public sector deployment. 

Private sector customers are essential, as are follow-on funding, and the ability to prove a product’s viability at scale.

What US, China Do

In several countries, mechanisms exist to help startups make the transition.

A comparison with the US and China is particularly relevant, as they have the most well-established AI ecosystems. While the US is home to leading models like ChatGPT and Gemini, China has DeepSeek.

The US, for example, has two technology development programmes - the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) - structured in three phases.

Phase I establishes proof of concept, Phase II supports further technology development, and Phase III takes the technology towards commercialisation through private-sector funding or federal contracting without using SBIR/STTR funds for the final stage.

The National Science Foundation (NSF), which runs America’s Seed Fund, has awarded over 4,000 grants to startups and small businesses since fiscal year 2016 and supported nearly 400 companies annually through the fund. 

Since 2013, South Korea’s Ministry of SMEs and Startups has supported some 5,000 startups, mobilising US$ 15.5 billion in investment.

Its Tech Incubator Program for Startups (TIPS) brings private investors into the process at an earlier stage, with accredited operators investing in startups before they receive linked public R&D support. 

For startups to scale up and expand overseas, the country is now extending support through Scale-Up TIPS and Global TIPS.

My real concern is Series A. We have plenty of angel and seed money, and a reasonably active growth market 

- Vishnu Rajeev, Investment Partner, Speciale Invest

China, meanwhile, is using patient capital as a distinct strategy. This involves long-term investment where funders don’t expect quick returns. Its national Venture Capital Guidance Fund has a 20-year lifespan.

The models differ, but the underlying thinking is similar: startups need support even after demonstrating that their technology works.

That Big Cheque

So how can India’s AI startups secure bigger corporate investments?

The importance of this becomes clear at Series A, which is a startup's first large round of venture capital funding after the seed stage. 

“My real concern is Series A. We have plenty of angel and seed money, and a reasonably active growth market but very few funds writing the US$ 10-15 million cheque that a company needs after 18 months of proof,” Vishnu Rajeev, Investment Partner, Speciale Invest, told The Secretariat.

The additional capital is required for computing, enterprise integration, and customer acquisition before revenues become significant.

The increase in funding value alongside a lower number of funding rounds could be seen as a sign of the AI ecosystem moving towards greater maturity

- Ajay Modi, Director, Piper Serica

Sarvam AI is an Indian AI startup that has moved beyond early-stage, developing solutions around language access and enterprise automation. Its products are being used across banking, insurance, and government. 

The company raised US$ 234 million in the first close of its US$ 300 million Series B in 2026, led by HCLTech. The total valuation of Sarvam AI is around US$ 1.5 billion. Its growth shows how solving real-world problems, securing deployments, and demonstrating scale can help an AI startup attract larger follow-on capital. 

The funding market is also becoming more concentrated.

“The increase in funding value alongside a lower number of funding rounds could be seen as a sign of the AI ecosystem moving towards greater maturity,” said Ajay Modi, Director, Piper Serica, which invests in early-stage, technology-focused Indian startups.

Clearly, India requires a better pipeline between prototype funding and pilots, pilots and customers, and early funding and follow-on funding.