Right at the dawn of 2024, India birthed its first unicorn of the year, that too an artificial intelligence (AI) unicorn — Krutrim AI. Founded a year ago by Bhavesh Agarwal of Ola fame, the start-up raised a whopping $50 million to become the country’s third-fastest venture to hit billion-dollar valuation.
This comes amid a prolonged ‘funding winter’ in the Indian start-up segment. Investors — after the funding high of 2021-22 had worn off — are tightening purse strings, increasing scrutiny, and getting valuations back to ground over the last two years. But start-ups in the AI sphere are bucking this trend.
According to data intelligence platform Tracxn, AI infrastructure and generative AI companies in India bagged their highest annual funding in 2022, with $402 million raised in all, while 2023 mopped up $146 million.
This sector witnessed its highest monthly funding till date in April 2022, at $333 million. The following year, December raked in the most funds, at $44 million. This year, within just two months, AI start-ups in India have attracted $55 million in funding.
There are more than 550 Indian companies in the AI infrastructure and generative AI space, with cumulative funding exceeding $1.2 billion till date, says Neha Singh, co-founder of Tracxn.
Big money, small window
The fear of missing out, or FOMO in today’s lingo, is believed to be driving much of this funding for AI ventures. Venture capitalists have been vying to spot the next big winner ever since the launch of OpenAI in 2022 pushed generative AI technology to the forefront as a major game changer.
“We can’t escape the wave sometimes, because there are going to be some big winners. It is a great sector — like OpenAI was the big winner, India will also have its moment. There is a lot of value to be had here, so you can’t not play sometimes. There is also a lot of liquidity, as there is dry powder [unused funds] in the market, with fund houses sitting on capital,” says Madhu Shalini Iyer, Managing Partner of venture capital firm Rocketship.vc.
V Laxmikanth, Managing Partner, Pavestone Capital, sounds a similar note, saying, “In just the past year, there has been four times more funding in gen AI companies, according to our market research. I think the space is still not fully developed and a lot of money is chasing very few properties. The market is currently overhyped; for anything that’s happening in gen AI there is a FOMO effect, as people don’t want to miss out.”
While AI start-ups have been around in India for some time now, the new generative AI wave has spawned a clutch of related start-ups in the recent past. Jaspreet Bindra, founder of AI consultancy Tech Whisperer, points to two types of start-ups — large language models or LLMs (SarvamAI, KrutrimAI, AI4Bharat); and application-based start-ups built on OpenAI, Bard, and other open source AI platforms. “There is a need for Indian start-ups to build LLMs to suit the unique requirements of our datasets. While there is hype, it is (also) necessary to drive innovation in the country,” he argues.
Amid the scramble for a slice of the AI pie, valuations are shooting up. As Iyer cautions, “There are a lot of people just overlaying elements and calling it gen AI, while those applications may not be required. Just because it has gen AI slapped on it, people are giving it crazy valuations; but there must be value that’s being created.”
While other start-ups face questions over their cash flow generation and path to profitability ahead of their valuation, the AI start-ups are receiving valuations on the presumption of the future potential of the underlying technology, which still remains unknown, notes Laxmikanth.
Echoing this, Tracxn co-founder Singh says, “While in other industries we have seen the valuations of many start-ups sliding significantly due to investor scrutiny, there is less scrutiny for AI start-ups due to the excitement and optimism around the potential of this technology in the coming years.”
Countering this view, Arko Chattopadhyay, co-founder of start-up Xylem AI, says, “There is hype, but the funding is not going to just anyone. Previously investors would fall off their chairs if a big cheque was asked, but today they understand that big-ticket investment is required to build in this (AI) space. Raising a seed round has become easier; even Series B investors are ready to make seed investments because everybody wants to enter early, before it gets costlier going forward.”
If the trend in favour of AI funding continues, there could be a repeat of 2020-21, marked by over-valuations, Iyer says. “There is too much noise and there can’t be too many winners. A lot of risk is associated with investing, as one has to be sure that the company being picked is actually building something useful. How you separate the signal-to-noise ratio is important,” she adds.
The veterans, however, know from past experience that the funding momentum will eventually plateau. Laxmikanth trots out the standard theory of diffusion of innovation, according to which, after the hype dies down the survivors in the space will do well.
Chattopadhyay, on the other hand, doesn’t foresee the plateauing as the end of the hype cycle but rather a tapering of the investment needed to drive innovation once the required infrastructure has been built.