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In the world of startup valuations, there’s generative AI—and everything else

Valuations of generative AI companies have been climbing while non-AI startups watch their prices drop.

Rewind founder Dan Siroker (Sportsfile/Getty Images)

If you talk to many early-stage investors, they’ll say they’re now living in two different worlds.

Part of their day is filled with reviewing pitches of startups that show the exciting potential of generative AI, and the other part is spent helping their existing portfolio companies survive the slump.

This dichotomy between generative AI and all other startups is evident in valuations data.

Compared to 2022, median pre-money valuations for early-stage rounds of generative AI companies have jumped by 16% so far this year, according to PitchBook data. Meanwhile, prices for all other startups raising a Series A or Series B have dropped by nearly 24%.

“The bifurcation is huge,” said Sundeep Peechu, a general partner at Felicis Ventures. “There is a general euphoria that, ‘wow, generative AI has revolutionary potential.’”


Some generative AI startups with no revenue at all can now raise Series A rounds at valuations of around $250 million, according to Peechu.

Rewind, a startup that records and makes searchable all meetings, emails and electronic interactions, fetched a $350 million valuation from NEA, based on revenue of only $700,000, The Information reported. Other investors were also willing to assign the startup a price tag of as much as $1 billion, Rewind founder Dan Siroker told The Information.

In another example, LangChain, an AI startup with “minimal” revenue, has snagged a valuation of more than $200 million in a round led by Sequoia, Business Insider reported.

But the valuation environment looks very different for non-AI companies.

Yash Patel, a general partner at Telstra Ventures, said the best Series A startups could command a 10x annual recurring revenue valuation, but he is increasingly seeing early-stage startups raising capital at valuations that are only 5x next-12-months ARR.

“We expect a company to grow 300% a year at the minimum,” said Patel. That means that a Series A company with about $1 million in revenue and expanding at that rate can expect a pre-money valuation of $15 million, a far cry from the lofty prices assigned to their generative AI counterparts.

Growing pains

Some investors say that the pool of companies that qualify for Series A funding has been shrinking recently as revenue growth becomes more challenging.

“I’m seeing a lot more companies going out to raise a Series A that are frankly not ready to raise a Series A,” said Julius Schwerin, a partner at a venture firm RTP Global, “The quality of companies raising is not where it was even during the boom time of VC in last year or two.”

As most corporate customers have switched to cost-cutting mode, the startups that sell to them have found growing revenue at a good clip is more challenging. Schwerin said he is seeing a slowdown in sales growth across RTP’s portfolio of 110 companies.

Recent data from Kruze Consulting, an accounting firm that works with over 750 seed through Series C companies, shows that revenue growth for early-stage startups dropped significantly in 2022. At the end of 2021, Kruze’s SaaS customers grew about 100% in the year, but by the end of 2022, revenue increases slowed to less than 60%. And growth for ecommerce startups almost screeched to a halt.

Since fewer companies are growing at a pace that can attract Series A rounds, Schwerin expects the graduation rate from seed to Series A rounds to fall significantly in the coming quarters.

One thing is clear, investors are measuring generative AI and all other startups on very different criteria: the first on sheer potential and the latter on cold, hard revenue.

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    Written by Marina Temkin
    Marina Temkin covered the venture capital ecosystem from 2021 to 2024, based in San Francisco. Previously with Venture Capital Journal, Marina wrote about the VC industry, and she was a reporter with Mergermarket in New York and San Francisco. She also has been a financial analyst and is a CFA charterholder. Marina received an economics degree from the University of California, Davis, and she attended the CUNY Graduate School of Journalism.
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