VCs Use Tranched Rounds to Inflate AI Valuations — Even for Startups With No Product
A New Valuation Trick Is Reshaping AI Funding
Venture capital's latest maneuver is raising eyebrows across the startup ecosystem. According to a Bloomberg report published today, October 22, 2026, investors are increasingly relying on "tranched" or "two-step" funding rounds to drive AI startup valuations into the billions — sometimes for companies that are just weeks old and have no product, no revenue, and not even a public website.
How the Mechanic Works
In a conventional funding round, every investor pays the same price per share, locking in a single valuation. The tranched structure breaks that norm: a startup closes an initial slice of a round at one price, then deliberately keeps the round open for follow-on closes at rapidly escalating prices as more investors compete to get in. The result is that the same legal round can imply wildly different valuations depending on which tranche a firm joined.
Bloomberg's reporting highlights Emulate, a UK-based AI startup founded in August 2026 by alumni of Google DeepMind. The company has no product and no website, yet investor competition is so fierce that its valuation has been driven into the billions. Another case study cited is Ineffable Intelligence, whose valuation reportedly surged from $55 million to $4 billion within a single tranched round — a near-73x step-up inside one financing event.
The Broader AI Valuation Landscape
These extreme examples sit atop an already frothy market. Data tracked by analysts at genztech.blog shows that through mid-October 2026, some $5.47 billion flowed into startups in October alone, with roughly $2.34 billion going to AI model, infrastructure, and application companies. Just yesterday, October 21, Bloomberg reported that Flapping Airplanes — a one-year-old AI research lab with no commercial product — raised $1 billion at a $6 billion valuation led by Index Ventures and Lux Capital, with Sequoia, GV, and Kleiner Perkins also participating. Its valuation quadrupled from a prior round in January 2026.
Meanwhile, valuation benchmarks compiled by Value Add VC show that foundation model labs are trading at revenue multiples between 30x and 120x, with a median around 37.5x — compared to roughly 3.4x for median public SaaS. AI-native SaaS companies command 15x–30x, while commodity AI wrapper apps with no proprietary IP are compressing toward 8x–15x, approaching traditional SaaS territory.
Structural Risk Hiding in Plain Sight
Multiples.vc notes that public software investors are now pricing companies based on AI application potential and disruption risk — not just total addressable market size. That shift is flowing into private markets, where the tranched structure lets investors at each successive close justify a higher headline number without any fundamental change in the underlying business. As Startup Fortune observed today, the tactic highlights how intense competition for elite AI talent can push capital to accept terms that would have been unthinkable for any other sector. Whether this represents rational option-pricing on transformative technology or a repeat of late-cycle excess is the defining debate in venture right now.