AfterQuery reportedly becomes Y Combinator’s fastest-ever unicorn, now valued at $3.2B
TechCrunch Julie Bort ● Covered by 2 sources
AfterQuery’s new round reportedly puts it at $3.2 billion. That makes it Y Combinator’s fastest path from launch to unicorn, in about 18 months.
Based on reporting by TechCrunch, Julie Bort — read the original for the full story.
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AfterQuery, the AI training-data startup, has reportedly jumped to a $3.2 billion valuation after its latest funding round. That is a sharp leap from April, when it said it had raised a $30 million Series A at a $300 million valuation. Five months later, the number is more than 10 times higher.
Y Combinator partner Gustaf Alströmer called it the fastest any startup has gone from launch to unicorn status in the accelerator’s history. The company’s founders are 22 and 23, and they went through Y Combinator’s Winter 2025 cohort just 18 months ago. That pace is the real story here: not just a hot valuation, but how quickly one has arrived.
In April, AfterQuery said its annualized revenue run rate had reached $100 million and that it was working with many of the biggest labs. It has also named Nvidia, Legora, and the Korean AI lab Motif Technologies as customers. Forbes first reported the round.
AfterQuery sits in a familiar corner of the AI boom. Like Mercor and Scale, it relies on knowledge professionals — doctors, lawyers, and other specialists — for model training. But its pitch is a little different. Instead of teaching models to answer questions accurately, it trains them to work like professionals do when they finish tasks, which the company describes as encoding the patterns, decisions, and reasoning of top practitioners. That is a much broader ambition, and one that clearly has investors paying attention.
My take — AI-written commentary, not fact-checked reporting
This is what happens when AI money starts chasing workflow imitation instead of just chatbots: the valuations get stupider, faster. The market loves anything that sounds like “expert reasoning,” because it’s easier to sell than raw model quality and just vague enough to keep everyone squinting. The boring part is that it probably works better than most of the grand AI theater.
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