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FollowingAfterQuery, an 18-month-old AI startup, is valued at $3.2 billion in a new round of funding, it was reported on Monday. That's more than ten times the $300 million valuation five months ago-when the company completed a $30 million Series A funding round, an early funding stage when startups sold part of their stake to gain growth capital.
This leap makes AfterQuery the fastest start-up to unicorn in Y Combinator history, according to YC partner Gustaf Alströmer. AfterQuery declined to comment on the report. A source said that the company has achieved profitability and has identified a lead investor for this round of financing.
Spencer Mateega and Carlos Georgescu founded the company in February 2025 when they joined Y Combinator's 2025 winter batch as two high school friends with no products or fixed ideas. Mateega posted on X in July that annual recurring revenue (the annual value of the company's continued subscriptions) had grown to "hundreds of millions of dollars," up from $100 million in April.
The founders originally wanted to build AI agents for the financial sector. Tests have shown that leading models repeatedly fail at handling subtle, professional-level judgments-not because they lack raw ability, but because they have never been taught how experts actually reason through difficult decisions.
So they adjusted their direction. AfterQuery now pays experts to generate inference data: a written record of how professionals gradually solve problems, used to teach AI models judgment, not just facts. Nvidia has used the data to train its open source Nemotron model, and AfterQuery also lists former OpenAI CTO Mira Murati's Thinking Machines Lab and legal AI firm Legora as customers, according to people familiar with the matter.
The demand behind this shift is industry-specific. Frontier laboratories (companies that build the most advanced AI systems) have sifted through most of the text available on the open web, while synthetic data (AI-generated training material) has limited use. What is scarce at present is the judgment from real, qualified experts.
Other companies are chasing the same scarcity from different directions. South Korean financial technology company Toss recently opened up the AI data economy to its 30 million users by partnering with data infrastructure company Poseidon, paying for real-world data that ordinary user record models cannot find online.
AfterQuery is not the only company benefiting from this shortage. Scale AI's Alexandr Wang became the industry's first data-tagged billionaire in 2021 at the age of 24. Later, Meta bought a 49% stake in his company for US$14.3 billion and pushed Wang to the top of its AI laboratory. The founder of rival Mercor surpassed Wang's early record in October last year, becoming a billionaire at the age of 22.
Mateega said that AfterQuery's advantage over Mercor, which relies on AI interviewers to manage a large pool of contractors, is that its customized software can filter submissions to "Goldilocks" difficulty-enough to challenge cutting-edge models but not enough to make it impossible for models to learn from the answers. AfterQuery also trains the data with its own models before selling it to show the laboratory that these materials can indeed improve performance, rather than just verbal promises.
As for Mercor, it is currently in talks with Nvidia about a financing round that will value it to US$20 billion, double the US$10 billion valuation last October. AfterQuery's round of financing has not yet been completed, and the company has not disclosed the leading investor.
