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AfterQuery Says It Hits $100 Million Run Rate, Raises $30 Million for Expert AI Data

The San Francisco startup pitches researcher-tested datasets as a new layer of infrastructure for labs training advanced AI systems.

Overview

  • AfterQuery disclosed it surpassed a $100 million annual revenue run rate and raised a $30 million Series A at a $300 million valuation led by Altos Ventures with The Raine Group, Y Combinator, and BoxGroup participating.
  • The company turns real-world professional workflows into structured datasets and training environments so AI models can learn how experts think through complex tasks.
  • AfterQuery says it validates each dataset with custom checks and post-training evaluations to hit a “Goldilocks” difficulty range and to show measured benchmark gains before delivery.
  • The startup plans to use the new capital to grow its expert network, expand into more specialized fields, and add engineering, research, and enterprise support.
  • Executives say every major AI lab is a customer and that nearly 100,000 verified professionals contribute, a scale the company touts in a fast-growing yet volatile human-data market highlighted by rivals’ rapid rises and recent security stumbles.