AfterQuery, a data infrastructure company providing high-quality datasets and reinforcement learning environments for AI models, announced a $30 million Series A at a $300 million valuation led by Altos Ventures. The round included participation from The Raine Group, Y Combinator, BoxGroup, and Latitude Capital. Funding will support expansion of expert data networks and continued development of professional-grade AI training environments.
Scaling Professional Expertise
AfterQuery focuses on capturing tacit knowledge from domain experts and transforming it into structured training data for AI systems. The platform enables models to encode decision-making patterns across fields such as finance, software engineering, law, and enterprise workflows. In 14 months, the company reports adoption by leading AI labs and a revenue run rate exceeding $100 million.
Data Quality as Competitive Advantage
The company positions high-quality training data as the key differentiator for next-generation AI models. AfterQuery develops research-driven workflows and proprietary tools to generate datasets reflecting real-world professional tasks, including complex judgment calls and edge cases. Nearly 100,000 verified professionals contribute domain expertise through the platform.
Software-First Data Creation
AfterQuery builds internal systems to manage data generation and validation rather than outsourcing collection. The approach aims to ensure consistency, scalability, and higher-quality training environments for advanced AI applications.
The new funding will expand domain coverage, grow the expert contributor network, and accelerate development of data infrastructure designed to support professional AI use cases.