AfterQuery lands $30M as demand for expert AI training data surges
AfterQuery, a fast-growing provider of high-quality training data for artificial intelligence models, has raised $30 million in fresh funding at a reported $300 million valuation, led by Silicon Valley investor Altos Ventures. The deal underscores how intensely AI labs are competing to secure scarce, expert-level datasets to power the next generation of large-scale models.
Funding round led by Altos Ventures
The latest round, backed primarily by Altos Ventures, values AfterQuery at roughly ten times its new capital injection, reflecting strong investor conviction in the company’s position within the AI infrastructure stack. Existing and new institutional investors are understood to have participated, seeking exposure to the critical layer of data that underpins modern AI models and machine learning systems.
While detailed terms were not fully disclosed, the $300 million valuation places AfterQuery among the more highly valued private companies focused specifically on training data, rather than on core model development. The company plans to use the capital to expand its network of domain experts, strengthen its data quality controls and scale its engineering team.
Rising competition for expert training data
As leading AI labs race to build more capable large language models (LLMs) and multimodal systems, the market for curated, reliable and rights-cleared expert data has tightened sharply. Public web data is abundant but noisy, while specialist content created by professionals in fields such as law, medicine, finance and engineering remains limited and expensive.
AfterQuery positions itself as a bridge between AI developers and this high-value information, working with vetted experts to produce structured datasets, annotations and evaluations tailored to specific use cases. This approach is increasingly viewed as essential to reducing hallucinations, improving factual accuracy and meeting emerging regulatory expectations around AI safety and transparency.
Strategic role in the AI ecosystem
For investors like Altos Ventures, companies that control differentiated, high-quality training data pipelines are becoming strategic assets. As foundation models converge in performance, access to proprietary, expert-labelled datasets may become one of the key levers for competitive advantage.
The new funding gives AfterQuery additional firepower to deepen relationships with leading AI labs and enterprise customers that require trustworthy data to build domain-specific copilots, decision-support tools and automation platforms. With capital in hand and demand accelerating, the company is positioned to play a central role in how the next wave of AI systems is trained and evaluated.