AfterQuery closes $30M funding round
AfterQuery has raised $30 million in fresh funding at a $300 million valuation, as the company scales its effort to build expert-grade reasoning datasets designed for AI model training.
Building datasets from verified professionals
The company’s core product centers on collecting and structuring reasoning-oriented data from a network of nearly 100,000 verified professionals. Unlike conventional web-scraped corpora, expert-sourced datasets aim to capture higher-signal inputs—such as domain judgments, step-by-step explanations, and decision rationales—that can improve how models perform on complex tasks.
Why “reasoning data” matters
As AI developers push models beyond pattern matching toward more reliable problem-solving, demand has grown for training data that reflects how experts think and justify answers. These datasets can be used for training and fine-tuning, including supervised learning and evaluation, helping teams measure performance on specialized workflows and reduce errors in high-stakes domains.
Use of proceeds and market context
AfterQuery is expected to use the new capital to expand its professional network, increase dataset coverage across industries, and improve data quality controls, including verification and labeling processes. The funding also underscores investor interest in the “picks-and-shovels” layer of the AI stack—companies that supply critical inputs such as data, tooling, and evaluation frameworks.
While the company did not disclose additional terms of the deal in the announcement, the round positions AfterQuery as a notable player in the fast-growing market for expert-labeled and reasoning-focused data products used by model builders and enterprises deploying AI systems.
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