
Test agents in realistic worlds built from production usage
Hue turns production usage of agents into repeatable tests that preserve the tools, data, and state behind the real run. As AI agents take on real work, their behavior depends increasingly on the nuances of the world around them. With Hue, teams can test and improve their agents under conditions that mimic real usage.
Hue builds a testing platform for AI agent teams. It captures real production runs and converts them into repeatable test cases that preserve the original user context, tool calls, and stateful environment, so teams can replay and score agent behavior under conditions that match actual usage. The product replaces ad hoc manual testing and synthetic benchmarks that fail to reflect the complexity of live deployments.
AI engineering teams building production agents are the buyers, with a self-serve onboarding flow via the Hue website.
GPAgent keeps YC listings public and neutral. Fund-specific scoring, notes, and workflow state live in each customer workspace.
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