Agnost AI analyzes conversations between users and your production AI agents and discovers: silent failures, agent behavior drift, hallucinations, user frustration, hidden feature requests, and churn signals. It groups them into recurring patterns, shows the exact users and conversations behind each insight, and turns them into evals and fixes.
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Agnost AI is a production observability and improvement platform for AI agents. It continuously analyzes real conversations between users and your deployed agents, detecting failures that typical evals miss—silent errors, behavior drift, hallucinations, user frustration, hidden feature requests, and churn signals. Instead of just surfacing raw data, it groups these issues into recurring patterns, shows the exact users and conversations behind each insight, and converts the highest-impact findings into reviewed fixes—often as pull requests your team can merge directly.
Agnost AI reads real chat and voice conversations the moment you connect. It automatically generates failure categories relevant to your product—broken workflows, repeated retries, setup friction, churn risk—and surfaces patterns your evals never see.
Every insight is grouped into recurring themes, and you can drill down to the exact users and conversations behind each one. This turns vague complaints into actionable, verifiable signals.
The platform doesn't stop at analysis. It turns high-impact patterns into concrete fixes—opening pull requests that your team reviews and merges. One customer reported 16 out of 18 autonomous PRs merged, with bugs fixed overnight.
Works with any LLM and any framework. Setup takes about two minutes, and the platform is built on OpenTelemetry standards, so it fits into existing observability stacks without ripping anything out.
Agnost AI turns silent production failures into reviewed fixes that actually ship.
Most observability tools stop at dashboards and alerts. Agnost AI closes the loop by converting insights into code changes your team can approve and deploy. It's backed by Y Combinator, and early adopters—including engineers at Google and Exa—report real outcomes: one team surfaced 1,247 feature requests from user chats, another saw voice BDRs improve booking rates once they understood which conversation patterns converted. The free tier supports up to 1,000 messages per month, making it easy to start before scaling to Pro or Enterprise plans.
You're shipping AI agents and suspect your evals are missing real-world failures. If you want to stop guessing why users get stuck, frustrated, or churn—and prefer fixes that arrive as reviewed PRs rather than raw logs—Agnost AI is worth a look. It's especially valuable for teams that already have production traffic and want to turn conversation data into a continuous improvement loop without building the infrastructure themselves.
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