Agnost AI
Find recurring AI-agent failures in conversations and traces
Turn agent interactions and corrections into reviewable behavioral guidance

Reflexio adds a learning loop to existing AI agents without retraining the underlying model. Applications publish interaction outcomes, user corrections, and other feedback; the platform extracts guidance about how an agent should behave under similar conditions. Relevant guidance is retrieved during later requests rather than sending an entire history into every prompt.
The system keeps learned behavior visible and revocable, allowing teams to inspect, reject, or replace rules as circumstances change. Evaluation tools compare augmented responses with a control to help assess whether a learning is useful. Integration options include a Python SDK, REST API, CLI, and a setup skill for coding agents, making the approach adaptable to different application frameworks.
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