Automate AI Agent Improvement

Generate fixes, simulation-test them, ship what works. Every fix passes 36+ simulated conversations and regression testing first. Each cycle builds on the last.

Get Started

Audit an Agent

API Reference

MCP Integration

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Public Agent Audit

Paste any AI agent's URL, get a graded report in under a minute. Verdict, score, and findings backed by real transcripts. Re-audit later to track improvement.

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Automated Agent Fixes

Generate targeted prompt, configuration, and model variants that address diagnosed failures — not random improvements.

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Simulation-Tested Proof

Every fix survives 36+ simulated conversations and regression testing before it touches production. If any metric regresses after deployment, it rolls back automatically.

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Step-Level Diagnosis

Identify why your agents underperform — from conversation-level breakdowns to the exact step and turn in multi-agent flows.

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Ship Proven Improvements

Proven improvements flow to your stack via API, webhooks, or GitHub PR. Full audit trail, instant rollback.

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Data Connectors

Ground optimization in real data. Import traces from LangSmith, Langfuse, or any OpenTelemetry-compatible source.

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Stack-Agnostic

Works with any framework, any LLM, any observability tool — or none at all.