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Introduction ​

Converra is a closed-loop optimization system for production AI agents. It diagnoses why your agents fail, generates targeted fixes, proves every change in simulation, and deploys winners back to production.

What is Converra? ​

Your stack might have observability. Observability shows you what broke—Converra fixes it. It reads from your logs, diagnoses failure patterns, generates and tests prompt fixes, and ships proven improvements back to where your prompts live.

Converra helps you:

  • Diagnose failures - Automatically identify why agents fail, down to the specific step in multi-agent flows
  • Fix prompts and config automatically - Generate targeted variants that address diagnosed prompt and configuration issues
  • Prove changes before production - Every fix is tested against diverse personas and regression-checked in simulation
  • Deploy with confidence - Ship proven fixes back to production via API, webhooks, or manual apply

How It Works ​

  1. Diagnose - Import conversations and traces to identify failure patterns
  2. Fix - Generate targeted prompt variants addressing diagnosed issues
  3. Prove - Simulate against diverse personas and regression-test against known-good scenarios
  4. Deploy - Ship the proven winner back to production

Key Concepts ​

Prompts ​

Your AI system prompts with metadata like objectives, constraints, and LLM settings.

Agent Systems ​

When you import multi-step traces (e.g., a router handing off to specialists), Converra can auto-discover agent systems: prompts that operate together in a flow. Converra simulates these systems with a bounded flow model so runs terminate and results stay comparable.

Conversations ​

Real user-AI dialogues logged for performance analysis and insight generation.

Optimizations ​

Automated testing cycles that generate prompt variants and evaluate them through simulation.

Insights ​

Aggregated learnings from conversations identifying patterns, issues, and opportunities.

Next Steps ​

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