From trace to tested fix — without regressions. Converra finds the failing step, generates a fix, and validates it with simulation. Nothing ships without proof it works.
Production AI
Live traffic • Never A/B tested
Converra
Optimized Prompt
v3+18% task completion
Converra runs the full optimization loop end-to-end, so improvements are proven before they ship.
Choose Converra when you have a human-facing agent in production and want measurable improvement without regressions, without building a custom optimization pipeline.
Keep your observability/evals tools: Converra can sit on top of your existing stack and turn measurement into validated change.
If you're still defining what the agent should do (early discovery, low stakes), playgrounds/DIY may be enough, until repeatability and risk control matter.
Best together: Converra doesn't replace your tracing or evals. It uses them as inputs and runs the optimization loop end-to-end. Keep your observability for visibility, your eval suites for measurement, and let Converra handle the analyze → generate → simulate → select → deploy cycle.
From connection to continuous improvement
Your data, your way
Add the Converra MCP to your AI coding assistant and let it handle the rest. Or connect LangSmith for continuous sync, use our SDK/API, or paste transcripts directly.
See the full picture
Converra automatically groups multi-agent traces into agent systems, visualizes execution paths, and identifies the weakest link in each chain.
Not random rewrites
Converra generates a small set of candidate prompt variants (typically 3–5). Each variant targets specific improvements while preserving constraints.
The core differentiator
Each variant is tested against personas that represent real user types and scenarios derived from production patterns, including edge cases. Simulations are run head-to-head against the baseline.
Automatic safety check
When a variant shows improvement, Converra automatically tests it against a "golden set" of scenarios your baseline handles well. Regressions are caught before deployment. You see the tradeoff and decide.
Confident deployment
Deployment works like CI/CD for agent improvements. Every fix passes simulation and regression testing before it ships. Deploy automatically, via GitHub PR, or with manual review.
Converra doesn't stop after one win. When production performance drifts (models update, user behavior shifts, new edge cases appear), Converra can alert you, auto-trigger new optimizations, and keep your agents improving without constant engineering cycles.
The loop compounds. Each improvement becomes the new baseline.
No. Converra can generate test coverage from personas and scenarios derived from production patterns. You can still use real conversations as grounding input.
That's what simulation + regression testing is designed to prevent. Improvements must prove lift and avoid regressions before shipping.
Exploratory runs in 5–15 minutes; validation runs take 30–60 minutes for higher confidence.
Yes. You control what Converra tests and what it optimizes for.
Let Converra handle the optimization loop while you focus on building your product.