Autonomous optimization for production AI
without regressions

Converra turns your production conversations into prompt improvements you can trust. Changes are simulated offline, gated by confidence, and deployed with versioning and instant rollback.

🤖

Production AI

Live traffic • Never A/B tested

Converra

🔍
Analyze
Generate
🧪
Simulate
🚦
Gate
OfflineNo Regressions

Optimized Prompt

v3

+18% task completion

↺ Deploy (versioned) + rollback

Converra is

  • An autonomous optimization loop for production AI agents
  • Simulation-first, with gated deployment decisions
  • Compatible with your existing stack (no pipeline rewrite)

Converra is not

  • Only observability (“here's what broke”)
  • A prompt design playground
  • Runtime A/B infrastructure (no prod traffic experiments)
Competition

Head-to-Head Comparison

Converra runs the full optimization loop end-to-end—so improvements are proven before they ship.

Prompt playgrounds / prompt IDEs
Great for: Rapid exploration and prototyping
Breaks down: Hard to prove improvements hold at scale
Converra wins: Tests variants at scale; recommends winners that pass your guardrails
LLM observability / tracing
Great for: Visibility, debugging, and diagnosis (cost/latency/failures)
Breaks down: Doesn't produce changes; still requires manual iteration
Converra wins: Turns insights into validated changes—automatically
Evaluation suites
Great for: Measurement discipline (datasets, scorers, comparisons over time)
Breaks down: No variant management, selection, or deploy workflow
Converra wins: Full cycle: variants + winner selection + versioned deploy/rollback
Runtime A/B / experimentation platforms
Great for: Live traffic splits for product and UI metrics
Breaks down: Risky for agent changes; regressions found in prod
Converra wins: Validates offline before any production exposure
DIY (spreadsheets + transcript review)
Great for: Early-stage learning and quick iteration
Breaks down: Subjective, doesn't scale, knowledge lives in people
Converra wins: Versioned, auditable, one-click deploy/rollback

Fit, stated plainly

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.

The optimization loop, step by step

From connection to continuous improvement

1

Connect once

Your data, your way

Add the Converra MCP to your AI coding assistant and let it handle the rest. Or import from LangSmith, use our SDK/API, or paste transcripts directly.

  • MCP: works with Cursor, Claude Code, Windsurf, and any MCP client
  • LangSmith: import existing traces + feedback (Langfuse coming soon)
  • SDK/API: integrate programmatically from your backend
2

Analyze the baseline

Understand before changing

Converra analyzes your prompt and conversation history to detect optimization goals, find recurring failure patterns, and identify constraints that must be preserved.

  • Goals detected automatically (or override with explicit intent)
  • Baseline performance snapshot
  • Plan for what to change (and what NOT to change)
3

Generate targeted variants

Not random rewrites

Converra generates a small set of candidate prompt variants (typically 3–5). Each variant targets specific improvements while preserving constraints.

  • Changes are structured to be explainable
  • Constraints preserved (schema, boundaries, brand voice)
  • Think "small, provable edits" not "prompt roulette"
4

Simulate head-to-head

key

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.

  • Personas: new, frustrated, technical, power user
  • Multi-turn conversations, not just single-turn
  • Exploratory mode (faster) or Validation mode (higher confidence)
  • Replay mode: test variants against imported production traces (offline) to verify fixes on the cases that actually failed
5

Gate and select a winner

No-regression rules

Variants are evaluated across multiple metrics. Converra only recommends a winner when it beats baseline by a meaningful margin and critical metrics do not regress.

  • Task completion, response quality, sentiment
  • Safety/policy adherence, schema compliance
  • Inconclusive? Recommend validation mode or keep original
6

Deploy with control

Versioned and reversible

When you apply a winning variant, your prompt updates automatically. A new version is created, the original is preserved, and integrations receive update events via webhooks.

  • Manual approval (default) or auto-accept
  • Full history of what was tested and why it won
  • Instant rollback capability

Always-live optimization

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 prompts improving without constant engineering cycles.

The loop compounds. Each improvement becomes the new baseline.

FAQ

Do I need a dataset?

No. Converra can generate test coverage from personas and scenarios derived from production patterns. You can still use real conversations as grounding input.

Will Converra break what's working?

That's what simulation + gating is designed to prevent. Improvements must prove lift and avoid regressions before shipping.

How long does an optimization take?

Exploratory runs in 5–15 minutes; validation runs take 30–60 minutes for higher confidence.

Can I bring custom personas, metrics, or rules?

Yes—you can tailor what Converra tests and what it optimizes for.

Ready to stop hand-tuning prompts?

Let Converra handle the optimization loop while you focus on building your product.