Handit vs Converra: Production Agent Fixes

Each row answers the same question for both products. Handit statements come from its own documentation, reviewed on the date shown above; sources are listed at the end.

Handit's public repository describes tracing AI applications, detecting issues such as hallucinations, schema failures, privacy leaks and timeouts, then connecting a finding to a proposed fix. Its setup links an SDK, evaluation models and a GitHub repository. That is a concrete production-improvement workflow, not passive logging.

Converra also begins with production behavior, but it narrows the next step to a diagnosed failure pattern and a bounded prompt or configuration candidate. A broken service, code path or tool integration still needs an engineering repair. Neither a trace finding nor a recommendation is evidence that a behavior fix worked.

Handit says it can generate fixes, test them against production failure cases and open a GitHub pull request. That gives an engineering team a reviewable artifact in its normal workflow. A pull request is not itself a released change, and its public description does not make a merged change a result on future production traffic.

Converra compares a bounded behavior change with the current agent before approval, with regression scenarios for behavior the baseline already handles. The team still approves what goes live. Treat a passing candidate test, an opened pull request and an approved production change as separate states so a strong suggestion is not presented as a completed fix.

A support agent may begin inventing refund eligibility after a model change. Handit can surface the recurring pattern, propose a prompt or code change and send the team a pull request. Before release, review the change and test eligible refunds, expired returns, ambiguous purchase dates and escalation cases.

After approval, measure the same failure on comparable production traffic. Converra records a verified, not fixed or confounded production verdict when its evidence rules support one. Confounded does not prove the fix failed: overlapping edits to the same prompt can prevent attribution, and model changes or traffic-mix shifts are not automatically excluded. This is a workflow example, not customer performance evidence.

You want an open-source, GitHub-connected system to trace production agent failures and create reviewable fixes.

Your engineering team wants recommendations that can include prompts, configuration, code or model settings.

You want to investigate failures through an instrumented SDK and keep the release decision in your repository workflow.

A recurring production behavior failure needs a bounded prompt or configuration candidate, not only a proposed code change.

You want the current agent and candidate compared head-to-head before approving a change.

You want the approved behavioral fix tracked afterward with a verified, not fixed or confounded production verdict.

They overlap on using production evidence to improve an agent. Converra does not replace every code-analysis, SDK-instrumentation or GitHub pull-request workflow in Handit.

Do not assume a native Handit connector. Converra's documented native trace connectors are LangSmith and Langfuse. For another stack, use the Converra SDK integration guides to send supported conversation data and verify capture coverage before relying on the combined workflow.