Langfuse vs Converra: What Each Does for Production Agents

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

Both care about whether a change made the agent better. Langfuse gives you experiments with baselines and CI checks before release, and per-version metrics and label-based A/B tests after it. Converra runs a candidate head-to-head against the current agent before release and measures the targeted failure after it. If your team already builds this workflow by hand in Langfuse, Converra automates the parts between a visible failure and a judged result.

Who writes the fix. Langfuse does not generate fixes; its own guides show an external coding agent reading feedback and proposing prompt changes. Converra generates bounded prompt or configuration variants aimed at a diagnosed failure pattern.

How the fix is tested. Langfuse experiments run your datasets and evaluators, and multi-turn simulation is available through a cookbook. Converra's simulation is built in: multi-turn personas derived from production patterns, paired head-to-head comparisons, and regression scenarios.

What happens after release. Langfuse shows metrics by prompt version; your team decides what they mean. Converra counts the targeted failure on live traffic and returns a verdict, including confounded when another change to the same prompt overlapped. The guide to verifying a fix after deployment explains why per-version metrics alone are correlational.

You want open-source tracing and evaluation you can self-host for free, or you need your trace data to stay in your own infrastructure.

You want prompt management with versions, labels, and rollback, and you are comfortable owning the analysis and the fixes.

You run many kinds of LLM workloads, not only conversational agents, and want one instrumentation layer for all of them.

Your team keeps finding the same agent failures in Langfuse but spends the time writing, testing, and checking fixes by hand.

You want every candidate fix tested head-to-head against the current agent in multi-turn simulation before release, with regression scenarios.

You want each shipped fix to come back with a production verdict: verified, not fixed, or confounded.

No. Converra complements Langfuse. It connects with your Langfuse public and secret keys, works with the EU or US cloud or a self-hosted URL, and imports traces with their system prompts and transcripts. Langfuse remains your tracing, evaluation, and prompt-management layer.

There is no direct overlap in fix generation or production verdicts, because Langfuse leaves both to the team or to an external agent.