Langfuse
An open-source platform for tracing, evaluating, and monitoring LLM and agent applications.
Langfuse gives an AI system the observability that ordinary software takes for granted: every call, prompt, tool use, and agent step is traced, with cost and latency attached.
On top of tracing it adds evaluation and prompt management, and it is open-source and self-hostable, so the record of what your AI did can stay inside your perimeter.
Where it fits
A strong default whenever an AI system reaches production and you need to see what it actually did, call by call.
Where it does not fit
More than a one-off script or a quick prototype needs: instrument once the system is real.
Alternatives to Langfuse
The closest options on the map, and where each fits instead.
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LangSmith LLM observability
A natural fit when a project is built on LangChain or LangGraph and you want tracing and evals from the same ecosystem.
Unlike Langfuse ProprietaryNot self-hostable
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Helicone LLM observability
A fit when you want fast, low-effort visibility into model calls, costs, and latency through a simple proxy.
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Opik LLM observability
A fit when you want an open-source, self-hostable platform spanning tracing, evals, and production monitoring.
Unlike Langfuse Maturity: growing
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Braintrust Evaluation platform
A fit for product teams who want disciplined, data-driven evaluation as the centre of their iteration loop.
Unlike Langfuse ProprietaryNot self-hostableMaturity: growing
How it compares
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The smooth choice on a LangChain stack. When self-hosting the trace data is a requirement, we point clients to Langfuse instead.
Pairs with
Commonly used alongside it.
