Quality & Security / Evals & Testing
Langfuse
Open-source LLM observability and evals.
Operator context
Best for
Teams measuring whether AI systems behave reliably before and after release.
Why it's here
Open-source LLM observability and evals. We included it because it adds a practical reference point for evals & testing and helps make that part of the ecosystem easier to evaluate.
When to use it
- Evaluate prompts, models, or agent behavior
- Create repeatable tests for an AI workflow
- Catch regressions as an AI system changes
Where this fits
Indexed under Quality & Security → Evals & Testing. Captured in the August 2026 edition, sourced via Curated Web.
Common questions
What is Langfuse? +
Langfuse is Open-source LLM observability and evals.
Which AI models does Langfuse work with? +
It is tagged for: Model-agnostic.
Where can I access Langfuse? +
It is available at langfuse.com.
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