About Langfuse
Overview
Langfuse is an open source LLM observability and evaluation platform that helps engineers trace, evaluate, and improve AI agents. It connects tracing, monitoring, datasets, experiments, and evaluation in one continuous loop.
Built for teams building AI applications with LLMs, Langfuse supports any language and framework via OpenTelemetry instrumentation and offers 100+ integrations. It is used by 19 of the Fortune 50 and over 100,000 engineers processing 10+ billion observations per month.
Key Benefits
- Hierarchical traces capture every LLM call, tool invocation, and retrieval step with filtering by user, session, cost, latency, or custom metadata.
- LLM-as-a-judge, heuristic functions, or human review — run evaluators on production data or during experiments.
- Separate prompts from code with one-click deployments and rollbacks, making prompt improvement a team activity.
- Test prompts on real production inputs and compare models side-by-side in the Playground.
- Define test cases, run experiments, and compare results side by side with the Experiments feature.
- Collaborative human-in-the-loop workflows let teams review traces and create golden datasets together.
How It Works
You instrument your LLM application using Langfuse SDKs (Python, JavaScript, TypeScript), OpenTelemetry, or proxy-based logging via LiteLLM. Traces flow into the platform where you filter by user, session, cost, latency, or custom metadata. You then run LLM-as-a-judge or heuristic evaluators, manage prompt versions with one-click rollbacks, and define experiments on datasets — all from the same interface.
Use Cases
- AI engineering teams at large enterprises — debug and improve production LLM agents by tracing every tool invocation and LLM call.
- Startup founders building AI products — evaluate prompt quality and model cost before shipping to users.
- Machine learning engineers — run offline experiments comparing model outputs side by side to select best-performing prompts and models.
- Platform engineering teams — self-host Langfuse with Docker Compose, Kubernetes, or cloud Terraform to keep data inside their infrastructure.
- Generative design teams like Canva's AI team — trace and debug generative design features running in production.
- Open source contributors and hobbyists — get started free with the Hobby plan to trace personal AI projects without a credit card.
Why Choose This Product
Langfuse is best suited for engineering teams that need one integrated platform for tracing, prompt management, evaluation, and experimentation rather than stitching together multiple tools. It is open source under the MIT license, supports self-hosting at scale, and does not lock in data — all product features are available in the MIT-licensed version.
