What is Langfuse?
Langfuse is an open-source platform that brings observability, evaluation, and prompt management together for AI agents. You can trace every LLM call, tool invocation, and retrieval step, then filter by user, session, cost, latency, or custom metadata. It helps you understand how your agents behave using real production data.
You start by ingesting your first trace using OpenAI, LangChain, or the SDKs. Then you can run evaluators—LLM-as-a-judge, heuristic functions, or human review—on production data or during experiments. You can also manage prompts separately from code, deploy them with one click, and roll back when needed. The playground lets you test prompts on real production inputs and compare models side-by-side.
Langfuse suits engineering teams building chat agents, coding agents, or workflow automation. It works with any language or framework supporting OTel instrumentation, plus 100+ integrations. the website says it is used by 21 of the Fortune 50 and handles 90B+ observations per month. You can self-host via Docker Compose, Kubernetes, or Terraform.
Langfuse features
- Observability: Hierarchical traces capture every LLM call, tool invocation, and retrieval step for full visibility.
- Evaluation: Run LLM-as-a-judge, heuristic functions, or human review on production data or during experiments.
- Prompt Management: Separate prompts from code with one-click deployments and rollbacks for team collaboration.
- Playground: Test prompts on real production inputs and compare models side-by-side before shipping.
- Cost & Latency: Monitor cost, latency, and quality with dashboards and automated alerts.
What you can do with Langfuse
- Trace multi-turn chat agent quality, cost, and resolution in one view.
- Debug generative design features in production with detailed traces.
- Run evaluators on historical observations to catch regressions.
- Compare model outputs side-by-side in the playground before deployment.
How to get started with Langfuse
- Sign up for free or self-host via Docker Compose, Kubernetes, or Terraform.
- Follow the step-by-step guide to ingest your first trace using OpenAI, LangChain, or the SDKs.
- Set up evaluators and dashboards to monitor cost, latency, and quality in production.
Tips for better results with Langfuse
- Start by tracing a single real user session with Langfuse using the OpenAI or LangChain integration to see the full trace structure before scaling up.
- Use Langfuse's playground to test prompt variations on real production inputs, comparing model outputs side-by-side to catch regressions early.
- Set up LLM-as-a-judge evaluators on historical observations in Langfuse to automatically detect quality issues without manual review.
- Filter traces by custom metadata like user ID or session ID in Langfuse to isolate specific agent behaviors and debug cost or latency spikes.
Langfuse pricing
Langfuse has a free way to start, with paid plans for heavier use. Check langfuse.com for current limits and prices.
What to check before you rely on Langfuse
- Check the pricing page for Langfuse to confirm what the free tier includes, since the website only labels it as freemium without detailing limits.
- Verify that Langfuse supports your specific LLM framework or language by reviewing the integrations list, as the website mentions 100+ but not all.
- Confirm data privacy policies for self-hosting versus cloud, as the website doesn't state how your trace data is handled in the hosted version.
Who Langfuse is for
Langfuse suits AI engineers, ML teams, DevOps and Product teams. If that is not you, the AI developer platforms below may fit better.
Similar tools compared with Langfuse
| Tool | What it is | Pricing |
|---|---|---|
| Langfuse | Open source LLM observability and evals platform | Freemium |
| SiVideoAPI | Unified API for top AI video models | Freemium |
| OpenSI | AI model comparison and pricing tool | See website |
| OpenRouter | Unified API for many AI models | Freemium |
| Ollama | Run open models locally or cloud | Freemium |
Langfuse FAQ
What does Langfuse do?
Langfuse is an open-source platform for tracing, evaluating, and improving AI agents. It connects observability, prompt management, experiments, and human feedback in one integrated loop, so you can understand production behavior and ship better quality.
Is Langfuse free?
Langfuse offers a free plan to start, and you can also self-host it. The website mentions 'Start free' and provides self-hosting guides, but it does not detail specific paid tiers or pricing limits.
Who is Langfuse for?
Langfuse is for engineering teams building AI agents, such as chat agents, coding agents, or workflow automation. It is used by companies like Canva and 21 of the Fortune 50, and supports 100,000+ engineers.
What integrations does Langfuse support?
Langfuse works with any language or framework supporting OTel instrumentation, including Python, TypeScript, Go, Java, and.NET. It also integrates with frameworks like LangChain, Vercel AI SDK, and LiteLLM, plus 100+ other integrations.
Can Langfuse be self-hosted, and what are the options?
Yes, Langfuse can be self-hosted. The website provides guides for Docker Compose, Kubernetes (Helm), and Terraform for AWS, GCP, and Azure. This gives you control over your deployment environment and data. Check the self-hosting guides in the documentation for detailed setup instructions.
Does Langfuse work with any programming language or framework?
Langfuse works with any language or framework that supports OpenTelemetry (OTel) instrumentation. It also offers SDKs for popular tools like OpenAI and LangChain. The website mentions over 100 integrations, so you can likely connect it to your existing stack. For specific language support, check the SDK documentation.
What does the free plan of Langfuse include?
The website labels Langfuse as freemium, but it does not detail what the free plan includes on the main pages. To know the exact limits or features of the free tier, you should visit the pricing page or contact their sales team for a clear breakdown of what you get at no cost.
