Glossary · AI & Agents
Langfuse
Overview
What Langfuse is
Langfuse is an open-source platform for observing and improving applications built on large language models. It captures detailed traces of each request, showing the prompts, model calls, tool use, retrieved context, latency, and token cost behind every response. That end-to-end visibility helps teams understand what their AI actually did and where it went wrong, which is difficult with logs alone.
Key capabilities
Beyond tracing, Langfuse provides evaluation tools to score outputs with automated checks, model-based grading, or human review; prompt management to version and test prompts; and dashboards for cost, latency, and quality over time. It integrates with common frameworks and model providers, and because it is open-source, teams can self-host it to keep sensitive prompts and data in their own environment.
Why it matters for AI projects
Shipping an AI feature is easy; keeping it accurate, fast, and affordable is not. Langfuse gives that operational layer, which is why it fits AI consulting and production AI agents and voice agents. A full-service team uses it to debug failures, catch quality regressions before users do, and tie model spend to real usage, turning a black-box demo into a maintainable system.
Where we use it
Related Zen in Tech services
How our team puts Langfuse to work in real projects.
FAQ
Langfuse — common questions
What is Langfuse used for?
Langfuse is used to trace, evaluate, and monitor LLM applications such as chatbots, agents, and RAG systems. It helps teams debug bad outputs, track token costs and latency, manage prompts, and measure output quality in production.
Is Langfuse open-source and free?
Langfuse is open-source and can be self-hosted for free, aside from your own infrastructure costs. It also offers a managed cloud with a free tier and paid plans that add scale, longer data retention, and team features.
Langfuse vs LangSmith: what's the difference?
Both are LLM observability and evaluation platforms. Langfuse is open-source and self-hostable, appealing to teams that want data control and no vendor lock-in, while LangSmith is a closed product from the LangChain team with tight LangChain integration.
Need Langfuse done right?
Book a free consultation and we’ll map the fastest, most cost-effective path for your project.
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