
Langfuse is an open-source LLM engineering platform for AI agent teams. It combines tracing, prompt management, evals, experiments, annotation, and metrics to debug quality, cost, and latency from prototype to production.
Langfuse connects the LLM engineering loop in one product. Traces, prompt versions, evals, experiments, and annotation queues sit together, so production issues can feed back into prompts and datasets.
It also stays open: OpenTelemetry, Python and JavaScript SDKs, Java and Go through OTel, LiteLLM logging, custom APIs, more than 100 integrations, and exports.
Teams instrument an app, then inspect traces, chats, users, token usage, cost, and latency. From there they can manage prompt versions, fetch prompts without hard-coding them, test changes in the playground, and run experiments.
Quality tools include datasets, SDK and UI experiments, custom scores, user feedback, external eval pipelines, LLM-as-judge, and annotation queues. Production controls include batch export, PostHog and Mixpanel, webhooks, data masking, retention, SSO, SCIM, audit logs, and compliance reports depending on plan.
No public average rating is listed. Canva's AI team uses Langfuse to trace and debug generative design features, and Langfuse reports 2,300+ customers, 100,000+ engineers, and 10+ billion observations per month.
Tradeoffs are usage and governance limits. Hobby is capped at 50k units/month, 30 days of data access, and 2 users, while SSO, RBAC, private support, and scheduled exports require higher paid options.
The free plan suits prototypes and POCs, while paid plans buy longer history, more users, higher limits, support, and security controls.
It instruments LLM apps with SDKs, OpenTelemetry, LiteLLM, or APIs, then shows traces, costs, prompts, evals, and scores in one app.
No. It is an independent open-source LLM engineering platform, not a LangChain product.
Yes. It has a free Hobby cloud plan with 50k units/month, and the MIT-licensed project can be self-hosted for free.
ClickHouse owns Langfuse after acquiring it in 2026.
It puts traces, prompt versions, cost and latency metrics, evals, experiments, and human annotation in one workflow for LLM teams.
Teams often compare it with other LLM observability and eval tools such as LangSmith, Phoenix, Helicone, and Braintrust.
It is used to debug and improve LLM apps with tracing, prompt management, evals, experiments, human reviews, and cost tracking.
Yes. Langfuse is open source under the MIT license and can be self-hosted; Langfuse Cloud is the hosted SaaS option.
Ask specific questions about this tool.