Cost visibility
You know exactly how much each user, each feature, each model costs. No more end-of-month bills with no idea who consumed what.
Tools · LLM observability
Langfuse
See what your LLMs actually do in production. Trace every call, measure latency and cost, debug bad outputs. Without Langfuse, AI is a black box that sometimes works.
You can't improve what you don't measure.
In 30 seconds
Every LLM call becomes a structured trace.
Langfuse intercepts LLM model calls from your applications and stores them in a structured way: input, output, prompt, parameters, latency, cost, user_id, session. A dashboard shows aggregate metrics (requests/day, cost, errors) and lets you drill into a single trace for debugging. Equivalent of Datadog/Sentry, but specific to the LLM domain.
For the business
The four advantages that matter
Debug bad responses
Unexpected response? Open the trace, see prompt, output, context, retrieval. Find the cause in minutes, not days of trial and error.
A/B testing and prompt versioning
Test different prompts on subsets of real users. Measure which converts better or responds faster. Keep the prompt versioned like code.
Self-hosted = logs stay in
Docker container running in your network. Conversations with your LLMs (which may contain sensitive data) never leave.
When it fits
Real use cases
- Monitor LLMs in production (corporate chat, agents, RAG)
- Cost tracking to attribute AI spend per team or feature
- Iterative debug of prompts and RAG flows
- Compliance audit: record of who asked what to the model
When it does NOT fit
Honest limits
- Adds latency if the SDK isn't in async mode
- Storage grows with volume: plan retention/archival
- Initial setup requires app code change (1-2 lines per call)
Installation
docker-compose stack. Python/JS SDK in 10 lines.
docker-compose stack with Langfuse + Postgres + Clickhouse. Official SDKs for Python, TypeScript, Java, Go. Out-of-box integration with LangChain, LlamaIndex. Web dashboard ready on port 3000.
Want to figure out if Langfuse makes sense for your organization?
The initial assessment clarifies use case, integration with the rest of the stack, investment. No generic presentations.