A clear breakdown of what Brainforge fixes, how fast, and what it actually delivers.
Langfuse tracing for LLM calls, tool use, retrieval, and multi-step agent workflows.
Ship AI you can trace, test, and improve
Brainforge pairs Langfuse with hands-on implementation for traces, evals, and monitoring, so LLM apps and agents stay reliable from first release through every prompt change.
Where Brainforge fits
What Brainforge builds with Langfuse
Eval harnesses and scorecards that catch regressions before users do.
Production observability setups that connect traces to human review and release gates.
How we work together
How the partnership shows up for clients
- 01We implement Langfuse for teams putting AI into production and need visibility from day one.
- 02We partner on observability and eval design with ClickHouse and Langfuse field motions.
- 03We operate the trace and eval loop as models, prompts, and agents evolve.
When this matters
Where this partnership matters
- You have LLM features in production and cannot explain what they did on a bad run.
- You need evals and traces behind releases, not ad hoc spot checks in a dashboard.
- You want open-source observability with a path to self-host or cloud as requirements grow.
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LET'S BUILD
together
together
We instrument and evaluate LLM applications with Langfuse so teams can improve quality, cost, and reliability in production.
