About Litefuse
Why agent reliability is hard
Agents are harder to make reliable than traditional software. The model is non-deterministic, plans go off-rail, tools fail in ways you didn’t anticipate, and memory silently drifts or disappears between turns. A hallucination in one step can poison everything downstream. The surface area of things that can go wrong is large — and most of it only shows up in production.
What Litefuse is
Litefuse is an agent observability and evaluation platform. Our mission is to help developers ship reliable AI agents with evaluation-driven development:
- Trace every step — LLM calls, tool invocations, subagent hops, memory reads/writes — so you can see why an agent did what it did.
- Evaluate continuously — run LLM-as-judge, user feedback, custom metrics, and offline dataset experiments against your agents, online and offline.
- Catch regressions before your users do — compare runs, diff prompts, and gate deploys on eval results.
Why we forked from Langfuse
Litefuse started as a fork of Langfuse. Langfuse is an excellent open-source project and the prior art here is substantial — we’re grateful for everything the Langfuse team has built.
We forked because we wanted a meaningfully different tradeoff curve for self-hosted deployments:
- Simpler architecture. Langfuse’s production setup has six moving components. Litefuse runs on as few as two — easier to deploy, easier to operate, easier to understand when something breaks.
- Apache Doris as the observability store. Litefuse supports Apache Doris as the backing store for trace and observation data. This unlocks better query performance on analytical workloads and fits teams already running Doris.
- ~80% lower storage footprint for the same trace volume, largely thanks to Doris’s columnar storage and compression.
Compatible with Langfuse SDK
Litefuse preserves wire compatibility with the Langfuse SDK. If you’re already instrumenting with langfuse or langfuse-python/langfuse-js, you can point it at a Litefuse endpoint — no re-instrumentation required. We intend to keep this compatibility as a long-term commitment, not a migration bridge.