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Integration

Observe, evaluate, and improve your LangGraph agents

Capture every StateGraph node and edge transition from your LangGraph agents — the compiled graph implements LangChain's own Runnable interface, so the same span structure follows every branch, loop, and checkpoint.

What Prefactor records from LangGraph

graph node executions (functions that read and update the shared State)conditional edge transitions (direct or routed)checkpointed steps (MemorySaver / PostgresSaver — pause/resume state)tool callsLLM calls

LangGraph + Prefactor

How the LangGraph integration works

See setup + the install snippet →

LangGraph integration FAQ

Do I need a dedicated package for LangGraph?

You can instrument LangGraph today with the framework-agnostic prefactor-core SDK; a dedicated package can be added on request.

What does Prefactor capture from LangGraph?

Prefactor records graph node executions, conditional edge transitions, tool calls and LLM calls as structured, timestamped spans — so every LangGraph run is captured as trace data you can reconstruct, search and export end to end.

Does Prefactor add latency or change how LangGraph runs?

No. Observability capture is designed to stay off your agent's critical path, so it doesn't alter your LangGraph logic or your users' responses. The only part that acts inline is the optional runtime guardrails you enable per agent — by design, so a high-risk or low-confidence action can be held for human approval before it executes.

Can I evaluate agents built with LangGraph and catch regressions?

Yes. Once runs are captured, eval suites score quality and groundedness on real traffic, drift detection flags behaviour changes after deployment, and versioned eval history catches regressions before they ship — the observe → evaluate → improve loop applied to your LangGraph agents.

Related guides

See it on your LangGraph agents

Book a 15-minute setup and our team gets you tracing in production.