LangGraph Compliance Review Workflow
A state-machine compliance document review pipeline built with LangGraph: document upload → risk element extraction → policy matching → human approval → report generation, compressing traditional 3–5 day reviews to minutes.
Overview
Key Features
LangGraph state graph: explicit workflow nodes (parse → extract → match → approve → generate) with conditional edges (high risk → human review, low risk → auto-pass)
Structured extraction: LLM extracts JSON-formatted risk elements (parties, amounts, durations, clauses) from unstructured documents
Policy matching engine: extracted elements compared against regulatory rules library, auto-flagging violations and risk levels
Human-in-the-loop node: LangGraph interrupt mechanism pauses for compliance officer annotation and judgment override
Audit trail: complete input/output, reasoning, and timestamps logged at every node to satisfy compliance audit requirements
Methodology
Workflow defined using LangGraph's StateGraph API. State fields include document content, extracted elements, matching report, and approval status. Conditional routing triggers human review when risk score > 0.7. Human-in-the-loop is implemented via NodeInterrupt, with the frontend polling a status endpoint. Structured outputs use Pydantic models to enforce LLM output schema consistency across nodes.
Tech Stack
Project Info
LangGraph Compliance Workflow Demo
Select a compliance document, run the state machine pipeline, and interact with the Human-in-the-loop approval node and conditional routing.
Compliance Document Review Workflow
LangGraph state machine: Doc Parsing → Risk Extraction → Policy Matching → Human-in-the-loop Review → Report Generation.
Select Document for Review