Building an Agentic Fraud Investigation System with TigerGraph, LangGraph & MCP
TL;DR : We built a 9-node LangGraph agent that investigates fraud cases end-to-end. It uses TigerGraph Community Edition as the knowledge graph substrate, TigerGraph MCP for tool access, and NVIDIA NIM for LLM reasoning. It produced FinCEN-standard SAR narratives for cases requiring regulatory filing, and wrote every case back to the graph as memory for future investigations. All 20 HHGOA…
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