{"slug": "built-an-agentic-fraud-investigator-using", "title": "Built an agentic fraud investigator using", "summary": "A developer built an agentic fraud investigator on TigerGraph for the HH Goa 2026 hackathon, chaining graph traversal, case memory, a policy engine, and next-best-action recommendations that produce suspicious activity reports. The project, with code on GitHub and a Streamlit demo, argues that because fraud is relational, the underlying database should be graph-based.", "body_md": "Built an Agentic Fraud Investigator using TigerGraph for #HHGOA2026 🚀\n\nMy agent investigates fraud like an analyst:\n\nGraph Traversal -> Case Memory -> Policy Engine -> Next-Best Action + SAR\n\nFraud is relational, so the DB should be too.\n\nRepo: [https://github.com/foxmaster77/tigergraph](https://github.com/foxmaster77/tigergraph)\n\nLInk : [https://tigergraph-2cd6jdrgrem2jblxb49zjj.streamlit.app](https://tigergraph-2cd6jdrgrem2jblxb49zjj.streamlit.app)\n\n@TigerGraphDB @247pmstudio", "url": "https://wpnews.pro/news/built-an-agentic-fraud-investigator-using", "canonical_source": "https://dev.to/sukalyan_ranasingha_c606a/built-an-agentic-fraud-investigator-using-4eeg", "published_at": "2026-09-24 18:20:23+00:00", "updated_at": "2026-09-24 18:29:42.322077+00:00", "lang": "en", "topics": ["ai-agents", "artificial-intelligence", "ai-tools"], "entities": ["TigerGraph", "HH Goa 2026", "GitHub", "Streamlit"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/built-an-agentic-fraud-investigator-using", "markdown": "https://wpnews.pro/news/built-an-agentic-fraud-investigator-using.md", "text": "https://wpnews.pro/news/built-an-agentic-fraud-investigator-using.txt", "jsonld": "https://wpnews.pro/news/built-an-agentic-fraud-investigator-using.jsonld"}}