The Answer Is an Edge, Not a Sentence — Building a Topology-Native GraphRAG Intelligence Platform with TigerGraph
The article describes the development of Shadow Network Intelligence, a GraphRAG-powered platform designed for financial crime investigations using TigerGraph. Traditional retrieval systems struggle with complex, multi-hop relationships, whereas GraphRAG preserves structural and topological connections critical in fraud detection. The platform was tested on a synthetic, relationship-dense dataset to demonstrate that 'the answer is an edge, not a sentence.'
- ▪Shadow Network Intelligence is a topology-native GraphRAG platform built for detecting financial crime through relationship reconstruction.
- ▪The system uses TigerGraph to enable graph traversal and topology-aware retrieval, outperforming traditional VectorRAG and PureLLM approaches.
- ▪A synthetic dataset with 175,204 vertices and 373,439 edges was created to test adversarial, multi-hop financial crime scenarios.
- ▪GraphRAG excels in reconstructing hidden structures like fraud rings, shell companies, and laundering chains where semantic similarity fails.
- ▪The platform includes specialized agents, reasoning engines, and a dashboard for operational intelligence and benchmarking.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3935527) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } feminist Posted on May 16 The Answer Is an Edge, Not a Sentence — Building a Topology-Native GraphRAG Intelligence Platform with TigerGraph #ai #database #python #graph How we built Shadow Network Intelligence — a GraphRAG-powered fraud investigation platform that proved why topology-aware retrieval outperforms traditional RAG for financial crime investigations. Introduction Most retrieval systems are built around documents. Financial crime investigations are not.
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