Building Casework: An Agentic Fraud Investigator with TigerGraph and GraphRAG

<p>Building an Autonomous GraphRAG Fraud Investigation &amp; Next-Best-Action Agent with TigerGraph</p> <p>A deep-dive into graph-native financial crime investigation,

<h1> SentinelGraph: Building a Graph-Powered AI Cybersecurity Investigation Agent with FalkorDB </h1> <p><em>How connected data can help security analysts investigate alerts,

<h1> EcoGraph AI: Why I Built a Knowledge Graph to Solve E-Waste Compliance </h1> <p>If you manufacture electronics, figuring out e-waste compliance is a nightmare.</p> <p>You're

<p>RAG is not dead. It just got promoted. For years, retrieval-augmented generation helped apps pull the right documents before an AI answered. Now, AI agents need something

<!-- SC_OFF --><div class="md"><p>I have built a programmable governance layer for AI agents. I am considering to open source completely. Looking for feedback.</p> <p>Agent demos

arXiv:2607.07721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) and agentic frameworks have advanced enterprise AI considerably, yet agents remain

<p><strong>This is a submission for the [GitHub Finish-Up-A-Thon Challenge]</strong></p> <p><strong>What I Built</strong><br /> Ten million property transactions happen in India

<blockquote> <p><strong>GitHub:</strong> <code>Arul1998/hackerrank-orchestrate-solution</code></p> </blockquote> <p>Insurance and warranty claims appear straightforward: customers