Building a Real-Time Agentic Fraud Sentinel using TigerGraph, FastAPI, and Verce

<blockquote> <p>A suspicious transaction starts an investigation. The harder part is deciding what evidence to gather, what remains uncertain, and which action is justified.</p>

<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

<p>As a solo developer, the biggest bottleneck isn't usually the ideas—it's the time required to execution. Recently, I wanted to launch a suite of free web tools for developers

<h2> The Problem That Made Us Build This </h2> <p>Phishing emails are getting much harder to identify.</p> <p>They’re no longer the obvious scam messages with bad grammar or

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