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RONI DAS5d ago · 34 min read

Neo4j Context Engine, Explained: An Ontology That Tells AI Agents What Your Words Mean, and a Lab You Can Run

On 19 October 2026 Neo4j announced Context Engine, a product that gives AI agents a map of what a company's words mean and where its data lives. It is in private preview, so I could not use it. I buil

systemdesignacademy.hashnode.dev

Tejas PawarOct 13 · 5 min read

Attackers Think in Graphs, Defenders Think in Lists: Why AI Must Learn to Navigate Networks

Imagine waking up to an alert from your security dashboard: “Critical Vulnerability Detected on Server DMZ-04.” What do you do? If you are like most network engineers or security analysts, you start s

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Muhammad TahirOct 2 · 14 min read

Architecting Agentic RAG: Autonomous Multi-Agent Synthesis Engines

This article was originally published on Muhammad Tahir's Portfolio. Introduction & Industry Context In the rapidly evolving landscape of enterprise artificial intelligence, retrieval-augmented genera

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Piyush BadodeSep 24 · 6 min read

Beyond the Risk Score: Building an Evidence-First Autonomous Fraud Agent with TigerGraph

How we built NexusWatch AI for the TigerGraph × Hackathon Goa 2026 Challenge to eliminate hallucinations and dismantle coordinated fraud syndicates using GraphRAG and deterministic policy gates. 1. T

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RONI DASSep 19 · 434 min read

How to Build a GraphRAG System with Python, Neo4j and ServiceNow [Full Book]

Somewhere in your company's ServiceNow instance is the answer to the question an engineer asks at two in the morning: if this is broken, what else is about to break? Every fact needed to answer it has

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The Flux ReadAug 23 · 7 min read

RAG vs. GraphRAG for Enterprise AI Agents: Architecture, Data Governance, & Latency Bottlenecks

Standard Vector-based Retrieval-Augmented Generation (RAG) is hitting a hard operational ceiling in enterprise environments. While dense vector embeddings excel at semantic similarity search across un

thefluxread.hashnode.dev

Aman KarkiAug 16 · 6 min read

I Built an AI Refactoring Tool That Can't See More Code Than the Dependency Graph Allows

I've spent few days building RAAG — a platform that parses code, builds a dependency graph, computes coupling metrics, and indexes the code for semantic search. Every piece of that was in service of o

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Neural CoreTechJul 29 · 1 min read

Are million-token context windows taking us in the wrong direction?

Modern Large Language Models can reason remarkably well, but they still suffer from one fundamental limitation: they don't retain knowledge between sessions. The common response has been to increase c

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Joshua Junsu KimJul 6 · 8 min read

The Euclidean Sinkhole: Why Local Dense Vector RAG Fails at Personal Knowledge Sensemaking

Tags: RAG, Vector Database, LLM, GraphRAG, Python, System Architecture TL;DR When building Retrieval-Augmented Generation (RAG) systems over personal knowledge archives (like Obsidian vaults or deve

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Nidhish KumarJul 2 · 9 min read

I Almost Made the Wrong RAG Pipeline the Default

Project Repo: Modular RAG I almost made my most complex RAG pipeline the default. It had query rewriting, multi-query expansion, hybrid retrieval, graph expansion, and reranking. It looked like the se

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