Index-RAG: Citation-first approach to RAG

The silent citation crisis in RAG systems is finally solved. Meet Index-RAG. Your AI Just Lied About Its Sources — And It Doesn't Even Know It You ask your AI assistant a question. It gives you a confident, well-structured answer and tells you it came from "page 5 of the compliance manual." You go to page 5. It's not there. It never was. This isn't a fringe bug. It's the defining flaw of how most AI retrieval systems are built today — and for industries where source accuracy is non-negotiable, it's a dealbreaker. A new paper, Index-RAG: Storing Text Locations in Vector Databases for Question-Answering Tasks , presents a deceptively simple but genuinely powerful fix. And if you're building or using AI systems that need to cite sources — in law, medicine, finance, compliance, or research — this is the most important RAG paper you'll read this year. The Hidden Flaw in Traditional RAG Retrieval-Augmented Generation (RAG) was supposed to solve AI hallucination. The idea: instead of asking a