Building a Local RAG System with Citations (No Hallucinations)

Part of my 24-week journey: Mapping the Blueprint for the 2030 AI Stack By Subrata Kumar Das The Problem (A Real One) Let’s start with something simple. You’re inside a company, and someone asks: “What’s our password reset policy?” The answer exists. Somewhere. In an SOP document Maybe updated last quarter Possibly duplicated across versions Now imagine a worse scenario: 🚨 A production incident happens. Someone asks: “Have we seen this before? What was the fix?” And now… You don’t have time to search folders. You don’t have time to guess. You need accurate answers, fast, and with proof. Week 2 Project: Local RAG System This week, I built a Local Retrieval-Augmented Generation (RAG) system. Not a chatbot. Not a demo. A grounded AI system that: Only answers from provided documents Provides citations for every response Refuses to hallucinate when data is missing And most importantly: It runs locally 🔐 What Data Did We Use? To simulate real-world usage, we ingested: 📂 IT SOPs 📑 Inciden