Learn how Retrieval-Augmented Generation (RAG) works on AWS using Amazon Bedrock, Knowledge Bases, embeddings, and Amazon S3 through a realistic HR chatbot scenario. Why Everyone Is Talking About RAG AI chatbots are becoming a major part of modern businesses. Companies want AI assistants that can answer questions about: internal company documents support articles training manuals policies product documentation customer knowledge bases The Problem Large language models (LLMs) do not automatically know your company’s private information. This is where Retrieval-Augmented Generation (RAG) becomes incredibly important. Instead of training a custom model from scratch, businesses can allow an AI model to retrieve relevant company information in real time before generating a response. This creates a smarter, more cost-effective AI assistant. In this article, we’ll walk through a beginner-friendly AWS architecture for building a RAG chatbot using Amazon Bedrock. What is RAG?…