When I started designing the RAG architecture for the internal AI assistant project, one of the first decisions I had to make was: Where should the application's knowledge live, and which component should be responsible for turning that knowledge into something the model can retrieve? There are several ways to build a RAG system on AWS. I could assemble and manage the retrieval components myself, use a vector database directly, or use Amazon Bedrock Knowledge Bases to manage much ...