Retrieval-Augmented Generation (RAG) has become the default architecture for building AI-powered document intelligence systems. Most implementations follow the same pattern:


Split documents into chunks
Convert chunks into embeddings
Store them in a vector database
Retrieve the most similar chunks
Send them to an LLM to generate answers


This...