What is RAG, really?

Retrieval-Augmented Generation (RAG) connects a language model to your own data. Instead of relying only on what the model memorized, RAG retrieves relevant documents at query time and feeds them into the prompt.

The result: answers grounded in your knowledge base, fewer hallucinations, and the ability to update knowledge without retraining. In this post we break down the moving parts — embeddings, vector search, and the generation step.