About Retrieval-Augmented Generation

Retrieval-Augmented Generation is an independent blog about one idea: Retrieval-Augmented Generation (RAG), the technique that pairs large language models with external information retrieval so their answers stay accurate, up to date, and grounded in real sources.

We publish plain-language explainers on how RAG works — retrieval, embeddings, vector search, and generation — and why it improves the reliability of LLM-powered applications.