Retrieval Augmented Generation. Fancy way of saying, retrieve chunks from your document corpus similar to your input using a similarity (mostly cosine) of embedding vectors of the chunks and input vectors, then inject those relevant chunks into your prompt to the LLM. Useful for Document Intelligence.
Retrieval Augmented Generation - using search (usually with some kind of semantic component) to find relevant context and provide it to the language model to help it respond, give it knowledge about a specific document, etc.