Definition
Look up relevant documents from your data first, then ask the LLM to answer using only those documents.
In practice
RAG is the most reliable way to ground an LLM in your specific business data — your docs, your past tickets, your SOPs. Pipeline: embed your documents into vectors, store them in a vector DB, and at query time retrieve the top-K most similar chunks and pass them to the LLM with a strict 'answer only from this context' instruction. Cheap, controllable, and dramatically reduces hallucinations.