LEARNER · GLOBAL
What is RAG? How banks use retrieval-augmented generation to ground LLMs in real data.
RAG (retrieval-augmented generation) is a technique that pulls live data from external sources—customer records, regulatory rules, transaction histories—and feeds it into an LLM before generating an answer, so the model doesn't hallucinate. BBVA's customer-experience AI likely uses RAG to fetch conversation transcripts before analyzing them.
WHY IT MATTERS
RAG is the standard production pattern for enterprise LLM deployments; understanding it separates pilot-stage AI from ops-ready systems that comply with audit and explainability requirements.