LEARNER · GLOBAL
What is Retrieval-Augmented Generation (RAG)?
RAG is a technique that lets LLMs fetch real-time data from external documents or databases before generating answers. Instead of relying only on weights baked into training, an LLM retrieves relevant context, then reasons over it—dramatically reducing hallucination and keeping answers current.
WHY IT MATTERS
Banks and insurers use RAG to ground LLMs on live regulatory rules, customer data, or transaction records without retraining. It's the backbone of compliant chatbots, Q&A systems, and risk-engine integrations—trades speed for accuracy by coupling retrieval + reasoning.
Source: AITechHive · 2026-08-29