Retrieval-Augmented Generation
Retrieval-augmented generation, or RAG, grounds AI responses in retrieved documents, policies, FAQs, or knowledge-base entries before generating an answer.
Why it matters
RAG helps AI systems answer with current business context instead of relying only on model memory.
Examples
- Event FAQ support
- Policy lookup
- Internal knowledge search