Retrieval-Augmented Generation (RAG) combines a large language model with external knowledge retrieval. Before generating a response, the AI retrieves relevant information from documents, databases, or knowledge bases to improve accuracy and relevance.
Voice AI platforms use RAG to provide accurate, up-to-date, and organization-specific answers without retraining language models. It is widely used in customer support, enterprise search, AI voice agents, and knowledge assistants.