How RAG Helps AI Answer Questions Using External Information
, or RAG, lets AI search external information instead of answering only from what it already remembers. When someone asks a question, the system searches a and selects the most relevant material. It adds that material to the prompt, and the AI uses it to produce a more accurate answer that fits the question's context.
This approach can support customer-service assistants, internal company search, research tools, education, legal document search, and online shopping assistants. Related beginner topics include , embeddings, , GraphRAG, and AI agents, presented without heavy use of equations.
Key points
- The system searches a after receiving a question.
- It selects the information most closely related to the question.
- The retrieved material is added to the prompt as evidence for the answer.
- RAG can support customer service, company search, research, education, legal search, and shopping assistants.
- To control costs, limit unnecessary retrieved text and input tokens.