AI Search and RAG Topic Hub

AI search and retrieval-augmented generation connect language models to external information. This hub helps readers understand when to use RAG, how vector search differs from keyword search, and why retrieval quality matters as much as model choice.

Start here

Use this page as a guided path through related explainers and comparisons. Start with the broad overview, then move into the implementation, evaluation, and risk topics that match your project.

Key questions

• When is RAG a better fit than fine-tuning or a longer prompt?
• How do vector databases, keyword search, and ranking layers work together?
• What should teams verify before trusting AI-generated answers from retrieved sources?

Related guides

• What is Retrieval-Augmented Generation (RAG)?
• RAG vs fine-tuning
• Vector databases vs keyword search
• What are vector databases?
• Perplexity vs ChatGPT Search