Building
RAG (retrieval-augmented generation)
Letting an AI look up real documents before it answers.
RAG is a way to make an AI answer from trustworthy sources instead of just its memory. Before the model replies, the system searches a collection of documents, pulls out the most relevant bits, and hands them to the model to work from. This keeps answers current and grounded, and it lets the AI cite where its information came from.
For example
A company help bot uses RAG to pull the exact policy page before answering a customer's refund question.
Related
AI agentAn AI that can take actions and complete multi-step tasks on its own.Tool useAn AI reaching outside itself to use calculators, search, or other software.MCP (Model Context Protocol)A common standard that lets AI plug into apps and data sources.Function callingHow an AI asks software to run a specific action with the right details.