Dictionary
RAG (Retrieval-Augmented Generation)
Inject external knowledge into an LLM at query time.
Definition
Retrieval-Augmented Generation is a pattern where relevant documents are retrieved from a vector store and inserted into the model's context before generation, grounding answers in source material.
Example
A support bot retrieves the 3 most relevant help-center articles for a user question and asks the LLM to answer using only those sources.
Related Workflows
Related Tool Stacks
Related Prompts
↳ connected nodes
Workflow↳ linked
Build an Internal Knowledge Bot
Ship a Slack bot that answers questions from your company docs.
Workflow↳ linked
AI Customer Onboarding Flow
Walk every new user through activation with an AI guide.
Tool Stack↳ linked
RAG Starter Stack
Minimum viable stack to ship a production RAG chatbot.
Prompt↳ linked
Grounded Answer Prompt
Force the model to answer only from provided sources, with citations.
Workflow↳ linked
RAG Content Ingestion Pipeline
Convert messy docs into searchable, cited knowledge chunks for AI systems.