ARVK Labs · Learn · Gen AI Explained

How RAG works

Retrieval-Augmented Generation in motion — watch a question flow through the pipeline and come back as a grounded answer. (A sample of the interactive explainers a Learn hub could host.)

Question"How do I…?" Embed→ vector Vector DBfind similar chunks LLM+ retrieved context Answergrounded
1 · AskYou type a question.
2 · EmbedIt's turned into a vector.
3 · RetrieveClosest chunks are found in the DB.
4 · GenerateThe LLM answers using that context.
5 · AnswerGrounded, with citations.
RAG keeps an LLM grounded in your own data — instead of guessing from training memory, it answers from the exact documents you retrieved. This is the foundation of every enterprise AI assistant, and one of the first systems you build in FORGE.
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