Grounding an LLM: what RAG actually buys you

Retrieval-augmented generation isn't magic — it's a filing system. You chunk your content, embed it, and at query time you pull only the passages that actually matter, then ask the model to answer from those passages only.

The payoff is grounding: the model stops guessing and starts citing. That's the same pattern behind Botaura, just scaled down.