A toy space with real math
Real embeddings have hundreds or thousands of dimensions, which no screen can draw. This model squeezes a small library of example farm passages into three dimensions so you can see the idea: passages about similar things sit near each other, and retrieval is literally measuring distance and keeping the nearest ones.
Why RAG matters for business
A language model on its own only knows what it saw in training, which goes stale and never included your private documents. RAG lets a company keep its knowledge in a store it controls and update it any time, while the model handles the language. It also makes answers auditable, because each one can point back to the passages it used.