Bro do you even eigenvector??
The dimensionality of most RAG knowledge bases is at least 1000 parameters, and in the enterprise usecases I've helped my customers deploy they're upwards of 15,000 parameters. It's pretty crazy because at those higher dimensionality spaces you can start to categorize and encode wildly different types of information. You can entangle the lingustic meaning of "clear blue sky" with the actual color of sky blue, and the idea of warmer temperatures, and everything else that could contextually enrich that phrase.
Or brought into the business context, you can use a multimodal input to process and transform pictures of items coming off a production line for QA and create a pretty damn good description and written report that's checking visual and spatial qualities. Or you could feed a knowledge base all of your contracts originated from your various branch offices and have an O(1) lookup for the meaning within those contracts to determine what it is you've actually comitted to or are due. Sure you still have a lawyer validate it, but you can sift through SUCH A HUGE VOLUME of information incredibly quickly and accurately to only act on the things that need it.