That sounds more like semantic search and vector db.

RAG is simply fetching external data (retrieval) and adding it to LLM context (augmenting) prior to generating a final response.

Any time LLMs do a grep or a web search to answer the query, it’s RAG. Many people use vector db for their own RAG implementation bc of the semantic search benefits.