Is RAG even necessary here? Minimal information like a couple of price list with job times and opening hours should easily fit into any context window, right? It's not like he's dumping entire service manuals into the vector database here...
It most likely isn't, but it seems like this project was more for learning purposes than for anything else. In that case, why not go for the "production-ready", "highly scalable" solution? I sometimes do the same for my personal projects. I over-architect them not because it's necessary, but because I want to get my hands dirty and learn something new.
For voice conversations the issue can be more latency than filling the context. Without knowing the site is hard to say, but if he had multiple pages worth of text (dunno, type of cars, procedures, some emotional story, etc.) and a "slower" model, it might be worth it to use RAG to preselect fast a small portion and use LLM to refine the answer.
