Why would the size of your docs have any bearing on whether or not the chunking process works? That makes no sense. Unless of course they're operating on the document entirely in memory which seems not very bright unless you're very confident of the maximum size of document you're going to be dealing with.
(I implemented a RAG process from scratch a few weeks ago, having never done so before. For our use case it's actually not that hard. Not trivial, but not that hard. I realise there are now SaaS RAG solutions but we have almost no budget and, in any case, data residence is a huge concern for us, and to get control of that you generally have to go for the expensive Enterprise tier.)
Not all problems have to be solved. We just fell back to using older, more proven technology, started with the simplest implementation and iterated as needed, and the result was great.
RAG worked well for us in this recent case but, in 3+ years of developing LLM backed solutions, it's the first time I've had to reach for it.
I think this turned out to be one of those lessons about premature optimization. It didn't need to be as complex as what people initially assumed. Perhaps with older models it would have been a different story.