You are probably right, but there has been nothing like gpt4 before, having seen some versions before I would wager that their entire application can probably be redone for a fraction of the cost and it would work better... :)
This was done by hand by people like Footnoted. They received SEC filings using a key red flag word filter into a shared Gmail account with special attention for filings done on Friday night or ahead of the holidays.
I think using LLMs to ask a company about their company figures is missing the point. After all, XBRL already exists, and that data is widely accessible anyways. Where LLMs would add more value is analyzing changes in different sections of a company's filings, such as Risk Factors, MD&A, or governance filings.
Yes, I think the broader point is you have these readers available on call via api, so you can do all that you suggested and more...
These already exist and are not primitive. Groups have been applying NLP and analysis against text for longer than you would think.
Yes, they are definitely not primitive, but considering how the breakthrough in LLMs happened, i.e MSFT, GOOGL were working on it, even as late as 2021, Google's BERT was not really there (at least the one they showed the public in the blog from Google research). So the sudden jump from ok to great thanks to openAI would probably mean a lot of existing systems also need to do that.
You basically monitor the SEC website for when filings are made public, quickly parse the document in some automated way and make trades based on the output.
It wouldn't surprise me if some hedge fund has been trying to build something with LLMs for past few years (and possibly already deployed it).