You can think of it like this, you now have an army of readers that can go through tables really quickly.
FactSet, CapIQ etc use a combination of automation/manual entry and fit these tables into a homogenized schema so that they can be saved, compared etc. So if you want to get Apple's Greater China sales from 2020, you would be lucky if they decided to create an item for that. https://imgur.com/a/bp2hb7n
Here are two examples, AMD's revenues and AMD's revenue outlook using beatandraise.com https://imgur.com/a/61jqiUk I doubt you can get AMD's own outlook on CapIQ for e.g
Context sizes mean getting 100s of reports on one call is not possible, but multiple iterations will still do the trick. So in effect, you can actually create a dataset like FactSet for a lot lower cost, more comprehensive and can be customized to what the user wants, if you see my point... :)
If we run this query over an api for income statements for all 8k companies, we pretty much have all income, balance sheet, cashflow items, shares outstanding etc. Add stock price data, that can give you EV/Ebitdas, P/Es and all that stuff.
When you say that generating graphs of gross margin, EV/Ebitda is just one step further, are you talking about generating those based in just a single report's information or are you combining information from multiple years to for example show gross margin trends over 10 years and EV/TTM Ebitda?