For anything long term and high volume it's far cheaper to use open source solutions and hire a manual review team in the developing world where English is a common second language. Unless you are comfortable with the high rate of errors there's still a need for review.
For small one-off tasks the cloud solutions do fine.
Also quite expensive since it is at the head of the pack IIRC. There is probably some value in making a competitor with new deep learning techniques provided you have a sufficiently diverse training set. It would take years to build tho.
I've done some work on deep learning approaches - specifically table extraction.
It's not at all obvious how to make this work - there is a lot of human judgement involved in judging what a header is vs what are values, especially with merged header column/row columns.
Yeah I remember Abbyy also has an interface to define layouts for this kind of problem. I.E., this thing is a table and here are the headers etc.
Sorry, I was not trying to say deep learning would be a substitute for all such issues, just that new approaches may help a smaller team build those tools more efficiently.
I don't know if Abbyy combines its layout tool with training a model for customers, but it seems like a reasonable thing to build and expose.