I built a simple pipeline with bash and python. Did it for free for learning, but it has been deployed and used in a professional setting on daily basis for almost a year now. (Use case: fax with headers and tabular data).
Most of time was spent in field parsing and validating ocr output (is it valid date). At one point I realized that playing with tess config was giving marginal improvement, and investment in post-ocr parsing/wrangling was more valuable e.g. in date column, if ocr says b, consider it 6 and flag low confidence record.
One new nice-to-have use case customer asked was varying orientation of pages, that I couldn't hack together quickly.
I use a £15 arm with a vice grip for my phone from Amazon, copy the files to my laptop and then run a bash for-loop of the tesseract CLI over the resultant files.
I use https://github.com/4lex4/scantailor-advanced to deskew the images and generate the PDF.
It isn't perfect but my purposes are more around research than publication, so, YMMV!
Thanks for this and the other replies!
One point of friction has been selecting an OCR workflow. Any chance you would share what you’ve been successful with?