I think the difficulty was specifically with CAPTCHA challenges, which had to be quick to generate but still legible - OCR on physical documents has to be robust to a different set of problems

That said, what kind of errors are you getting? I think the main practical difference between Tesseract's LSTM-based OCR and newer VLM-based OCR like PaddleOCR [1] is (hopefully) getting to skip making heuristics for the layout of the document, but errors possibly compounding over multiple tokens - are you getting individual illegible words or having the documents smooshed together because the OCR can't parse the layout?

[1] https://github.com/PaddlePaddle/PaddleOCR