Is there a SOTA OCR model that prioritises failing in a debuggable way?

What I want is an output that records which sections of the image have contributed to each word/letter, preferably with per word confidence levels and user correctable identification information.

I should be able to build a UI to say: no, this section is red-on-green vertically aligned Cyrillic characters; try again.

The relevant term is "bounding box", as you probably need the confidence level of a character or word, not just the image. I built such an interface. I think the effort is only worth it if you really have multi-millions of pages.

Niels lately posted a lot about other OCR engines: https://www.linkedin.com/posts/niels-rogge-a3b7a3127_lots-of...