I'm currently solving this problem for work and thinking of a spin out, what's a ballpark figure you'd be willing to pay per 1000 pages for 99.999% character level accuracy?
At least for my use case, which is Layout processing (i.e. must output tables in some kind of table format), the OCR part (Azure Document AI or AWS Textract) dominates the cost factor.
Running OCR on a document is twice more expensive than processing the output on the most expensive GPT offering. Intuitively, this was kind of unexpected for me. Only when I did some calculations on Excel that I realized it.
If you’re able to halve the pricing for Layout output then you’re unblocking lots of use cases out there.
> I'm currently solving this problem for work and thinking of a spin out, what's a ballpark figure you'd be willing to pay per 1000 pages for 99.999% character level accuracy?
I guess anything up to 5 ¢ per page would be acceptable. But I'm afraid my company wouldn't be a customer. We are in Germany and we deal with particularly protected private data, there is no chance that we would exfiltrate this data to a cloud service.
I'm not using generative models to fill in details not present in the original document. If there's a typo there then there will be a typo in the transcript. If you want to fix that then you can run another model on top of it.
I realise that. The point is that a user is implicitly committing to the baseline error rate that exists in whatever means by which the document was created. If any additional loss was insignificant in proportion to that error rate then it would be unreasonable to reject it on that basis.
Running OCR on a document is twice more expensive than processing the output on the most expensive GPT offering. Intuitively, this was kind of unexpected for me. Only when I did some calculations on Excel that I realized it.
If you’re able to halve the pricing for Layout output then you’re unblocking lots of use cases out there.