We are working on PDF data extraction doing a POC with a few LLMs like Claude, Co-pilot, Power automate, Textract etc. While, machine printed pdfs are fairly trivial and accurate from LLMs extraction, we are running into a challenge with hand written PDFs, as the image clarity is often very poor. Despite trying to OCR it and then parsing, it is not working well. I am trying to figure out, if anyone has a better suggestion or solution for this need?

So we got this challange from one of our customer and we've solve it custom solution. If you share your usecase/senario, I am happy to see if we can support you with any insights, because we've spend some good time there.

Take a screen shot and feed it to LLMs they do a better Job, Also try Google's Document AI had good experience with it.

We had a good experience using the Docling library (https://docling-project.github.io/docling/). It was able to extract accurate data even in low quallity scenarios.

We have found quite a bit of success using Microsoft AI Document Intelligence. It's worth checking out.

Handwritten PDFs can be tricky, especially when the scans are low quality. 

Clean up the images first (contrast, noise removal, deskewing)

Use OCR that’s designed for handwriting (like Azure Read or TrOCR)

Or even let a vision-capable LLM look at the image directly to extract info

For tricky parts, a quick human check can save a lot of headaches

This approach usually works much better than just running standard OCR.