Posting this because the "how do I extract a table from a PDF" question comes up here constantly, and the answer is usually "try pdfplumber" or "use Tabula"  which work fine until someone hands you a scanned PDF where the table has merged cells, or the document has two columns and the text extraction reads straight across both of them.

Nanonets just released OCR-3. It's an AI model (not a traditional OCR tool like Tesseract), and the table handling is the part that's actually different from what's been available.

What it does differently:

Simple tables come back as clean markdown. You get rows and columns, pipe-separated. Easy to paste into a spreadsheet or convert to CSV.

Complex tables, merged cells, headers that span multiple columns, nested sub-tables — come back as HTML with the structure preserved. colspan, rowspan, indentation all intact. If you've ever tried to copy a financial table from a scanned 10-K filing and gotten a wall of jumbled text, this is the problem it solves.

Multi-column documents (court filings, academic papers, newsletters) get the reading order right. Left column first, then right column. Sounds obvious but most OCR tools just go left-to-right across the entire page width.

Every extracted piece of text also comes with the exact coordinates of where on the page it was found. If you need to verify that a number was read correctly, you can trace it back to the source region.

It's an API, not a desktop app. You send a PDF, you get structured output back. There's also a confidence score on every extracted element — basically the model telling you how sure it is about each value. Useful if you're processing a stack of documents and want to know which ones need a human check.

It's a paid service, not free like Stirling-PDF or OCRmyPDF. But for anyone who's spent hours manually fixing table extractions from scanned documents, the accuracy difference might be worth looking at. 

[https://nanonets.com/research/nanonets-ocr-3](https://nanonets.com/research/nanonets-ocr-3)

What types of PDFs are giving you the most trouble? Scanned tables seem to be the universal pain point but curious what else people are fighting with.

Extracting tables from scanned PDFs without losing the structure — Nanonets OCR-3 handles merged cells and multi-column layouts