PDF Extraction

Intelligent Document Processing (IDP) is a category of software that extracts structured data from unstructured documents — automatically, reliably, and at scale.

Most PDF extraction projects start with the document. You open a PDF, look at the text, write a regex, extract a value. Repeat for each field.

Extracting data from PDFs in Python is straightforward for clean, simple documents. For production workflows — multiple layouts, edge cases, tables that span pages, scanned inputs — it requires a different approach.

If you’re extracting data from PDFs in Python, you’ll encounter three libraries repeatedly: pdfplumber, PyMuPDF (imported as fitz), and PyPDF2. They overlap in capability but differ in what they’re optimised for.

Extracting tables from PDFs is one of the most common requirements in document automation and one of the most reliable ways to introduce subtle errors if you do it carelessly.

Azure Document Intelligence (formerly Form Recognizer) is Microsoft’s managed IDP service. It handles invoices, receipts, purchase orders, and ID documents well — out of the box, with no custom training required for standard formats.