This PDF is a service call report covering 911 incidents at the Rainforest Cafe in Niagara Falls, NY. We're hunting for animals! The data is formatted as a spreadsheet within the PDF, and challenges include varied column widths, borderless tables, and large swaths of missing data.

This PDF has a data table showing election results from the Tunisian region of Mednine. Challenges include spanning header cells and rotated headers. It has Arabic script.

This PDF is all sorts of information about the Board of Education in Liberty County, Georgia

Extracting information from declassified CIA documents using AI

This PDF contains a set of complaint records from a local law enforcement agency. Challenges include its relational data structure, unusual formatting common in the region, and redactions that disrupt automatic parsing.

This PDF is a document from the OECD regarding the PISA assessment, provided in Czech. The main extraction goal is to get the survey question table found on page 9. Challenges include the weird table format, making it hard to extract automatically.

This PDF is the weekly “Focus” report from Brazil’s central bank with economic projections and statistics. Challenges include commas instead of decimal points, images showing projection changes, and tables without border lines that merge during extraction.

This PDF contains data on wait times at a state agency call center. The main focus is on the data on the first two pages, which matches other states' submission formats. The later pages provide granular breakdowns over several years. Challenges include it being heavily pixelated, making it hard to read numbers and text, with inconsistent and unreadable charts.

This PDF contains legal bills from the Georgia legislature, published yearly. Challenges include extracting marked-up text like underlines and strikethroughs. It has line numbers that complicate text extraction.

Learn the fundamentals of Natural PDF - opening PDFs, extracting text with layout preservation, selecting elements by criteria, spatial navigation, and managing exclusion zones. Perfect starting point for PDF data extraction.

Master OCR techniques with Natural PDF - from basic text recognition to advanced LLM-powered corrections. Learn to extract text from image-based PDFs, handle tables without proper boundaries, and leverage AI for accuracy improvements.

Extract text from complex multi-column layouts while maintaining proper reading order. Learn techniques for handling academic papers, newsletters, and documents with intricate column structures using Natural PDF's layout detection features.