Document understanding
Teaching a model to read, parse, and extract meaning from PDFs, forms, receipts, and scanned pages.
Think of it like
Like hiring a careful librarian to skim a messy stack of papers and pull out the facts you need.
Example
An invoice processor reads text and layout, finds the total amount, date, and vendor — then slots them into a database without manual entry.
How it actually works
Modern approaches combine vision (reading the layout and text position) with language (understanding context). Layout matters — where text sits on the page is semantic. Tables, headers, and field labels carry structure that pure OCR misses. Multimodal models excel here.
For product teams
Shrinks manual data entry and unlocks automation for paper-heavy industries — finance, insurance, contracts.
For engineers
Typically a pipeline: image → text extraction (OCR) → layout parsing → entity extraction + relation detection.
Related
- Layout analysis — Builds on layout analysis to understand spatial structure.
- Handwriting recognition — Text extraction step often leverages character recognition.
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