Definition
AI document extraction uses machine learning models, often large language models, to read documents such as purchase orders, invoices or quotations and turn their contents into structured data.
What is AI document extraction used for?
Older OCR tools read characters and need a fixed template for each layout. AI extraction interprets the document’s meaning, so it can handle different layouts, scanned PDFs and photos. The important controls are a strict output format, a confidence indicator and a rule never to invent values that aren’t in the document, followed by human review before anything is saved.
Example: a customer sends a 60-line PO as a phone photo, and AI extracts each line’s code, description, quantity and price for a salesperson to check against the customer purchase order.
Extraction speeds up data entry, but it doesn’t replace a person checking totals and terms.
View as text
- A salesperson opens a new draft quotation and chooses Import PO with AI.
- They drop in the customer's purchase order, PO-4471.pdf.
- 1flux imports 8 lines with a 94% confidence score: it fills the customer reference (PO-4471), the quote date and the currency (USD), and matches each item code to the catalogue.
- The salesperson chooses the customer and checks the totals. The source file stays attached to the quotation.