This is a working part of your finance process, not a demo. Here is what the AI reads, how it checks the data, and how the clean output reaches your systems.
The model reads the invoices your suppliers already send. It handles native PDFs, scanned paper and photos, and finds the header fields and the line-item table without a template per vendor.
Extraction is paired with checks. Each field gets a confidence score, and rules confirm that totals match the line items and tax adds up. High-confidence invoices pass through, and anything below your threshold is flagged for a quick human review.
The result is named fields and line-item rows, not a scanned image. That structured data can be posted into your ERP or accounting system, so an invoice moves from received document to booked record without anyone re-keying it.
Invoice number, dates, PO reference, supplier and currency, read straight off the document.
Every row with description, quantity, unit price and amount, kept as a structured table.
Subtotal, tax lines, discounts and grand total, checked against the line items.
A score on each field, so high-confidence invoices pass through and the rest get a review.
Validated data posted into your ERP or accounting system, no manual re-keying.
The extraction and language models are chosen for your accuracy, cost and privacy needs.
Book a free consultation. Send us a few real invoices and we will show you the extraction, the confidence scores, and how the clean data would post into your systems.
Book a Free Consultation →