Transform unstructured invoices into beautifully organized spreadsheets. Forget manual entry, let the machine do it.
Three steps — from raw PDF to structured data, ready for your workflow.
The key to great results
Upload a single PDF containing multiple samples of the same invoice type — all sharing the exact same layout.
⚠ Mixing layouts gives unexpected results
You can submit a PDF with invoices from different vendors or layouts — the system will still process it. However, mixing them will likely produce inaccurate or incomplete data.
✓ For excellent results
Including variable line items
Once uploaded, the AI reads each sample and extracts all fields — including line-item tables with any number of rows. No template, no fixed row count.
Learns the layout once
From the sample set, the model identifies every field and the exact table structure.
Handles spanning tables
Line items spread across multiple PDF pages are joined into a single contiguous table.
Variable row counts
Each invoice sample can have a different number of line items — the engine captures all of them.
Excel & CSV — ready to use
The extracted data is available right from your results. Download it as Excel (.xlsx) or CSV (.csv) — every extracted field becomes a column, every document sample becomes a row.
EXCEL .xlsx
Open directly in Excel, Google Sheets, or any spreadsheet tool. Ideal for reviewing and sharing.
CSV .csv
Import into any system: accounting software, ERP platforms, or databases.
Our system learns the structure dynamically. No rigid templates required. It just works.
Works with thousands of invoice layouts without human setup.
Precisely maps multi-page nested line items to tidy rows.
Upload the exported Excel row directly to SAP or QuickBooks.
Catch duplicate invoices or mismatched PO totals automatically.
No. Our system gets the context using AI, so you just upload the invoice and it finds the fields.
Yes, it intelligently links line items across pagination so you have a contiguous table.
The AI is multilingual. English, spanish and french are supported.
© 2025–2026 NOLAIN OCR. ALL RIGHTS RESERVED.