Receipt & Expense Extraction.

Most expense workflows break down on the same detail: receipts are the worst-formatted documents a business processes. Thermal print fades, phone photos come in at an angle, and no two merchants lay out a total the same way. Receipt and expense extraction exists to read that mess anyway, without a person retyping totals into an expense report by hand.

Axia Extract uses AI rather than a fixed template, so it doesn't need to recognize a specific merchant's layout to extract the fields you care about: merchant name, date, line items, tax, total, and category if you define one. That's the difference between a tool that only works on receipts it was trained on and one that works on the receipt an employee actually hands in.

Accuracy on real-world receipts, not clean samples, is what decides whether a tool is usable in production. Axia Extract publishes its benchmark openly: 98.2% average field accuracy and 99.9% on totals, tested against SROIE2019, a public dataset of 347 real receipts with mixed formatting and print quality, detailed on the accuracy page. Every field returns its own confidence score, so a hard-to-read line item routes to a reviewer instead of getting silently accepted at face value.

Employee expense reporting, accounts payable teams processing vendor receipts, and expense management platforms embedding extraction through the API all hit the same wall without it: manual re-entry that doesn't scale past a handful of receipts a day. The same schema-first approach covers full invoices once a vendor relationship grows past one-off receipts, and our guide to AI OCR for business documents covers what to check before picking a tool. Results export to CSV, JSON, or Excel, or pull directly through the REST API into an existing expense or accounting system.