Finance teams are under pressure to do more with less, faster approvals, better accuracy, and no increase in headcount. Invoice data extraction as a service offers a scalable, flexible way to automate without complex IT projects. Here are the key questions decision makers ask when exploring this solution.

What is invoice data extraction as a service?

It’s a cloud or on premise solution that extracts structured data from unstructured supplier invoices, including scanned PDFs and image files, and delivers it to your finance system. At DOConvert, we provide this as a service with no setup, no templates, and no ongoing maintenance required.

How is this different from OCR tools?

OCR tools read text. DOConvert goes further, it understands the context of the invoice, validates the data (like PO numbers or vendor codes), and connects it to your ERP. We also handle multi line tables, currency conversion, and supporting documents like delivery notes.

Which finance systems does it connect with?

Our system integrates directly with Priority ERP and other platforms like SAP, Oracle, and NetSuite. The data we extract is mapped exactly to your system’s requirements, including header and line level fields.

Can it replace internal AP staff?

No, and it shouldn’t. Instead, invoice data extraction frees your team from manual data entry so they can focus on approvals, payments, and exception handling. For most clients, we reduce 80 to 90 percent of the manual work, not the people.

Is it cost effective for small to mid sized companies?

Yes. There’s no expensive license or setup fee. DOConvert charges by volume (number of pages or invoices), so even companies processing just a few hundred invoices per month benefit from automation. No need to hire extra staff or outsource.

What kind of documents does it support?

We support commercial invoices, pro forma invoices, delivery notes, and customs forms. The system automatically classifies the document type and applies the right logic, even if the supplier changes the layout from one month to the next.

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