AI invoice processing: from inbox to accounting system without retyping

The manual process today

In most SMBs, supplier invoices arrive at a shared inbox as PDF attachments. Someone in admin or finance downloads each one, opens it, types the supplier, invoice number, date, base amount, VAT and total into the accounting system, checks the sums by eye and files the PDF in a folder. With 300 invoices a month at 5 to 8 minutes each, that is 25 to 40 hours of skilled time spent copying numbers.

The errors are predictable: a transposed digit in the total, the wrong VAT rate, a duplicate invoice entered twice because it was sent to two addresses. They tend to surface weeks later, at month-end close or when a supplier chases a payment.

How the automation works, step by step

1. Intake. Invoices go to a dedicated address, for example invoices@. A watcher picks up each new email and saves the attachments to a Drive folder.
2. Extraction. Claude reads the PDF or image and extracts supplier name and tax ID, invoice number, dates, line items, tax base, VAT rate, withholding if any, and total.
3. Checks. The workflow verifies that the lines add up, that the VAT rate matches the supplier’s usual rate, that the tax ID exists in your supplier list and that the invoice number has not been entered before.
4. Draft entry. A draft is created in your ERP or accounting tool with the PDF attached and the expense account suggested from that supplier’s history.
5. Review queue. Anything that fails a check, or has low extraction confidence, is flagged in a review list with the reason. Clean invoices are grouped for one-click approval.
6. Log. A Google Sheet records every invoice processed, its status and any correction, so you can see the time saved and the error rate each month.

What you need

• A mailbox or folder where invoices arrive, and permission to redirect them.
• An ERP or accounting tool with an API, or at least a stable import format.
• Your supplier list with tax IDs, and ideally a few months of past entries so the workflow can learn your usual accounts.
• A Claude API account in your company’s name. You pay Anthropic directly.

Limits and human review

AI extraction is very accurate on typed invoices, but not infallible. That is why nothing is posted without passing the checks, and why the default is a person approving every draft. Handwritten notes, invoices with dozens of lines spread over several pages and credit notes are the usual edge cases; they go to the review queue with a clear explanation. The workflow never pays anything: approving payments stays a human decision.

Typical timeline

A first version for your main suppliers is usually live in 2 to 3 weeks: one week to connect the mailbox and the accounting system, one to tune extraction and checks with real invoices, and a final week running in parallel with the manual process before switching over. This is a typical AI implementation project. If you are not sure invoices are your biggest time sink, start with a process audit, as in the case of the distributor that stopped retyping email orders, which used the same extraction approach for incoming orders.