Extracting data from PDF supplier invoices into your accounts system
A worked example of using document AI to read supplier invoices and post them to an accounting or ERP system, with a person reviewing anything uncertain.
This is a worked example of our approach, not a client case study.
The situation
A typical case: an accounts team receives supplier invoices as PDF email attachments in many layouts, and keys the supplier, dates, line items and VAT into the accounting system by hand. It is slow, repetitive and error-prone, and it piles up at month end.
How we would approach it
Watch the invoices mailbox and pick up new PDF attachments automatically.
Extract the text with OCR, then use a language model to pull out supplier, invoice number, dates, totals, VAT and line items into a fixed structure.
Validate every invoice against rules: totals add up, VAT is calculated correctly, the supplier exists, the invoice is not a duplicate.
Send anything that fails validation or has low confidence to a review screen, where a person checks it before it is posted.
Post approved invoices to Xero, Sage or the ERP through its API, with a link back to the original PDF.
Typical technology: Python, FastAPI, OCR, OpenAI or Anthropic models, Xero / Sage APIs.
What changes for the team
- No manual keying for invoices that pass validation
- People spend their time on exceptions, not routine data entry
- Every posted invoice is traceable to its source document
- Data stays within agreed processors, with GDPR obligations documented
Related service: AI automation
Got a process like this?
Send a short brief and we will come back with questions, a rough approach and whether we are the right fit. No sales sequence.
Prefer email? info@elslabs.co.uk
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