Finance Document Reading with AI

The problem

Documents arrive as PDFs and emails; someone reads each one and types the figures into the ERP or a spreadsheet. It is slow, it is where errors enter, and the people doing it are the same people needed for the close.

What we build

A Python workflow with an AI reading step: documents in, fields out, each with a confidence flag. High-confidence rows flow through; the rest go to a person with the document beside them. Starts with one document type as a pilot, measured, then widened.

What you receive

• Document workflow for one document type (e.g. supplier invoices or bank statements)
• Extracted fields in a table your ERP or Excel can take
• Confidence flags, so a person checks only what the model was unsure about
• Structured summary per document, kept with the original
• Pilot report after the first month: time saved, error rate, next document type

What we need from you

Fifty to a hundred past documents of one type, with the values your team entered for them, so the pilot can be measured against the truth.

How it runs

1. 1 · Understand
2. 2 · Map
3. 3 · Build
4. 4 · Validate
5. 5 · Train & hand over