Turning Documents Into Data Without a Keying Team

The three components

1. Extraction — pulling fields from the document, whatever its layout
2. Validation — checking the result against your master data and internal arithmetic
3. Routing — confident items proceed, uncertain items reach a person

Most disappointing implementations have the first and neither of the others, which is why they work in a demonstration and not in a month-end.

Validation is where accuracy comes from

• Does the supplier exist in your ledger?
• Do the line totals sum to the stated total?
• Does the tax figure match the rate and the base?
• Is the currency plausible for that supplier?
• Is this invoice number already recorded?

Extraction alone might reach 90%. Extraction with validation reaches the same accuracy but knows which 10% it got wrong, which is the property that makes automation safe.

What accuracy means here

Per field, not per document. A 95% per-field rate across twelve fields means barely half of documents are perfect, which is a very different conversation from “95% accurate”.

We report both, plus the straight-through rate, which is the number that determines how much work actually disappears.

Design for the awkward ones

Multi-page invoices, credit notes, scanned faxes, handwritten annotations, statements masquerading as invoices, and the one supplier who sends a spreadsheet. Every document set has these.

They will not be automated economically, and the system should identify them instantly and route them to a person rather than producing a confident wrong answer.

Typical results

Frequently asked questions