Invoice OCR products no longer differ much on reading a clean invoice, which makes accuracy comparisons unhelpful. What still separates them is what happens at the edges: how uncertainty is signalled, what reaches a person, and how quickly a correction can be made. Those three determine how much review time you actually owe after buying.
Confidence, exposed per field
Good products return a confidence value for each extracted field and let you set the level at which it goes to a person. Products that return a value with no signal about certainty force you to choose between checking everything and checking nothing, and the second option is how wrong data reaches a ledger quietly.
The review screen
The document beside the field, the position on the page highlighted, and correction in one keystroke. This is where your team spends its time, and it is the part least visible in a demonstration. Ask to see it with a messy invoice from your own pile rather than a curated sample.
Line items, which still separate products
Header fields are effectively solved. Lines are not, and lines are what the three-way match needs. Test a genuine multi-line invoice with several deliveries against one ordered line. A blank or garbled line grid tells you the product automates keying but not matching, which is a different and smaller benefit.
Questions people ask about invoice ocr software
What accuracy figure should we accept?
None as given. Ask by field and test on your own documents, then measure the review minutes still required.
Does it learn from our corrections?
Often, particularly per supplier. Ask what a correction changes and how soon the effect appears.
Is a text-layer PDF easier?
Considerably. If suppliers can send system-generated PDFs rather than scans, that improves results more than a change of product.