Every vendor says their extraction is accurate. The questions below help you find out what that really means for your documents.
1. How is accuracy measured?
Ask whether the figure is per field or per document. A model that gets 99% of fields right can still get far fewer whole documents right if each document has fifty fields.
2. Do I need templates or training data?
Template-based tools break when a supplier changes a layout. Look for models that read new layouts on day one and improve from corrections.
3. What happens to low-confidence fields?
You want a confidence score on every field and a review queue that shows the source region, so a person can confirm a value in seconds.
4. How does data reach my systems?
Check for a clear REST API, webhooks, a sandbox for testing and connectors for the systems you already run.
5. Where does my data live?
Ask about encryption, retention controls, certifications and whether private or on-premise deployment is available if your policies require it.
Run the same sample of your own documents through every shortlisted tool. The differences show up quickly.
