Many digitalisation projects start by asking how good the text recognition is. That is understandable but too narrow. Modern models read invoices, delivery notes and contracts very reliably. The actual work starts afterwards.
From fields to decisions
A recognised field is not yet a result. An invoice number only becomes valuable once you have checked whether it appeared before, whether the amount matches the order and whether the approving person is responsible. Those rules decide whether a workflow really takes work off people’s hands.
Make uncertainty visible
A good system does not claim to always be right. It states how confident it is and routes doubtful cases to humans. Ninety percent automatic processing with clearly flagged exceptions is worth more than claimed full automation that nobody trusts.
Plan for traceability
Every automated decision needs a trail: which model version, which rule, which input value? Without that trail, troubleshooting is impossible when it matters, and so is a review by a third party.
Takeaway
Value does not come from better recognition, it comes from clean rules, honest uncertainty and complete traceability. Start there and simple technology will take you further than the largest model.
