Implementation Guide
Normalize documents before extracting data
Convert files to consistent orientation, quality, and text encoding first. Most extraction accuracy gains come from this prep layer, not from swapping models repeatedly.
Score every extracted field
Extract vendor, PO number, tax, due date, and line items with confidence. Low-confidence values should trigger targeted review instead of blocking the entire invoice.
Enforce policy checks before approval
Run duplicate checks, PO matching, tax compliance, budget limits, and vendor registry validation. The earlier these controls run, the lower your rework burden.
Design exception queues by reason
Create queues like missing PO, amount mismatch, tax mismatch, and unknown vendor. Structured queues shorten reviewer time and make performance analysis clearer.
Use correction data as operational intelligence
Track what reviewers fix repeatedly and why. Those patterns should drive extraction model updates and policy rule improvements every release window.