Illustrative use case, not a completed client engagement.
The starting point
Accounting data is typed from PDFs or scans. Missing purchase order numbers and mismatched amounts are only spotted later.
A possible workflow
Relevant fields are extracted and checked against existing records. Uncertain values and mismatches enter a review queue. This example does not include automatic payments.
What we would measure in a pilot
Accuracy per data field, review time and the proportion of documents with exceptions.
Include these exceptions in testing
- Poorly readable or multi-page documents
- Different currency or missing purchase order number
- Duplicate documents
Keep the decision traceable
For each test case, define what counts as correct and when the system should abstain. The reviewer sees the input, proposal and available supporting information together. Corrections are assessed before further steps are automated. A high success rate alone is not enough: the types of errors and their consequences matter too.
Prerequisites
Suitable sample data, available interfaces and an owner for subject-matter review. Actual integrations are determined after reviewing your systems.