Index
AI can help identify whether a request contains the expected documents. This does not mean proving authenticity, legal validity or full compliance with company rules.
How to evaluate this decision
Define the list of attachments by order type and which information needs to be legible. Separate absence, illegibility and incompatible content. The solution should explain the backlog and forward uncertain cases for review. A probable classification should not be presented as definitive confirmation when the decision depends on specialized documentary analysis.
Criteria for comparing proposals
- Requirements: maintain lists by category and version, with someone responsible for updating.
- Extraction: indicate protected, empty or partially read files.
- Handling: Generate a clear add-on request and preserve the link between submitted versions.
A scenario to discuss with the supplier
Hypothetical example: the user attaches a receipt, but the image is cropped. Marking the requirement as met just by the file name prevents checking; the system must point out the missing information.
What to validate upon delivery
Test swapped, duplicate, unreadable attachments, and incomplete sets. Compare the screening to a human review and record errors that could clear an improper request.
Prepare the conversation about the project
Bring Quantum9 anonymized order categories, document list and examples. The pilot must delimit what the AI checks and what will continue to be decided by a person.
AI for processes · Map the company's priority