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How to Design an AI Verification Case File
A case file should combine documents, extracted fields, risk signals, analyst notes, and final decisions in one place.
Why it matters
AI verification becomes practical when it produces a usable case file instead of isolated model outputs. The case file should help an analyst understand the supplier, evidence, risk signals, and decision history without searching across chats and folders.
Evidence to collect
Include original documents, extracted fields, source links, company name matrix, address matrix, beneficiary check, certificate table, risk signal list, reviewer notes, and final status. Keep timestamps for uploads, reviews, and decision changes.
How to review it
Design the file around decisions. A buyer needs to know whether to pay, pause, inspect, request more documents, or reject the supplier. Each section should support one of those actions.
Where buyers get misled
Teams get misled when AI output is stored separately from source evidence. A summary without documents, or documents without extracted fields, makes later review difficult and weakens accountability.
Practical next step
Build a standard case file schema before adding more models. The strongest AI workflow is usually the one that improves evidence organization first.
Working checklist
- Store originals and extracted fields.
- Use entity and address matrices.
- Record risk signals.
- Add analyst notes.
- Keep final decision history.