Extraction is not clearance
OCR, translation, and layout parsing can fill a case file quickly. Those outputs remain draft evidence until a reviewer or source check confirms the field.
AIVerify Asia
How AIVerify Asia Handles AI Verification Claims
AI-assisted verification works only when extraction, matching, scoring, escalation, and final clearance stay separate enough for a reviewer to inspect the evidence trail.
Scores need reasons
A risk score should point back to the names, dates, addresses, beneficiary details, and source checks that shaped it. A number with no evidence trail does not help a buyer defend a decision.
Escalation rules matter
The handoff from model to analyst needs hard triggers: high-value orders, regulated products, entity mismatches, edited documents, and stale records should not close without human review.
Failure modes stay named
OCR mistakes, translation drift, hallucinated summaries, over-normalized entity names, and training-data blind spots need plain labels because those errors show up in live verification work.
Review boundaries
- AI is treated as review support, not a replacement for due diligence.
- Examples stay tied to review tasks instead of model-vendor hype.
- Document extraction stays separate from source verification.
- Workflow notes identify when a human reviewer, fresh source, or formal report is needed.