What happens when onboarding documents tell different stories?
Blog post from Box
A small Node.js application demonstrates an employee onboarding verification workflow using Box AI to extract structured fields from identity documents, utility bills, and tax forms, store the results as Box metadata, and compare overlapping information such as names, addresses, and ID expiration dates. Rather than allowing AI to determine verification outcomes, the application uses explicit, explainable rules to normalize and compare extracted data, while Box AI Ask produces a contextual summary for a generated PDF report. When inconsistencies or issues such as an expired ID are identified, the workflow marks the case as needing review and creates a Box task for a designated human reviewer, who can inspect the report and original documents directly in Box. The approach is intended as a reusable pattern for other multi-document processes, including insurance, vendor verification, lending, compliance, and claims, combining AI-based document organization with application logic and human oversight.
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