From upload to routed review with Box Extract and OpenAI Decisions API
Blog post from Box
A demonstration application automates insurance certificate intake in Box by using Box AI Extract to pull key fields from uploaded certificates of insurance and project requirement documents, then sending the combined evidence to the OpenAI Decisions API to choose among three fixed routes: request a missing additional-insured endorsement, assign a specialist for unclear or conflicting evidence, or prepare the submission for standard human review. A Box V2 webhook can initiate processing when a file arrives through a File Request, after which the app stores extracted data and decision confidence as Box metadata, creates a contextual review task, and adds an insurance specialist as a collaborator for selected routes. The workflow relies on typed, closed-ended API choices rather than parsing free-form model output, with low-confidence or unsupported decisions defaulting to specialist review. The sample project includes fictional documents and setup instructions for Box authentication, webhooks, metadata templates, File Requests, OpenAI credentials, and optional local tunneling, while noting that production deployments should add durable state management, safe retries, and monitoring. Potential extensions include finding existing evidence with Box Search, evaluating multi-file submissions together, incorporating extraction-confidence signals, learning from reviewer corrections, and notifying submitters when documents are missing.
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