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    AI Detection API Webhook Guide

    Plan AI detection webhooks for asynchronous scan results, reviewer routing, retry handling, event logs, and responsible writing-integrity decisions.

    Open core guide

    Return scan results without blocking review

    Webhook workflows let teams submit documents, receive status updates, and route completed detection results into a queue without forcing reviewers to wait on a synchronous request.

    Make every callback auditable

    Each webhook event should carry a run identifier, document reference, risk band, confidence language, timestamp, and retry state so teams can explain what happened later.

    Keep human review in the loop

    Webhook delivery should trigger triage, not automatic punishment. Sensitive or low-confidence results should move to a reviewer with policy context and supporting evidence.

    FAQ

    When should an AI detection workflow use webhooks?

    Use webhooks when scans are asynchronous, when documents move through a queue, or when completed results must update an LMS, CMS, CRM, case system, or internal review tool.

    What should an AI detector webhook payload include?

    A practical payload includes event type, run ID, document ID, status, risk band, confidence, completed timestamp, reviewer routing fields, and links to evidence or audit records.

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