AI Infrastructure
Content moderation at scale requires automated AI classification (text toxicity, image safety, video analysis) with human reviewers handling edge cases. This Azure-native pipeline processes uploads through Azure AI Content Safety classifiers in parallel, routes flagged content to human review queues based on severity and confidence scores, and enforces platform policies with configurable thresholds. Essential for platform trust-and-safety teams automating content review at scale with human-in-the-loop escalation and appeals.
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Content flows through Service Bus into parallel classification pipelines — text, image, and video each have dedicated App Service workers scaling independently. Azure AI Content Safety handles classification with automatic scaling. Low-confidence or high-severity results route to human review via a separate Service Bus queue. Cosmos DB stores moderation decisions with audit trails. Event Grid notifies content owners of decisions, and Functions handles appeal processing with separate reviewer routing.
RAG AI Knowledge Base
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