AI Content Moderation Systems: Architectures, Costs, and Implementation Trade-offs
AI Content Moderation Systems: A Practical Guide to Architectures, Costs, and Trade-offs TL;DR: Building an AI content moderation system is a complex engineering challenge that balances accuracy, latency, and cost. This guide breaks down the core moderation architectures—from single-model to multi-stage cascades—provides real cost breakdowns, and offers practical Python code for implementation. Key trade-offs involve choosing between speed and thoroughness, and between building in-house models versus using third-party APIs. A well-designed automated content filtering system can scale to millions of documents while managing expenses, but requires careful planning around AI safety systems and human-in-the-loop fallbacks. ...