Day 11: Content Verification Service
AI Output Validation and Quality Control
🎯 What We're Building Today
Multi-stage Verification Pipeline - Format validation → AI accuracy check → Quality scoring
Claude AI Integration - Structured prompting for factual accuracy verification
Async Queue Processing - Bull + Redis for scalable content verification
Quality Decision Engine - Approve/reject/flag logic with configurable thresholds
Production Monitoring - Comprehensive logging and error handling
Why Content Verification Matters in Production Systems
Picture this: your quiz platform generates thousands of questions daily. Without verification, you might serve students incorrect information, poorly formatted questions, or content that doesn't match the intended difficulty level. In production systems handling millions of requests, content quality directly impacts user trust and business outcomes.
The verification service acts as your quality control checkpoint - it's the difference between a reliable educational platform and one that damages learning outcomes.