Quality Monitoring System

AI Quality Dashboard

Monitor AI model performance and improve quality through data-driven insights.

How Quality Tracking Works

Reinforcement Learning Approach: Like training an AI model, we track what works and what doesn't

Input/Output Recording: Every AI interaction is recorded with prompts, responses, and performance metrics

Quality Scoring: Automated assessment of relevance, coherence, completeness, and accuracy

Continuous Improvement: Recommendations generated from successful patterns vs failures

About This Quality System

What Gets Tracked

  • • AI prompt inputs and generated responses
  • • Processing times and success rates
  • • Response structure and content quality
  • • User satisfaction ratings (when provided)
  • • Error patterns and failure modes

Quality Improvements

  • • Prompt template optimisation
  • • Model parameter tuning recommendations
  • • Context enhancement suggestions
  • • Performance bottleneck identification
  • • Success pattern replication

Privacy & Anonymous Data

All quality data is stored anonymously for AI training purposes. No personal information, contact details, or business-specific content is collected. Only anonymous AI interaction patterns, quality metrics, and performance data are tracked to improve model performance.