Model Monitoring

The ongoing process of tracking an AI model's performance, data quality and operational metrics after deployment to detect degradation, drift or anomalies.

Keeping a constant eye on your AI after deployment; tracking its accuracy, speed and behaviour. Like a car dashboard that alerts you when something needs attention.

Continuous model monitoring is a governance essential. Without it, you have no visibility into whether your AI systems are performing safely and fairly in production. Your governance framework should define monitoring requirements for every deployed model.