Data evolves over time, causing a change in the distributions and interpretation of data and a corresponding degradation in model performance. The Drift Detector uses an incremental learning method, in which each incoming instance retrains the model. The solution detects drifts in the model output, providing useful insights with respect to the data and model behavior. This helps businesses identify degradation in model performance and need for retraining.