Churn prediction model for business customers that identified potential churners with higher precision than the client’s existing model, achieving a 15-20% improvement in accuracy.

Achieving a 15% decrease in carbon footprint and energy consumption costs by creating an optimization algorithm for charging electric vehicles.

Reducing energy costs by predicting and controlling efficiency, saving up to 35% and enabling anomaly detection and automated management for commercial properties.