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

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.

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