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.

Many clients face the challenge of maintaining outdated platforms that, while generating revenue, hinder growth and scalability.