Real-time control over your HVAC and lighting systems from any device, at any time, through our professional cloud-based interface. This central intelligence hub allows facility managers to define complex operational policies, manage granular user permissions, and generate automated performance reports across multiple buildings or sites. By providing a seamless link to your physical infrastructure, it ensures total visibility and operational agility, empowering you to manage your facility’s energy footprint from the palm of your hand.

The IRIS sensor is an advanced, all-in-one detection unit that integrates high precision PIR, IR, and temperature assessing. By continuously monitoring real time occupancy and environmental climate data, it feeds critical information back to the central platform. This allows the system to automatically trigger energy saving modes - adjusting. lighting and HVAC in unoccupied spaces to eliminate waste without compromising user comfort.

Engineered for industrial grade reliability, this robust power unit is designed to safely and efficiently switch heavy electrical loads. It acts as the essential hardware bridge between the Classit software and your building’s core physical infrastructure. Capable of managing demanding lighting circuits and HVAC systems, the hub translates digital commands into physical action, providing a secure and scalable solution for facility wide power automation.

Our integrated smart metering solution provides an exhaustive, 24/7 granular view of energy consumption across your entire facility. from specific high-load machinery to individual building wings. By functioning as a high-precision data bridge, the ClassitEM gateway translates complex electrical metrics into actionable insights within the Classit cloud platform. This level of transparency allows facility managers to identify hidden inefficiencies in real-time, receive instant automated alerts for irregular usage patterns or potential phase imbalances, and generate comprehensive sustainability reports. This data-driven approach is essential for predictive maintenance, verifying utility billing accuracy, and achieving up to 30% in overall energy cost savings.