Predictive Maintenance

This application area focuses on using data and advanced analytics to anticipate when building systems and equipment are likely to fail, so maintenance can be performed before breakdowns occur. In real estate, this includes HVAC units, elevators, boilers, pumps, and other critical infrastructure across commercial and rental properties. Instead of relying on fixed schedules or reacting after something breaks, property teams use sensor data, asset histories, and usage patterns to prioritize and time interventions. It matters because unplanned outages drive up emergency repair costs, disrupt tenants, and can lead to churn, reputational damage, and lower occupancy. Predictive maintenance reduces downtime, extends asset life, and smooths maintenance workloads, which lowers operating expenses and improves tenant comfort and satisfaction. AI models detect early warning signals in equipment behavior and recommend optimal maintenance actions, transforming maintenance from a reactive cost center into a proactive, value‑adding function for landlords and property managers.