22% energy cost reduction across 60 commercial buildings through real-time monitoring and ML anomaly detection.
An energy management company serving commercial buildings had no real-time visibility into facility energy consumption. Monthly billing data arrived too late to act on, equipment faults went undetected for weeks, and clients were frustrated by the lack of actionable insights.
We deployed an IoT-based monitoring system with smart meters feeding real-time data into a cloud platform. The system includes ML-based anomaly detection to identify equipment faults, predictive models for demand forecasting, and automated alerts for consumption spikes. A client-facing dashboard provides real-time and historical energy analytics.
Average energy costs reduced by 22% across all monitored sites
Equipment faults detected 72 hours earlier on average
60 commercial buildings onboarded in 4 months
Client retention rate increased from 78% to 96%
“We can now show our clients exactly where their energy goes and why. The anomaly detection alone has saved several buildings from costly equipment failures.”
Head of Product
Energy Management Firm
