Predictive maintenance with Utility IQ
A machine learning platform that forecasts equipment failure before it happens.
Client: Utility Operators
The problem
Utility operators relying on calendar-based maintenance were spending money servicing healthy equipment while unplanned failures still slipped through between scheduled checks—driving up both maintenance costs and downtime risk.
The solution
We built Utility IQ, a predictive maintenance SaaS solution that uses AWS-powered machine learning (SageMaker, IoT Analytics, Kinesis, and Glue) to monitor infrastructure in real time and forecast degradation before it causes downtime.
The measured delivery result
Operators saw up to a 40% reduction in maintenance costs, advance warning of developing equipment issues, and longer infrastructure lifespan through condition-based rather than calendar-based maintenance.
What was delivered
Real-time sensor data ingestion (vibration, pressure, temperature, corrosion)
ML models for anomaly detection and remaining-useful-life forecasting
Streaming and batch data pipelines via Kinesis and Glue
Risk-based prioritization of maintenance work orders
Industry-tailored models for gas, hydro, and water assets