Protecting revenues from grid losses
We help utilities identify energy that is consumed but not billed.
overview
Energy fraud and non-technical losses quietly erode utility revenues, as energy is consumed but not billed. By identifying anomalies and suspicious consumption patterns across large volumes of meter data, utilities can focus investigations where they matter most and recover lost revenue faster.
use cases
Operational use cases addressed
Identify suspicious consumption patterns by applying machine learning to meter time-series. This enables flagging unexpected drops, spikes and other irregular behaviour.
Quantify and locate energy losses, separating technical losses from non-technical ones by comparing consumption with grid-area aggregations.
Detect unauthorised connections and inconsistencies between the grid and customer records by combining meter data with topology and master data.
Improve data quality and billing accuracy through automated validation, estimation and editing (VEE), ensuring that true anomalies are not hidden by missing or incorrect meter data.
Prioritise investigations and field inspections by automatically generating and ranking operator tasks based on detected anomalies. This helps field teams to focus on the cases with the highest revenue recovery potential.
success stories
How we turn challenges into results
Related products
Built for energy intelligence
Revenue Protector helps utilities identify non-technical losses, abnormal consumption and water leaks through continuous metering data analysis. Using machine learning and anomaly scoring, it prioritises suspicious cases and supports energy balance calculations. These features help teams detect issues earlier, reduce manual checks and plan field inspections more accurately.
Energy Data Manager collects, validates and manages energy data for electricity, gas and water utilities, energy retailers, TSOs/DSOs, and large energy users. Built on a scalable, cloud-native time-series platform, it delivers accurate, high-quality metering data to support operational processes, analytics and regulatory compliance.
Demand Analyzer uses metering data to support customer clustering, demand forecasting, portfolio management and energy community calculations. Built on the Energyworx time-series platform, it helps utilities and energy retailers better understand consumption patterns and improve load forecasting and portfolio analysis.