Spot abnormal
consumption patterns.
Identify abnormal consumption patterns automatically — across the full meter base, without manual scanning.
Energy theft and revenue loss often go undetected until it’s too late. Traditional methods rely on manual investigation and lagging indicators.
Bidgely uses AI-driven analytics to identify anomalies, flag high-risk accounts, and prioritize investigations — reducing non-technical losses and improving recovery rates.
Jobs to Be Done
Stop chasing lagging indicators. Detect anomalies, prioritize the cases worth working, and protect revenue at scale.
Identify abnormal consumption patterns automatically — across the full meter base, without manual scanning.
Rank accounts by AI-driven risk scoring so investigators focus on the cases most likely to be theft.
Cut revenue leakage by detecting losses earlier and improving recovery rates across your service territory.
Improve hit rate per investigation and reduce cost per case by sending crews to higher-confidence leads.
Use Cases
Each use case runs on the same AI-driven anomaly detection layer — so your investigators, revenue protection teams, and field crews operate from the same source of truth.
Detect what manual methods miss.
Stop the leak. Recover what's lost.
Send crews to the cases that matter.
Agentic Automation in Theft Detection
Bidgely’s agentic layer scans consumption data, flags anomalies, and triggers investigation workflows automatically — so revenue protection runs around the clock without analyst overhead.
Continuous anomaly detection across the full meter base — not lagging indicators
Continuously scans consumption data across the meter base to identify abnormal patterns — including the subtle ones manual methods miss.
Flags and ranks high-probability theft cases by risk score so investigators always work the highest-confidence leads first.
Automatically triggers investigation, field dispatch, and recovery workflows when a case crosses the action threshold — no manual handoff required.
Resources