Predictive maintenance software built for real field conditions
Anomaly scoring from live and historical asset behavior
Well Manager establishes a performance baseline for each asset using live sensor data and historical trends. Deviations from that baseline are scored and surfaced as alerts with Anomaly Detection, so your team can focus on the signals that matter.
Condition monitoring sensor ingestion and contextual alerting
The system ingests data from connected condition-monitoring sensors across your asset base and generates alerts in context — not just when a threshold is crossed, but when behavior starts trending toward failure.
Vibration and operating-pattern deviation detection
Well Manager monitors acoustic and vibration data to detect early signs of equipment stress. Anomaly Detection uses statistical analysis and ML signal processing to establish typical baseline noise levels and flag deviations above or below those parameters.
Predictive maintenance dashboard for operations and reliability teams
Anomalies surface in a centralized dashboard where operations and reliability teams can review alert history, track asset health scores, and prioritize maintenance actions based on failure probability.
Alert-to-workflow handoff for faster maintenance decisions
Alerts include enough context for teams to act without additional investigation. The gap between detection and maintenance dispatch is getting shorter, and so is the window for avoidable failures.
Identify failure signals before production is impacted
Basic threshold alerts tell you when something is already wrong. Anomaly Detection tells you when something is starting to go wrong, giving your team time to act before production is affected.
- Detect signs of well pump failure from abnormal sensor behavior and trend drift
- Surface well pump failure symptoms in a prioritized maintenance queue
- Reduce unplanned downtime and avoid emergency repair cost spikes
- Improve maintenance planning confidence with earlier anomaly visibility