Spot Failures Before They Happen
Your equipment already produces the data that announces failures – in controllers, SCADA and historians. We make it usable: anomaly detection and failure prediction without additional hardware.
From Raw Data to Maintenance Decisions
Models that learn from your historical operating data what normal looks like – and report when it no longer does
Failure Prediction
Models learn from time series and maintenance history which patterns precede failures and estimate the risk per asset.
Anomaly Detection
Detects deviations from normal behaviour in currents, pressures, temperatures or cycle times – even without labelled failures.
Connected to Your OT
OPC UA, S7, Modbus, MQTT, historian, SCADA, MES and maintenance system – read-only, the control system stays untouched.
Alerts You Can Act On
Warnings with context: which signal, since when, how unusual – sent straight to maintenance.
Dashboards
Asset condition, trends and forecasts for maintenance and production management at a glance.
Fixed-Price PoC
6–8 weeks: data access, a model on your historical data, validation against real events and a decision paper for the rollout.
Where It Applies
Anomaly detection on the data your equipment already delivers
Manufacturing Equipment
CNC machines, presses and conveyors: spindle load, motor currents and cycle times from the controller reveal wear early.
Robots & Handling
Axis currents, torques and position deviations from the robot controller as condition indicators for gearboxes, drives and grippers.
Energy & Utilities
Pumps, turbines, transformers and substations: operating data from SCADA and control systems shows deviations before failure.
Building Services
Ventilation, chillers and elevators: data from the building management system detects faults before occupants notice them.