AI Anomaly Detection
A model learns the normal pattern of each machine across load and time of day, and scores how far today has drifted from it.
AI anomaly detection watches vibration, temperature and current on motors, pumps, fans and conveyors, estimates remaining useful life, and opens a Work Order with the parts before a failure.

Most breakdowns announce themselves weeks ahead as a small change in vibration or heat. IoTServa learns what normal looks like for each machine, flags the drift early, and turns it into planned work instead of an emergency stop.
A model learns the normal pattern of each machine across load and time of day, and scores how far today has drifted from it.
Trend overall vibration, bearing temperature and motor current, and spot imbalance, misalignment and bearing wear early.
Estimate how many days a component has left at the current rate of wear, with the confidence shown.
Open a Work Order automatically with the likely cause, the steps and the spare parts, and book it into a maintenance window.
Plan condition-based and time-based maintenance on one calendar, with greasing and inspection reminders by running hours.
Track MTBF, MTTR, availability and maintenance cost per asset, Site and Organization.


Screens from the live IoTServa software with a demo company and demo data.
Vibration and temperature sensors on bearings, and current from the motor starter or an energy meter. Existing PLC values can be used too.
It starts scoring after a few weeks of normal running and improves as it sees more load conditions.
See VYROX Hardware or Read the Protocol Guides
Tell us which protocols are on site. We will scope a pilot that reads your real devices.