Anomaly detection
Per-sensor, per-unit models that learn each asset's normal — and flag deviations static thresholds miss. False positives are suppressed with one tap, and the rule syncs to the detection pipeline in minutes.
Cortex watches every signal across your fleet, around the clock. It learns each asset's healthy signature, flags the moment something drifts, forecasts what's left, and turns the finding into scheduled work — automatically.
Every sensor on every unit streams into the platform — vibration, temperature, flow, gate position, water level — alongside lab results, inspections and operator readings.
Models trained per sensor, per unit flag deviations from each asset's own healthy signature — long before static SCADA thresholds would fire.
Remaining-useful-life forecasts on bearings, windings and runners turn anomalies into dates — the difference between a planned outage and a forced one.
Cortex writes the work order with evidence, parts and permits attached. Your team reviews, schedules — or marks it false positive with one tap, and Cortex learns.
Per-sensor, per-unit models that learn each asset's normal — and flag deviations static thresholds miss. False positives are suppressed with one tap, and the rule syncs to the detection pipeline in minutes.
Remaining-useful-life forecasts that convert drift into dates. Plan the bearing swap for the October outage instead of losing August to a forced stop.
Confirmed anomalies become work orders with the evidence attached: signature plots, RUL trends, affected components, recommended procedures, parts and permits.
Dissolved-gas analysis for transformers interpreted automatically — gas ratios, fault classification and trend alerts straight from lab results.
Ask in plain language — "what's driving the maintenance backlog on the east cascade?" — and get answers grounded in your plant's own data: work history, sensor trends, compliance records. Multi-LLM under the hood, your tenant's data only, every answer traceable to its sources.
We'll run a pilot against your real sensor data — and show you what it hears.