From anomaly to answer.
Most predictive systems produce alerts without explanations. We start where the data originates — proprietary sensors and an edge device feeding a model trained on real, live fleets — so the warning is specific, and it's early.
Planned-maintenance data becomes the training data for prediction.
Sense
Vibration and thermal sensors stream raw telemetry from engines, gearboxes, generators, and waterjets.
Fuse
The edge device fuses sensor data with CMMS maintenance history — what failed, when, and how it was fixed.
Predict
Our model surfaces failure precursors ~3× earlier than CMMS-only or sensor-only baselines.
Act
Operators get an answer, not an alarm: “Bearing wear on gearbox #2” — with weeks to order parts and schedule.
The hardware moat.
Engine Vibration Sensor
- 3-axis · 0.5–10 kHz · ±16g
- Magnetic mount · <20s install · IP67
- Detects imbalance, misalignment, bearing wear
Thermal Imaging Sensor
- VOx 640×512 · 16-bit · 30 Hz
- Marine-grade aluminum · −20°C → 550°C
- Catches overheat, friction, electrical hotspots
IoT Edge Device
- Onboard sensor fusion & local analytics
- Ship → shore uplink
- Runs the model where the data is born
We'd like to show you the data.
Already shipping, already paid, already live in San Francisco Bay. Book 30 minutes and we'll walk you through the live fleet.