Predictive maintenance with AI for equipment already installed
Reveal learns the normal operational fingerprint of every connected device. When behavior drifts — even subtly — it flags the anomaly days before a human would notice. AI that learns your equipment and anticipates its failures.
It works on equipment that is already installed, such as generators, UPS units and batteries, chillers and DVR recorders, without replacing it.
How it works
- 01
Normal behavior learning
Reveal builds a model of expected behavior for each piece of equipment based on historical data. It learns patterns by time of day, season, operational load, and environmental conditions.
- 02
Subtle deviation detection
Identifies gradual changes a human wouldn't notice — a compressor consuming 3% more than normal, a generator taking 2 extra seconds to start — early signs of degradation.
- 03
Prediction with action window
It doesn't just detect that something will change — it estimates when. This gives the maintenance team an action window to intervene before the failure, at the most convenient time.
- 04
Continuous improvement
Each confirmed or dismissed prediction improves the model. As Reveal learns more about your specific equipment, its predictions become more accurate.
Concrete examples
- Detect gradual DVR hard drive degradation before it fails
- Anticipate chiller compressor failure based on atypical vibration and consumption
- Predict generator maintenance needs days before a mechanical failure
- Identify progressive UPS battery deterioration before backup capacity is lost