Nexbe believes that static, pre-trained, AI models are insufficient in a dynamic energy landscape.

Therefore, upon installation, the NX30E uses grid-edge computing supported by a proprietary embedded AI neural network, RaptorVision™ , to learn the localized grid conditions.

In continuous background mode, the embedded AI trains itself against ‘normal’ network operating conditions. Anomalies such as arcing events, lightning strikes and broken neutrals can then be easily identified.

Upon anomaly detection, voltage and current inputs are simultaneously captured at 14-bit resolution through adaptive sampling from 2kHz to 2MHz per measurement point (voltage and current).

What sets this solution apart is its collaborative learning. Insights from one meter are shared with others in the same feeder constellation, continuously updating network ‘normal state’ conditions in real-time.

The self-learning AI analyses, identifies and locates anomalous events and escalates reporting in accordance with utility requirements.
Nexbe’s product design approach delivers

Ultra-High-Resolution Data
Capturing and storing all electrical parameters,
escalating only insights that add business value
to the utility.

Scalable, Cost-Effective Deployment
High-end, future-proofed network analytics for
widespread use at a competitive price point.