ChargeLab Inc.

Published purpose

This project develops an AI- and ML-driven solution to improve EV charger reliability through predictive maintenance. By analyzing historical data, real-time metrics, and OCPP logs, it identifies patterns and anomalies indicating failures. Site hosts receive notifications to schedule automatic restarts during low-usage periods, minimizing disruptions and maximizing uptime. Network operators benefit from trend analyses to uncover systemic issues, reduce manual interventions, and extend equipment lifespan. LLM-powered semi-automated labeling enhances training dataset quality, improving AI accuracy and scalability. The solution ensures compatibility across diverse hardware for seamless deployment.