Our end-to-end system transforms data into structured, actionable insights in real-time, through advanced preprocessing flows. An intelligence layer applies machine learning to detect both visible and hidden charger issues, categorising faults with precision. By learning from historical patterns, analytics and applying reinforcement techniques, our models continuously strengthens their diagnostics and resolution capabilities, ensuring charging networks become more reliable and efficient over time.
Supported by:
Charge Point Models
Data Logs Analysed
Monitoring Active Chargers
Our system can process your data logs, using advanced algorithms and machine learning models to intelligently enrich the datasets, providing you with improved insights, automatic fault handling, outlier detections and future fault predictions - all automated and in real-time.
