Our platform connects with any existing data source, cloud based data lakes and warehouses, live MQTT or OPC-UA data, or offline SQL dumps. 

With intuitive data visualizations and unsupervised machine learning, we help our users to label their piles of IoT data as efficiently as possible. Once labelled, our AutoML pipeline will optimize diagnostics, predictive, anomaly detection and quality control models with a single click. The optimized models are automatically deployed in our in-house MLOps framework for scalability and continuous improvement. 

Our platform comes off the shelf with a  full monitoring solution to identify performance issues early on, and helps you focus your attention to improve the machine learning performance.