Industry Solutions

• Personalization: Retailers create personalized models for each user using data from their device, such as sensor readings, usage patterns, and browsing history.
• Privacy-sensitive applications: Train models on sensitive data, such as medical or private financial records, without requiring the data to be shared or stored in a centralized location.
• Mobile and IoT applications: Enables telco providers to train on device data, such as sensor readings, to perform tasks such as image recognition, natural language processing, and anomaly detection.
• Healthcare: Trains models using patient data to produce individualized treatment regimens or detect illnesses in their early stages.
• Autonomous vehicles: Federated Learning is used to train models using sensor data from several vehicles in order to enhance self-driving car performance.
• Industry 4.0: Scalytics Copilot enables companies to detect inconsistencies in rotation at earth drilling projects, help utilities understand renewable energy flows, or predict upcoming maintenance of ship engines.
• Edge computing: Models are trained on edge devices such as gateways and routers to accomplish tasks smart building operations, based on usage patterns and air quality readings.