ScaleOut Software has added GenAI and machine learning into its Digital Twins platform, improving real-time monitoring.
ScaleOut Software has integrated GenAI and machine learning into its Digital Twins platform, improving real-time monitoring, anomaly detection, and operational intelligence. With Version 4, ScaleOut Digital Twins now leverages OpenAI’s language models to analyze telemetry data. As well as detect anomalies and provide instant insights. Operations managers can now pinpoint emerging issues without constant oversight, streamlining complex system monitoring. Additionally, the platform introduces automated machine learning retraining. Ensuring that digital twins continuously adapt to evolving conditions for more accurate predictions.
The new release enhances user interaction with natural language queries, allowing managers to create visualizations and extract insights without complex query construction. By integrating TensorFlow alongside Microsoft ML.NET, ScaleOut expands its machine learning capabilities, making it possible to handle over 3 million digital twins and process 100,000 messages per second. These enhancements position ScaleOut as a leader in AI-driven, real-time monitoring for industries like smart cities, logistics, and security.
By merging GenAI with real-time digital twins, ScaleOut enables businesses to transition toward autonomous operations. This advancement reduces manual workload, improves safety, and provides deeper insights into large-scale systems. The open-source API and workbench further support developers in building and testing AI-driven monitoring applications.