Where the BG24L really sets itself apart is in its AI/ML capabilities. With the built-in Matrix Vector Processor (MVP) enables on-device inferencing up to 8x faster and at 1/6th the power compared to CPU-only processing. That unlocks a whole range of applications where real-time data from sensors is used to detect patterns, learn over time, and trigger events without needing to stay connected to the cloud. This makes the BG24L an excellent fit for predictive maintenance, anomaly detection, and condition monitoring in industrial or agricultural settings. For example, sensors placed on a motor can continuously track temperature and vibration. If those values drift outside normal patterns, the device can flag it as a potential early failure, helping prevent downtime and extending the life of the equipment.

The BG24L was built specifically for sensor-driven, ML-capable devices. Flash and RAM are optimized for this class of applications, and if your ML use case demands more, Silicon Labs has other SoCs ready for that. But when it comes to edge inferencing on real-time sensor data, BG24L ultra-low power Bluetooth SoC hits the sweet spot—smart, efficient, and ready to deploy.