Many devices still rely on cloud processing, which causes latency, increases energy consumption, and raises privacy concerns. As the number of connected sensors grows, centralised computation becomes expensive and difficult to scale. Health and IoT applications often need instant, reliable responses, but bandwidth limits and offline environments make this challenging. The need for intelligence that operates directly on the device is becoming essential for real-time and privacy-sensitive tasks. 

Imec at Holst Centre develops Edge AI solutions that run directly on the device. We design compact algorithms and efficient machine-learning models that operate on low-power hardware, wearables and embedded systems. Our work focuses on model compression, lightweight architectures and on-device signal processing that deliver accurate results without depending on cloud connections. 

These capabilities enable partners to build devices that act immediately, protect sensitive data and operate for long periods on limited energy. Edge AI supports safer medical monitoring, more autonomous IoT systems and faster decision-making in environments where reliability and efficiency matter.