Machine Learning
Specialized in implementing Machine Learning across a wide range of hardware—from lightweight MCUs to high-performance GPUs. Our expertise covers the development of ML models for diverse applications including, but not limited to, logistics tracking, software-defined wireless sensor networks (SDWSNs), motion and speed estimation, pattern recognition, anomaly detection,and voice processing.At the forefront of intelligent innovation, our team builds robust, scalable AI solutions that transform user inputs into meaningful results across diverse industries. By leveraging the latest in AI research, cloud-native architectures, and automation, we develop highly adaptive applications that are both intuitive and powerful.
We have hands-on expertise integrating AI capabilities into real-time, production-grade systems—ranging from creative content generation and audio processing to real-time assistance in high-stakes scenarios.
Specialized in integrating lightweight machine learning models into resource-constrained embedded systems to enable real-time intelligence at the edge. Expertise in ARM Cortex-M-based platforms, such as Nordic’s nRF52/53 series, and in deploying optimized ML solutions using frameworks like Neuton AI and Edge Impulse for on-device classification, anomaly detection, and pattern recognition without cloud dependency.
Specialized in deploying Machine Learning within RF-based mesh networks,
particularly through ML-SDWSN (Machine Learning–Software Defined Wireless Sensor Networks) architectures. Our expertise enables dynamic optimization of node
behavior at the edge—supporting adaptive sensing, intelligent routing, and traffic balancing based on real-time environmental insights. By embedding ML models into edge nodes, we achieve reduced data redundancy, extended battery life, and
prioritized data flow without relying on constant cloud connectivity
Specialized in integrating machine learning for motion classification and behavior inference directly on embedded devices used in logistics tracking and sports monitoring systems. Our ML solutions enable transport type detection—such as shaking, falling, orientation, or stationary states—empowering smart tracking systems to adapt beaconing rates based on activity context, thereby conserving energy and enhancing accuracy
We specialize in developing and deploying machine learning solutions using
TensorFlow and TensorFlow Lite. Our expertise spans building robust AI models with TensorFlow and optimizing them with TensorFlow Lite for efficient execution on edge devices. From real-time inference on microcontrollers to intelligent mobile and embedded applications, we ensure high-performance ML integration even in resource-constrained environments
AI Technologies Expertise
AI Frameworks Expertise
