XMotiv™ M3 is a secure MCU designed to meet the requirements for functional safety, cybersecurity, and real-time control in automotive and robotics. Built on the Arm Cortex-M33 core, XMotiv™ M3 provides a robust and scalable control platform for safety-critical embedded systems, well-suited for body control modules and robotic control nodes.

• 160 MHz Arm Cortex-M33 Core: Efficient, deterministic compute for real-time automotive control, enabling smooth actuation, fast response, and reliable subsystem behavior.
• Extensive Peripheral Interface: Flexible, scalable connectivity for vehicle networks, making integration with distributed ECUs and smart actuators faster and more predictable.
• Advanced Safety & Security: Protects critical vehicle functions with built-in safety mechanisms and hardware-level security that reduce risk and support ISO 26262 compliance.

SiliconPilot™ streamlines the creation of next‑generation vehicles and robots by enabling developers to model, test, and validate hardware-software systems entirely in a virtual environment. Automakers and robotics teams can explore future designs, uncover issues early, and refine performance before committing to silicon—reducing risk, accelerating schedules, and clearing a faster path to breakthrough innovation.

• Shorten the Development Cycle: Model, test, and validate hardware–software systems through a high‑fidelity digital twin. Reduce iteration time, catch issues earlier, and accelerate your path to production‑ready silicon.
• Accelerate Architecture Exploration: Rapidly explore design options in a virtual environment. Evaluate trade‑offs, optimize performance, and de‑risk decisions long before committing to physical silicon.
• Leapfrog into New Markets: Build on a scalable, modular platform that spans automotive, robotics, drones, and emerging autonomy systems—empowering teams to expand product lines and enter new categories faster.

As physical AI workloads grow, the challenge shifts from peak compute to balancing performance within power, thermal, and cost constraints. Developers need high-performance compute solutions that optimize these trade-offs, delivering right-sized performance for real-world edge AI deployments across automotive, robotics, drones, and beyond.

• Inference-Optimized Architecture: Purpose-built to accelerate AI inference workloads, delivering fast, efficient execution of trained models while balancing performance, power, and thermal efficiency.
• Ultra-Low Latency Performance: Enables real-time AI processing with minimal delay, ideal for time-sensitive applications such as object avoidance in autonomous driving and advanced robotic platforms.
• High Performance per Watt: Optimizes compute efficiency to maximize AI performance while minimizing power consumption in physical AI deployments such as autonomous vehicles and robots.