Intelligence at the Edge
Artificial Intelligence is transforming the world of embedded systems, pushing intelligence directly to the edge — where data is generated and where decisions must happen instantly.
This paradigm shift enables devices to analyze, learn, and act locally, reducing latency, enhancing security, and improving system autonomy.
By integrating neural networks into dedicated hardware accelerators — such as NPUs (Neural Processing Units), DSPs, and GPUs — embedded systems can now perform complex AI inference offline, without constant dependence on cloud connectivity. This capability allows real-time decision-making in critical applications, from machine vision and autonomous robots to industrial automation and medical devices.
Running AI locally not only ensures low latency and deterministic performance but also significantly strengthens data privacy and security, as sensitive information never leaves the device. This approach is particularly valuable in sectors that require reliability and regulatory compliance, such as manufacturing, automotive, and healthcare.
Our solutions — including platforms based on NXP i.MX8 Plus, i.MX95, and Rockchip RK3568 — integrate NPU, CPU, and GPU subsystems, providing a balanced architecture for AI acceleration, multimedia processing, and edge computing.
The latest addition to our portfolio, however, sets a new benchmark in embedded AI performance: the Engicam TIA RZ/V2H. This innovative System on Module (SOM), built around the RENESAS® RZ/V2H processor, integrates the DRP-AI accelerator delivering up to 8 TOPS (dense) and 80 TOPS (sparse), combined with a GE3D GPU for advanced graphics and vision tasks. Designed for powerful vision, machine automation, and real-time processing, the TIA RZ/V2H is perfectly suited for applications such as autonomous robotics, smart cameras, and factory automation systems.
Complementing the SOM, the AI.DEV RZ/V2H provides a complete development platform for rapid prototyping and evaluation. This industrial-grade starter kit integrates the TIA RZ/V2H System-on-Module and includes three built-in CSI cameras, offering an optimized environment for advanced artificial intelligence and computer vision development.
With scalable AI performance and high integration, Engicam’s embedded platforms enable the creation of the next generation of intelligent, connected, and autonomous devices — systems that not only sense and react, but truly understand their environment.
