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Published
9 April 2026
Written by Yunus Unal Mechatronics Engineer and Content Specialist
Yunus is a mechatronics engineer with a background in 5G mobile communications and intelligent embedded systems. Before joining TKO and ipXchange, he developed and tested IoT and control-system prototypes that combined hardware design with embedded software. At ipXchange, Yunus applies his engineering knowledge and creative approach to produce technical content and product evaluations.
Premio is positioning itself as a hardware platform provider for industrial edge AI, with a focus on ruggedised, modular systems for real-world deployment.
At Embedded World 2026, the company showcased solutions across warehouse automation, robotics, transport, smart infrastructure, and human machine interface (HMI). The common theme was running AI locally on reliable industrial hardware rather than pushing workloads to the cloud.
One of the clearest takeaways is Premio’s broad compute range. At the lower end, systems based on Intel processors with integrated neural processing units (NPUs) target efficient edge inference in compact, low-power designs. Moving up, modular M.2 accelerator cards add significantly more AI performance while keeping power relatively low. Above that, Nvidia Jetson-based platforms support more demanding vision language models and multimodal AI workloads. At the top end, Premio also offers rackmount systems for larger edge AI deployments using discrete graphics processing units (GPUs).
The company also puts strong emphasis on modularity. Across panel PCs, industrial computers, and embedded systems, Premio is aiming to make upgrades, maintenance, and deployment easier for original equipment manufacturers (OEMs) and system integrators.
For engineers evaluating edge AI hardware, the main pitch is straightforward. Premio offers rugged, fanless, industrial-ready platforms that span from low-power inference to much higher compute performance, depending on the application.
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