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Published
19 May 2025
Written by Harry Forster
AI accelerator system-on-module solutions are popping up across the embedded space. But few are as plug-and-play as DeepX’s new offering. At Embedded World 2025, we spoke with Tim from DeepX to learn how their M.2 AI accelerator and carrier board combo can add serious AI capability—instantly.
Add AI to Your Existing Designs
Most system-on-modules (SoMs) on the market rely on MCUs from NXP, Renesas, MediaTek, or TI. While they handle embedded tasks well, they often lack the power for AI workloads. That’s where DeepX steps in.
Their AI accelerator comes in an M.2 form factor. You simply plug it into a standard carrier board to bring AI compute to your project. As a result, you can upgrade your hardware without rebuilding your design from scratch.
Fast AI Prototyping, No Fuss
DeepX’s carrier board isn’t just a breakout—it’s a whole system. The module includes the necessary interfaces, processing power, and SDK support. Once connected, you can deploy AI models right away.
For example, DeepX showed a face recognition demo for access control. The entire solution ran directly on their system-on-module. No extra setup. No additional development time.
Why System-on-Modules Still Matter
Designing embedded systems from the ground up takes time and resources. That’s why system-on-modules are still popular with engineers looking to speed up prototyping. DeepX’s AI accelerator system-on-module goes one step further. It gives you a working solution that’s ready for AI workloads.
You don’t need to find a compatible GPU. You don’t need to design a new board. Instead, you get a drop-in module that handles AI tasks efficiently. Their SDK also makes it easy to port your existing models. This means you can move from idea to prototype faster than ever.
The Takeaway
If you’re building edge AI applications—especially in fields like security or automation—DeepX offers a fast track. Their system-on-module brings everything together: the hardware, the software, and the support. You just plug it in and go.
For engineers tired of long integration times and complex AI deployments, this could be the shortcut you’ve been waiting for.
AI accelerator system-on-module solutions are popping up across the embedded space. But few are as plug-and-play as DeepX’s new offering. At Embedded World 2025, we spoke with Tim from DeepX to learn how their M.2 AI accelerator and carrier board combo can add serious AI capability—instantly.
Add AI to Your Existing Designs
Most system-on-modules (SoMs) on the market rely on MCUs from NXP, Renesas, MediaTek, or TI. While they handle embedded tasks well, they often lack the power for AI workloads. That’s where DeepX steps in.
Their AI accelerator comes in an M.2 form factor. You simply plug it into a standard carrier board to bring AI compute to your project. As a result, you can upgrade your hardware without rebuilding your design from scratch.
Fast AI Prototyping, No Fuss
DeepX’s carrier board isn’t just a breakout—it’s a whole system. The module includes the necessary interfaces, processing power, and SDK support. Once connected, you can deploy AI models right away.
For example, DeepX showed a face recognition demo for access control. The entire solution ran directly on their system-on-module. No extra setup. No additional development time.
Why System-on-Modules Still Matter
Designing embedded systems from the ground up takes time and resources. That’s why system-on-modules are still popular with engineers looking to speed up prototyping. DeepX’s AI accelerator system-on-module goes one step further. It gives you a working solution that’s ready for AI workloads.
You don’t need to find a compatible GPU. You don’t need to design a new board. Instead, you get a drop-in module that handles AI tasks efficiently. Their SDK also makes it easy to port your existing models. This means you can move from idea to prototype faster than ever.
The Takeaway
If you’re building edge AI applications—especially in fields like security or automation—DeepX offers a fast track. Their system-on-module brings everything together: the hardware, the software, and the support. You just plug it in and go.
For engineers tired of long integration times and complex AI deployments, this could be the shortcut you’ve been waiting for.
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