Ezurio delivers production-ready Edge AI platforms through AI-capable SOMs and SBCs built across leading silicon ecosystems. These platforms integrate pre-certified wireless, validated I/Os, and long-term lifecycle availability to help teams move from prototype to mass production.
Projected 2030 Market Size
Processor Market Growth by 2030
CAGR
Devices today process more sensor and camera data than cloud based systems can handle. Edge systems must make fast decisions locally, even when connectivity is limited or unavailable. That is why AI is moving directly onto the device: to deliver real time response, reduce load, and keep systems dependable.
Devices must see, decide, and act instantly to stay reliable
Cameras and smart sensors are everywhere and the data volume is overwhelming servers
Wi-Fi 6 & 6E finally give enough speed and stability for AI at the edge
Manufacturers are prioritizing sensors, IoT platforms, edge compute, vision, and AI/ML
Bundling of AI-ready hardware + certified software across devices & infrastructure
AI is shifting MedTech landscape for improved reliability and regulatory compliance
Edge AI succeeds when software ties everything together. Models, on-chip AI engines, and hardware must work as a complete system to deliver reliable, real-time results at the edge.
Modern processors integrate NPUs and vision engines, but software determines how easily those capabilities can be used. Ezurio supports proven AI frameworks, such as NXP eIQ, to help developers build, optimize, and deploy vision and AI workloads efficiently on supported processors.
Why This Matters
As customers move from AI evaluation to production, they need more than capable silicon. They need platforms that are validated, software that is supported, and a partner that understands system-level deployment. Ezurio brings these pieces together.
Choose the Right Platform for Your Edge AI Workload:
| Partner | SOM | AI Accels | TOPS | MIPI-CSI | Cameras | ISP |
|---|---|---|---|---|---|---|
|
|
1 | 2 | 2 | 1–8 | Yes |
|
|
|
1 | 2.3 | 2 | 2 | Yes |
|
|
|
1 | 0.7 | 1 | 1 | — |
|
|
2 | 4 | 4 | 1–64 | Yes |
|
|
1 | 3.7 | 2 | 1–32 | Yes |
|
|
|
1 | 2.8 | 2 | 1–32 | Yes |
This demo showcases real-time people detection running fully on device using Ezurio’s Tungsten700 SMARC SOM powered by MediaTek Genio 700. Video is captured through a MIPI CSI camera, processed locally through the MediaTek image and AI pipeline, and displayed in real time without any cloud dependency.
Hardware Platform
AI and Software
Ezurio helps teams move from AI evaluation to production by delivering integrated Edge AI platforms. We combine compute, vision, connectivity, and lifecycle support to reduce risk, accelerate development, and support long-term deployment across industries.
A ready-to-use platform for early hardware and software validation.
Camera-ready SOMs for vision evaluation and rapid prototyping.
Real-time vision systems running local inference across one or more camera streams
Suggested SOMs:
| SOM | Performance | Typical Use |
|---|---|---|
| CarbonAM67 | 4 TOPS, 4 MIPI-CSI, up to 64 cameras | Multi-camera and stream detection |
| Nitrogen95 SMARC | 2 TOPS, 2 MIPI-CSI, 1–8 cameras | Factory and healthcare imaging |
| Tungsten700 SMARC | 3.7 TOPS, 2 MIPI-CSI, 1–32 cameras | Vision and graphics workloads |
AI Workload:
Connectivity Role
Why Ezurio
Low-power edge analytics for continuous equipment health monitoring
Suggested SOMs:
| SOM | Performance | Typical Use |
|---|---|---|
| Nitrogen93 SMARC | 0.7 TOPS, 1 MIPI-CSI, single camera | Ultra-low power edge analytics and condition monitoring |
| CarbonAM62 | No NPU, 1 MIPI-CSI, 1–16 cameras | Ideal for sensor hubs and mixed I/O gateways |
AI Workload:
Connectivity Role
Why Ezurio
Smart interfaces combining graphics, control, and on-device AI
Suggested SOMs:
| SOM | Performance | Typical Use |
|---|---|---|
| Tungsten700 SMARC | 3.7 TOPS, 2 MIPI-CSI, up to 32 cameras | High-performance GUIs with integrated AI and 4K graphics |
| Tungsten510 SMARC | 2.8 TOPS, 2 MIPI-CSI, up to 32 cameras | Graphics-driven HMI for smart factories and automation |
| Nitrogen95 SMARC | 2 TOPS, 2 MIPI-CSI, 1–8 cameras | Industrial and medical GUIs with simultaneous AI processing |
AI Workload:
Connectivity Role
Why Ezurio
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Akron, Ohio – December 8, 2025 – Ezurio, a global leader in connectivity and embedded computing, today announces the Nitrogen95 Connected System-on-Module (SOM) — a high-performance vision...
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Our Tungsten700 SMARC is a powerful SOM with advanced vision capabilities, a powerful MediaTek image pipeline, and easy integration with tools like NVIDIA's TAO AI. In this video, Jeremiah Stanek...
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When building vision AI at the edge, specs like TOPS aren’t enough. Here are six platform features that determine real-world performance and scalability.
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Reliable edge AI depends on system-level integration across processing, wireless, and lifecycle support.
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Our work with Arducam has yielded an easy integration with Arducam’s excellence in embedded vision systems.
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Most Edge AI demos succeed. Most Edge AI product struggle to reach production. The difference isn’t the model, but if the entire system was designed, validated, and supported for real-world deployment.
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Edge AI promises real-time intelligence across industries, but many applications fall short due to poorly integrated systems, unstable wireless, and overlooking security.
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Smart building devices must combine real-time control, wireless, and lifecycle management in compact, low-power form factors. This application study explores how a single platform approach addresses RF complexity, thermal constraints, and long-term software support at the edge.
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Evaluating the i.MX 95 for vision should not start with broken drivers and bad images. Here is the first EVK that gives engineers a real, working camera pipeline out of the box.
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Edge computing addresses these challenges by processing data closer to where it's created, often at or near the sensor level.