The path from building an AI-powered demo to deploying thousands of secure, connected devices in the field is anything but straightforward. But thanks to a tight collaboration between Edge Impulse, Arduino Pro, and Foundries.io, engineers now have an integrated Edge AI deployment platform designed to make that journey smoother than ever.
At Embedded World North America, we sat down with representatives from all three companies -Zach from Edge Impulse, Guneet from Arduino, and George from Foundries.io – to talk about what’s missing in the AI ecosystem, and how they’re working together to fill in the gaps.
This platform is not just a collection of tools. It’s a full-stack ecosystem: from data collection and model training on an Arduino Nicla Vision, to secure deployment using Foundries.io, to low-power inference and OTA model updates – all driven by Edge Impulse.
And the best part? It works across a wide performance envelope. Whether you’re working with an M33 microcontroller or a Qualcomm-powered Arduino UNO R4, this platform helps you scale development, while keeping your AI models and data secure.
If you’re dealing with real-time sensor data, power constraints, or mass-deployment headaches, this solution brings it all together – especially for industrial, robotics, and IoT use cases.
Security is baked in, from the device level (thanks to hardware secure elements) to the firmware update pipeline, with signed models and verifiable provenance on datasets. The days of cobbling together open-source firmware and hoping it holds up in production are over.
Want a taste of what this looks like in action? The trio proposed a live demo combining a PLC (Arduino Opta), sensors, and Edge Impulse to monitor a conveyor belt. That’s the sort of practical, customisable, and production-ready Edge AI system you can build with this platform.
You don’t need a PhD. You don’t need a dev team the size of a small country. You just need the right combination of tools – and a clear path from prototype to deployment.
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