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We get it. You don’t have time to wrestle with complex, confusing workflows. So we’ll show you how to optimize like a pro and deploy smart AI applications with speed, ease and power.
Sign up for free
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Once you’ve trained and validated your model, you can deploy it to any device. The model should run without an internet connection, minimize latency, and run with minimal power consumption.
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Edge Impulse supports a variety of hardware targets including devices with MCUs, NPUs, GPUs, and CPUs such as:
Do you want to develop real-world Computer Vision applications for the edge? Get up to speed on the latest edge AI vision models, accelerate your project by experimenting with several ML models simultaneously, simulate the real world, and more.
Edge Impulse puts the power of ML into real products, across every industry.
Prebuilt projects created by our edge AI experts. Use them to kickstart your own solutions faster.
Build more accurate fire detection machine learning models by combining image and temperature sensor data for greater understanding of an environment.
A proof-of-concept computer vision application for retail checkout using a Raspberry Pi and FOMO.
Use a Particle Photon 2 to turn a device on or off by listening for a keyword or audio event, and opening or closing a relay accordingly.
Run an Edge Impulse computer vision model on the Hailo 8-powered Raspberry Pi AI Kit to detect and count vehicles.
Automate inventory management tasks with computer vision and an intuitive dashboard.
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