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Edge Impulse is the edge AI platform for enterprise teams building innovative products. Optimize your models and deploy to any edge device with ease. Accelerate product development while minimizing risks with a platform designed to handle real-world sensor data.
Meet our hardware and ecosystem partners here.
Collaborate across your data, ML, and embedded teams to build optimized production-ready models faster.
Build high-quality sensor datasets and leverage advanced feature engineering tools for better
on-device model performance.
Add intelligence to your products and deploy to any hardware — from low-power wearables to industrial gateways.
Extract meaningful
information from any sensor
Recognize sounds or keywords
Add intelligent sight
to your devices
Deploy to any
production target
ML projects
data samples
cloud jobs
"The sleep data we collect is... messy and hard to scrub. Edge Impulse makes it easy to bring data in, combine it, and refine it, so we can get as much value out of it as possible."
Xi Zhang
Head of Health Sensing, Oura
"The Edge Impulse tools are highly effective and have been a competitive advantage for Know Labs. It is rare to find a leading technology platform team that cares this much about making a positive impact in the world, all while maintaining a highly collaborative, positive, and customer success-focused culture."
Steve Kent
Chief Product Officer, Know Labs
"We’re aggregating sensor data to produce more useful results. With the Edge Impulse platform, we were able to find patterns in our data quickly, and develop a specialized algorithm tailored to our needs. As a startup we're always looking for quicker ways to free up time and tackle other problems that walk through the door."
Joe Boettcher
Chief Development Officer, SlateSafety
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Innovate with powerful automation, low-code capabilities and custom extensions.
Speed up ML tasks from data collection to edge-optimized deployments.
Integrate natively with existing tools or invoke programmatically using APIs to accelerate workflows.
Solve key business challenges with edge ML and recognize return on investment in months.
Improve collaboration between data science, machine learning, and firmware teams.
Increase your team’s productivity with a standardized, hardware-centric ML development framework.
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