Edge Impulse

Edge Impulse is a development platform for machine learning on edge devices, letting developers create high-quality datasets and run optimized AI models directly on a variety of hardware. That includes MCUs, NPUs, CPUs, GPUs, gateways, sensors and cameras.

Edge Impulse can gather data from a variety of sources, including sensor hardware, public data sets and simulated or synthetic data. It also includes tools for analyzing datasets, engineering features and optimizing models.

Among Edge Impulse's features are:

• Data Collection and Analysis: Create and analyze high-quality sensor datasets, flagging data quality problems and optimizing model performance.
• Model Optimization: Optimize models for on-device performance, fine-tuning them to take advantage of specific hardware acceleration abilities.
• Target-Agnostic Deployment: Create models and algorithms that work on any edge hardware.
• Collaboration Tools: Integrate with existing ML workflows, letting data, ML and embedded teams work more collaboratively.
• Anomaly Detection: Spot unusual signals in sensor data, flagging anomalies and weeding out unexpected inputs.
• Object Detection: Use FOMO (Faster Objects More Objects) to get real-time object detection, tracking and counting on microcontrollers.
• Integration with Leading Ecosystems: Works with a broad range of hardware, sensors, cloud services, data science tools and digital twin platforms.

Edge Impulse has a variety of pricing tiers to accommodate different customers:

• Community: A free tier for students, universities and individual developers with limited features.
• Professional: $400 per month, geared for professional developers with more features.
• Enterprise: Custom pricing for large teams and companies, with full commercial use and more advanced features.
• Partner and Reseller: Custom tiers for semiconductor and hardware companies, OEM and HW vendors, and SaaS resellers.

With Edge Impulse, developers can speed up AI development and deployment on edge devices, making it a good option for product managers, AI practitioners and embedded engineers. The company's emphasis on ease of use, security and performance means it's a good option for those who want to add AI abilities to their products.

Published on August 5, 2024