Want to see what AI on device can do? Download the Xnor SDK and find out.
The SDK has everything you need to start building ML models for edge devices.
Here’s what you get in our development kit
Technical documentation to answer your questions and get you working quickly
Pre-tuned models based on speed and memory footprint across a number of hardware targets
A benchmarking tool that helps you gauge the performance of your models
A set of samples (counters, visualizers, etc.) available in Python, C, and Swift
Customize an ML model for the task and hardware of your choice
We’ve built more than 100 custom ML models, specifically for on device AI, across popular use cases and hardware targets that are tuned for different speed and memory specifications. With AI2GO, you can build smart edge devices that have the ability to detect left behind objects in cars, classify in-stock food in a refrigerator, or can detect when a person is at the front door.
Build your custom ML model
To begin, start by selecting your hardware target
Please note: We currently support only the most popular hardware platforms. However, we’re always adding more more. Let us know if you’d like to see one.
Interested in Xnor’s Enterprise offerings?
Xnor’s highest performing models are available to our enterprise customers. As part of our enterprise offerings, Xnor conducts data collection and annotation services, custom training and delivers our highest performing XBs optimized for your hardware and use case specific environment.
