Unleash Deep Learning Computer Vision on the Edge – in 4 Simple Steps

Step One:  Select deep learning computer vision model

Select a model from our catalogue; or provide your own

Step Two: Download our development virtual machine

Use our software toolkit – our middleware – that will have everything you need to easily build and deploy CV applications across ARM-based devices

Step Two: Download our development virtual machine

Use our software toolkit – our middleware – that will have everything you need to easily build and deploy CV applications across ARM-based devices

Step Three: Use our APIs to build core computer vision applications

Quickly build and enable CV applications like object detection,
classification, tracking, counting and facial recognition

Step Four: Deploy to your IoT device – quickly and easily

Enjoy inference on the edge, untethered from the cloud!

Step Four: Deploy to your IoT device – quickly and easily

Enjoy inference on the edge, untethered from the cloud!

Our Product Stack – Complete and Integrated

The alwaysAI Deep Learning CV Platform will provide application developers with the following

  • Core computer vision services such as object detection and classification, saliency, and object tracking exposed as consistent Python and RESTful APIs 
  • A registry that standardizes Caffe and TensorFlow models across 12 key parameters 
  • Middleware that integrates over 50 language libraries and deep learning frameworks compiled from source code and optimized for the ARM Cortex 
  • Linux kernel and device drivers optimized for popular system on a chip (SoC) platforms working in resource-contained and unconnected environments
  • End-to-end versioning and dependency management

Stay up to date with the company and our progress.

Join the alwaysAI community.