Get up and running in minutes, regardless of your current skill level with vision machine learning.
- New to Vision ML? Waiting for your DevKit? Start building a vision model, letting Azure Custom Vision Service do the heavy lifting.
- Experienced with vision ML? Use Jupyter notebooks and Visual Studio Code to create and train custom vision ML models.
Azure IoT Edge can push your containerized vision ML models to the Vision AI DevKit with ease, whether the camera is on your desk or in another country.
Prove your concept
Use the Vision AI DevKit and Azure services to quickly take your Intelligent Edge project from concept to proof.
Join the Community
Get help and help others with vision ML projects by joining our Tech Community and Gitter
Build the intelligent edge
As an Intelligent Edge device, the Vision AI DevKit can be combined with Azure IoT Edge to deploy vision ML models and custom business logic from the cloud to the edge via standard containers. Moving these workloads to the edge of the network means vision ML inferencing work requires less cloud interaction while enabling quick reaction to local events, including operating during extended offline periods.
An Azure IoT starter kit, the Vision AI DevKit can be used with models built and trained using the Azure Machine Learning service and CustomVision.ai.
The Vision AI DevKit features the Qualcomm Visual Intelligence Platform for hardware acceleration of AI models to deliver superior inferencing performance.