CVOps

Computer Vision works best when it is focused on a specific task and optimized for a specific
context. Cameras that look out your front door (at your porch and driveway) are doing a different
job to the camera looking down on your backyard from the roofline. Both watch for people to keep
you safe, but in the world of AI these are very different tasks.

CVOps is the enterprise software process for delivering the right Computer Vision to the right
camera at the right time. A reliable, accurate CV system needs to collect data over time (to deal
with factors like “Data Drift” and “Model Drift”), and to deliver software updates that adapt to the
changing realities of our physical world.

CVOps is best enabled by specialty software that securely and reliably manages the “learning loop”
of data collection, AI updates, deployment, and monitoring.

Early solutions in AI based Computer Vision required massive compute infrastructure and had to be executed in the cloud. These systems required exponentially more data and computing power to accurately address the diversity of the real world.

Technology trends of Edge Deployment and Ensemble AI emerged to address the problems of AI bloat – but created a new challenge in the logistics of matching data and AI to the cameras and use cases.

CVOps is an enterprise function incorporating the best practices of data collection, AI updates, release management, and performance monitoring to ensure high quality service and excellent customer experience.