CVAT (Computer Vision Annotation Tool) is an open source, Kubernetes native application designed to streamline the process of annotating images and videos for computer vision tasks. With CVAT, teams can efficiently label datasets, enabling the training of accurate and robust machine learning models. Deploying CVAT in your Kubernetes cluster provides a scalable and flexible solution for managing annotation workflows, enhancing collaboration among team members, and accelerating model development cycles. CVAT supports a wide range of annotation types, including bounding boxes, polygons, polylines, and keypoints, catering to diverse computer vision applications. By leveraging CVAT, organizations can unlock the full potential of their computer vision projects, from data preparation to model deployment.
Deploy CVAT on Kubernetes via Helm.
Label images and video with boxes, polygons, keypoints, and more.
Support multi-user annotation workflows and dataset review.
Prepare high-quality labeled data for computer vision training pipelines.
Additional Nebius infrastructure costs may apply. Use the Nebius Pricing Page to estimate your infrastructure costs.
Deploy CVAT on Kubernetes.
Some applications are easier with a hand on the wheel. Talk to an architect who has deployed this in production.
Reliable AI infrastructure backed by top-tier NVIDIA GPUs, purpose-built for demanding inference workloads. Multiple deployment methods — virtual machines for full hardware control, Kubernetes for scalable cluster deployments, and managed serverless applications for teams that want inference running without infrastructure overhead
Learn about Nebius AI CloudNebius meets a broad set of security and compliance standards. Fine-grained IAM controls, audit logs, and encrypted storage are available out of the box — so teams can meet security requirements without additional tooling.
Explore the Trust centerApplication support
Provided by Cvat. See the documentation and project links above.
Infrastructure support
Provided by Nebius for the underlying cloud infrastructure.
