Supervisely

Provides collaborative annotation tools for images, videos, point clouds, and DICOM medical data with built-in AI models (YOLOv11, RT-DETRv2, SAM2, ClickSEG) that generate automatic annotations to accelerate manual labeling workflows. Uses smart tool request quotas (500/day community, 5,000/day pro, unlimited for image max tier) to meter AI-assisted suggestions, reducing annotation time while maintaining human quality control through review workflows.

Enables multiple team members to annotate the same dataset concurrently with role-based permissions (annotator, reviewer, admin), version control for annotation changes, and quality assurance workflows that route annotations through review and approval stages. Tracks annotation history and supports nested ontologies with key-value tags for flexible metadata assignment across team members.

Offers managed annotation services where Supervisely's team or certified partners handle annotation work on behalf of customers. Provides consulting services for dataset strategy, annotation workflow design, and ML pipeline optimization. Combines platform capabilities with human expertise to accelerate dataset creation and reduce time-to-model for customers without in-house annotation capacity.

Provides an ecosystem index of custom applications and extensions built by Supervisely and partners. Enables discovery and deployment of pre-built applications for specialized annotation tasks, model training, and workflow automation. Marketplace approach allows community and partner contributions, though specific app categories, discovery mechanisms, and installation process not documented in available materials.

Provides search capabilities across images, annotations, and metadata using both keyword search (filename, class name) and semantic search (find similar images based on visual content). Supports filtering by annotation properties (class, confidence, annotator, date), metadata tags, and custom attributes. Search results can be exported as new datasets or used to create subsets for targeted annotation or analysis. Semantic search uses embeddings (model unknown) to find visually similar images.

Enables multiple annotators to work on the same image simultaneously with real-time synchronization of changes. Detects conflicts when two annotators modify the same annotation and flags them for resolution. Supports undo/redo with conflict awareness (undo by one user doesn't affect another user's changes). Annotation state is persisted to the server after each change, ensuring no data loss. Latency and conflict resolution strategy are unknown.

Provides integrated neural network training capabilities using built-in models (YOLOv11, RT-DETRv2, MM Segmentation, SAM2, ClickSEG) with support for custom model integration via SDK. Abstracts training infrastructure and hyperparameter configuration, allowing users to train models directly on annotated datasets without managing compute resources or writing training code. Custom models can be integrated for auto-labeling workflows, enabling iterative dataset improvement.

Manages annotation projects with version control, data retention policies, and export capabilities. Community tier archives inactive projects after 30 days (available as download), while pro/enterprise tiers offer unlimited retention. Supports downloading archived projects and exporting datasets in standard formats, though export completeness and supported formats not fully documented. Provides storage quotas (5GB community, 50GB pro, expandable at €40/100GB) with file limits (10,000 community, 50,000 pro, expandable via add-ons).

Enables developers to build custom labeling UIs and automation workflows using Supervisely SDK and deploy them via AppEngine. Custom applications can integrate with annotation projects, access datasets, and leverage built-in models for auto-labeling. AppEngine provides a runtime environment for interactive applications, though compute resources, scaling behavior, and deployment process details are not documented. Supports custom model integration for specialized labeling workflows.

Provides HIPAA-compliant annotation tools for DICOM medical imagery with 3D volumetric labeling, anonymization features, and compliance certifications. Medical Max add-on (€149/month) unlocks 3D medical labeling capabilities, enabling annotation of volumetric CT/MRI scans with tools for segmentation, measurement, and keypoint marking. Platform claims privacy compliance ('data not shared or used') and supports on-prem deployment for enterprise customers requiring data residency.

Supports annotation of multi-spectral imagery (beyond RGB), ultra-wide angle images, and high-depth 64-bit images for geospatial and remote sensing applications. Image Max add-on (€99/month) unlocks multi-spectral and medical 2D capabilities, enabling annotation of satellite imagery, aerial photography, and specialized imaging formats. Handles non-standard image dimensions and color spaces required for geospatial analysis.

Provides video annotation tools with frame-by-frame labeling, object tracking across frames, and multi-view video support for autonomous vehicle and robotics applications. Video Max add-on (€99/month) removes file limits (50 files without add-on) and enables advanced tracking features. Supports low-FPS and high-resolution video, with tracking algorithms to propagate labels across frames, reducing manual annotation effort for video sequences.

Provides 3D point cloud annotation tools for LiDAR and RADAR data with support for cuboid, polygon, and keypoint labeling in 3D space. Cloud Points Max add-on (€399/month) enables point cloud annotation and removes 50-file limit. Supports LAS/LAZ format point clouds with visualization and labeling tools for autonomous vehicle, robotics, and geospatial applications. Handles large point clouds with efficient rendering and multi-frame sequences.

Provides REST API and Python SDK for programmatic access to annotation projects, datasets, and models. Enables automation of annotation workflows, dataset management, and model training through code. API and SDK allow integration with external tools and CI/CD pipelines, though specific API endpoints, rate limits, and SDK capabilities are not documented in available materials. Supports custom automation scripts for batch operations and workflow orchestration.