Computer vision annotation tools play a vital role in training AI models to recognize and interpret visual data. These tools help label images and videos with precision, enabling machine learning systems to detect objects, classify scenes, and perform various visual tasks. In this article, we’ll look at the leading annotation platforms used in 2025, their features, and how they support scalable AI development.
1. AI Superior
At AI Superior, we understand the importance of high-quality data in training effective AI models. That’s why we focus on using the most suitable computer vision annotation tools for every project. These tools are essential for preparing labeled image and video datasets that allow computer vision models to detect, classify, and interpret visual input with high accuracy. They form the backbone of any successful AI system that relies on visual understanding.
Since our founding in 2019, we’ve worked with companies across various sectors to deliver tailored AI solutions. Our team of PhD-level engineers and data scientists knows how to select and adapt computer vision annotation tools to the needs of specific use cases. Whether it’s for autonomous driving, medical imaging, or industrial inspection, we make sure that the annotation process supports scalable and robust machine learning development.
We don’t stop at tool implementation – we integrate these tools into end-to-end AI project pipelines, ensuring they align with our clients’ business goals. Our comprehensive approach ensures that computer vision annotation tools contribute directly to the performance, accuracy, and scalability of each solution we deliver. By combining deep technical knowledge with strategic consulting, we help businesses unlock the full potential of AI.
Key Highlights
- Founded in 2019 by experts Dr. Ivan Tankoyeu and Dr. Sergey Sukhanov
- Specializes in transforming AI concepts into scalable solutions
- High success rate in Proof of Concept (PoC) projects
- Effective risk management in AI project life cycles
- Team comprised of PhD-level data scientists and engineers
Services
- AI and Data Strategy Development
- Process Optimization with AI
- AI Use Case Discovery & Identification
- AI Training and Workshops
- Generative AI Development
Contact Information:
- Website: aisuperior.com
- Address: Robert-Bosch-Str.7, 64293 Darmstadt, Germany
- Contact Email: info@aisuperior.com
- Phone Number: +49 6151 3943489
- LinkedIn: www.linkedin.com/company/ai-superior
- Twitter: x.com/aisuperior
2. Prodigy
Prodigy is a data annotation tool that supports tasks across text, images, audio, and video. It allows users to create custom annotation workflows using Python scripts called “recipes.” The tool is designed for developers and researchers who require flexibility in tailoring annotation interfaces and logic to specific project needs.
The platform includes a web-based interface that can be extended with custom JavaScript components. Prodigy also supports integration with machine learning models, enabling active learning workflows where model predictions can be reviewed and corrected by annotators. This approach facilitates iterative model improvement during the annotation process.
Key Highlights
- Extensible annotation tool for AI, machine learning, and NLP
- Supports image classification and segmentation
- Runs locally, ensuring data privacy
- Offers customizable workflows and interfaces
Contact and Social Media Information
- Website: prodi.gy
- E-mail: contact@explosion.ai
- LinkedIn: www.linkedin.com/company/explosion-ai
3. Supervisely
Supervisely is a platform for computer vision projects that offers tools for annotating images, videos, 3D point clouds, and medical imagery. It provides a suite of labeling tools, including rectangles, polygons, and 3D lasso, to accommodate various annotation needs. The platform also supports AI-assisted labeling and tracking to enhance annotation efficiency.
In addition to annotation, Supervisely includes features for data management, quality assurance, and user collaboration. It offers an ecosystem with an API and SDK for automation, as well as a developer portal for creating custom applications within the platform. Supervisely also provides services such as managed labeling and consulting to support enterprise workflows.
Key Highlights
- Comprehensive platform for image, video, 3D, and medical data annotation
- AI-assisted labeling with smart tools
- Supports custom labeling UIs and workflows
- Offers data management and quality assurance features
Contact and Social Media Information
- Website: supervisely.com
- E-mail: hello@supervisely.com
- LinkedIn: www.linkedin.com/company/deep-systems
- Twitter: x.com/@supervisely_ai
4. MakeSense.ai
MakeSense.ai is a free, web-based annotation tool that operates entirely within the browser. It allows users to annotate images for tasks like object detection and image classification without the need for installation or account creation. The tool supports multiple annotation formats, including YOLO, COCO, and Pascal VOC.
The platform is designed for simplicity and ease of use, making it accessible for users who need to quickly annotate images for machine learning projects. It does not require backend infrastructure, as all operations are performed client-side, ensuring that data remains on the user’s device.
Key Highlights
- Free online tool for image annotation
- Supports bounding boxes, polygons, and points
- Allows exporting annotations in various formats
- User-friendly interface suitable for quick projects
Contact and Social Media Information
- Website: makesense.ai
5. Scale AI
Scale AI provides data annotation services that include image, video, text, and sensor data labeling. It offers a platform that combines machine learning and human annotators to produce labeled datasets for training AI models. The company serves various industries, including automotive, government, and enterprise sectors.
Scale AI’s platform includes tools for quality assurance and integrates with customer workflows to manage large-scale annotation projects. It also offers services for model evaluation and fine-tuning, supporting the development and deployment of AI applications.
Key Highlights
- Provides data annotation services for AI applications
- Specializes in autonomous vehicles, government, and enterprise solutions
- Offers high-quality labeled data for machine learning models
- Features tools for model evaluation and red teaming
Contact and Social Media Information
- Website: scale.com
- LinkedIn: www.linkedin.com/company/scaleai
- Twitter: x.com/scale_ai
- Facebook: www.facebook.com/scaleapi
6. Encord
Encord is a data annotation platform that supports images, videos, text, and medical data. It provides tools for creating annotations such as bounding boxes, polygons, and keypoints. The platform includes features for managing annotation workflows, including task assignment and quality control.
Encord supports integration with machine learning models, enabling active learning workflows where model predictions can be reviewed and corrected by annotators. It also offers analytics to monitor annotation progress and model performance, facilitating iterative improvements in AI development.
Key Highlights
- Platform for labeling and curating multimodal data
- Supports images, videos, audio, documents, and DICOM files
- Offers AI-assisted labeling and customizable workflows
- Provides tools for data management and model evaluation
Contact and Social Media Information
- Website: encord.com
- LinkedIn: www.linkedin.com/company/encord-team
7. CVAT
CVAT (Computer Vision Annotation Tool) is an open-source annotation tool developed by Intel. It supports various annotation tasks, including object detection, image classification, and segmentation. The tool provides a web-based interface for annotating images and videos.
CVAT allows for collaborative annotation, enabling multiple users to work on the same project. It supports integration with machine learning models for semi-automatic annotation and offers features for managing annotation tasks and reviewing results.
Key Highlights
- Open-source annotation tool developed by Intel
- Supports image and video annotation tasks
- Features include bounding boxes, polygons, and masks
- Offers both online and on-premise deployment options
Contact and Social Media Information
- Website: cvat.ai
- LinkedIn: www.linkedin.com/company/cvat-ai
- Facebook: www.facebook.com/cvat.corp
8. OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source library that provides tools for computer vision and machine learning. It includes functions for image and video analysis, such as object detection, face recognition, and motion tracking. OpenCV supports multiple programming languages, including C++, Python, and Java.
The library is widely used in academic and commercial applications and is supported by a large community of developers. OpenCV also offers courses and tutorials to help users learn and implement computer vision techniques.
Key Highlights
- Open-source computer vision and machine learning software library
- Provides tools for image and video analysis
- Offers courses and tutorials through OpenCV University
- Supports a wide range of platforms and programming languages
Contact and Social Media Information
- Website: opencv.org
- E-mail: admin@opencv.org
- Twitter: x.com/opencvlibrary
- Facebook: www.facebook.com/opencvlibrary
9. Viso.ai
Viso.ai offers a platform for building and deploying computer vision applications without coding. It provides tools for data collection, annotation, model training, and deployment. The platform supports various computer vision tasks, including object detection, classification, and tracking.
Viso.ai’s platform includes features for managing devices and applications, enabling users to deploy models to edge devices. It also offers tools for monitoring and updating deployed applications, facilitating the management of computer vision systems in production environments.
Key Highlights
- Provides computer vision infrastructure for businesses
- Offers tools for building and deploying AI applications
- Supports real-time video analytics and edge computing
- Features a no-code platform for rapid development
Contact and Social Media Information
- Website: viso.ai
- LinkedIn: www.linkedin.com/company/visoai
- Twitter: x.com/viso_ai
10. Labelbox
Labelbox is a data annotation platform that supports images, video, text, and audio. It provides tools for creating annotations such as bounding boxes, polygons, and segmentation masks. The platform includes features for managing annotation workflows, quality assurance, and collaboration.
Labelbox supports integration with machine learning models, enabling active learning and model-assisted labeling. It also offers analytics to monitor annotation progress and model performance, facilitating iterative improvements in AI development.
Key Highlights
- Data labeling platform for AI teams
- Supports image, video, text, and audio annotation
- Offers managed labeling services and model evaluation tools
- Provides features for quality assurance and workforce management
Contact and Social Media Information
- Website: labelbox.com
11. Roboflow
Roboflow is a platform for managing computer vision datasets and models. It provides tools for image annotation, dataset versioning, and model training. The platform supports various annotation formats and integrates with popular machine learning frameworks.
Roboflow offers features for data augmentation, enabling users to enhance their datasets with transformations such as rotation and scaling. It also provides deployment options for running models on edge devices or in the cloud.
Key Highlights
- Platform for building computer vision models
- Offers tools for dataset management and model training
- Supports various annotation formats and export options
- Provides pre-trained models and deployment solutions
Contact and Social Media Information
- Website: roboflow.com
- LinkedIn: www.linkedin.com/company/roboflow-ai
- Twitter: x.com/roboflow
12. V7 Labs
V7 Labs offers a data annotation platform that supports images, video, and documents. It provides tools for creating annotations such as bounding boxes, polygons, and keypoints. The platform includes features for managing annotation workflows, quality assurance, and collaboration.
V7 Labs supports integration with machine learning models, enabling active learning and model-assisted labeling. It also offers analytics to monitor annotation progress and model performance, facilitating iterative improvements in AI development.
Key Highlights
- AI-powered data annotation platform
- Supports image, video, and document annotation
- Offers automated labeling with deep learning models
- Provides tools for quality control and workflow management
Contact and Social Media Information
- Website: v7labs.com
- Address: Fifth Floor, 60 Margaret Street, London, W1W 8TF
- LinkedIn: www.linkedin.com/company/v7labs
- Twitter: x.com/v7labs
13. Dataloop
Dataloop is a data annotation platform that supports images, video, and text. It provides tools for creating annotations such as bounding boxes, polygons, and segmentation masks. The platform includes features for managing annotation workflows, quality assurance, and collaboration.
Dataloop supports integration with machine learning models, enabling active learning and model-assisted labeling. It also offers analytics to monitor annotation progress and model performance, facilitating iterative improvements in AI development.
Key Highlights
- Data management and annotation platform
- Supports images, videos, and 3D point clouds
- Offers tools for data curation, labeling, and automation
- Provides integration with various machine learning frameworks
Contact and Social Media Information
- Website: dataloop.ai
- Address: 2 Sapir st, Herzliya, POB 12580, 4685206, Israel
- E-mail: info@dataloop.ai
- LinkedIn: www.linkedin.com/company/dataloop
14. SuperAnnotate
SuperAnnotate is a data annotation platform that supports images, video, and text. It provides tools for creating annotations such as bounding boxes, polygons, and keypoints. The platform includes features for managing annotation workflows, quality assurance, and collaboration.
SuperAnnotate supports integration with machine learning models, enabling active learning and model-assisted labeling. It also offers analytics to monitor annotation progress and model performance, facilitating iterative improvements in AI development.
Key Highlights
- End-to-end data annotation platform supporting image, video, text, audio, and multimodal data types
- Advanced tools for object detection, segmentation, classification, and pose estimation
- Automation features including interpolation and auto-tracking for efficient labeling
- Seamless integration with major cloud platforms like AWS, GCP, and Azure
Contact and Social Media Information
- Website: superannotate.com
- LinkedIn: www.linkedin.com/company/superannotate
- Twitter: x.com/superannotate
- Facebook: www.facebook.com/superannotate
Conclusion
In the rapidly evolving field of artificial intelligence, the importance of high-quality data annotation cannot be overstated. The tools and platforms listed above offer a diverse range of solutions tailored to various needs in computer vision. Whether you’re a researcher, developer, or enterprise, selecting the right annotation tool is crucial for the success of your AI projects. By leveraging these platforms, you can ensure accurate, efficient, and scalable data labeling, paving the way for more robust and reliable AI models.
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