In our previous post, an extensive guide was provided on choosing a data annotation or image labeling solution to prepare datasets for training, validating, and testing AI/ML models. That guide covered 11 factors to help teams select a vendor that aligns with project requirements. Ultimately, the most suitable data labeling platform depends on each use case, project complexity, and budget.
Hojiakbar Barotov
Factors in Selecting Data Annotation Vendors | Unitlab Annotate
There are numerous image annotation vendors—each claiming distinct advantages in features, precision, and performance. To clarify these options, we reviewed most prominent data annotation solutions of 2024, highlighting their features and pricing. These aspects significantly affect the speed and accuracy of data labeling, ultimately influencing the development of robust AI/ML models.
Shohrukh Bekmirzaev
Comprehensive Review of Image Annotation Tools | Unitlab Annotate
This post focuses exclusively on pricing differences across seven popular image labeling tools, based on a standardized project. While companies may have the necessary budget for a specific data labeling service, it is advisable to ensure that the chosen provider offers sufficient value for the investment.
A standardized project setup is essential because some platforms are oriented toward large enterprises, whereas others focus on a broader range of organizational sizes.
Standardized Project
Defining a standardized project helps account for the diverse needs each image labeling solution may serve: some excel at large-scale enterprise solutions with end-to-end services, while others aim to support businesses of all sizes. Pricing models often differ based on project size, team composition, and complexity.
However, the following configuration was used as a common denominator across all seven image annotation platforms:
- 10,000 source images
- Polygon segmentation
- 3 team members
- 1-month duration
This scenario enables a direct comparison of cost-effectiveness among different data annotation services.
Unitlab
Unitlab is an automated data annotation platform that aims to accelerate labeling by up to 15 times and reduce costs by up to 5 times through advanced data auto-annotation. By emphasizing hybrid data annotation, it strives to balance quality and speed by leveraging both human input and machine assistance.
Its AI-driven image labeling features and human feedback loops help reduce labeling time while maintaining quality standards. The pricing structure is offered through monthly subscription plans.
- Project Cost: $99/month (Active Plan)
- Limits: 10K source images + 10K Auto-labeling
- Users: 5 users
- Key Benefits: Accelerated labeling via AI, integrated human collaboration
Features within Pricing:
- Private datasets plus complete dataset management
- Foundational AI and external AI model integration
- Role-based access with collaborative labeling
- 7/7 support
Roboflow
Roboflow is an end-to-end image annotation solution for building and deploying computer vision models, featuring Roboflow Annotate, an AI-assisted image labeling service. Its pricing depends on a credit-based monthly system.
- Project Cost: $65/month (Basic Plan)
- Limits: 30 credits (10K images stored, 10K images uploaded, 2.7K AI labeling)
- Additional Credits: $3 per credit beyond the plan limit
- Users: 5 users
- Key Benefits: Centralized dataset management, pre-processing tools, and integrated model training
Features within Pricing:
- Private datasets with comprehensive management tools
- Model evaluation and weight download
- Model deployment
- Dataset analytics
ScaleAI
ScaleAI is a top-tier data labeling tool geared toward enterprise-level solutions and government entities, offering fully managed and integrated services. The platform also collaborates with leading AI organizations, including OpenAI, Google, and Meta.
- Project Cost: No published rates; pay-as-you-go model within Self-Serve Data Engine
- Limits: Free 10K image uploads + 1K data labeling; additional usage is pay-as-you-go
- Users: Not explicitly stated
- Key Benefits: End-to-end service, optimized annotation speed, and quality
Features within Pricing:
- Sophisticated auto labeling tools
- 3D LiDAR and mapping support
- Data curation strengthened by integrated model assistance
SuperAnnotate
SuperAnnotate is a platform for managing both data and vendors, designed to streamline AI data creation and curation. It combines automated image labeling with human review to ensure accuracy and supports flexible pricing models.
- Project Cost: Custom Pro Plan
- Limits: Configurable
- Key Benefits: Unified platform, various integrations, managed annotation services
Features within Pricing:
- Project and team management
- Dataset administration and data curation
- Advanced analytics and insights
- Cloud integrations
DataLoop
DataLoop is a scalable data annotation solution and AI development platform offering a suite of tools for unstructured data pipelines. Similar to SuperAnnotate, it seeks to provide a one-stop solution for data management, annotation, versioning, and related services.
Pricing:
- Project Cost: Tailored
- Key Benefits: Data management, dataset version control, data annotation, and scaling
LabelBox
LabelBox delivers software and services for constructing and operating data factories, enabling the swift creation of high-quality ML datasets for AI/ML applications. The platform offers both free and enterprise plans.
- Project Cost: $16.67/month; $1,000 one-time fee under the Starter Plan
- Limits: Pay as you go with LabelBox Units (LBU)
- Key Benefits: Straightforward user interface, team collaboration, ML pipeline integration
V7Labs Darwin
V7Labs delivers a high-performance image labeling tool with robust AI features, primarily serving medical and industrial use cases. Its V7 Darwin offering includes AI-assisted labeling and data annotation services, aiming to automate workflows for AI datasets.
- Limits: 50K files, 3 users, and 1 workspace
- Key Benefits: Automatic annotation, collaboration across teams, and customized workflows
Features within Pricing:
- Responsive customer support
- Additional administrative controls
- AI-assisted data labeling
Conclusion
In business, money is an important thing or everything. Financial considerations are central to any business decision, and data labeling solutions each come with distinct advantages, features, and pricing. Although this review compares seven platforms under a shared project framework, it is challenging to draw definitive conclusions about cost-effectiveness when providers cater to different scales of operation and offer a variety of image labeling services.
Prospective users are encouraged to explore each solution and request personalized demonstrations or pricing details before making a long-term commitment, as hands-on evaluation generally provides better insights than external reviews alone.
Explore More
If you need more comparison between data annotation tools, check out these posts:
- 12 Best Image Annotation Tools of 2024 - A Comprehensive Review
- 11 Factors in Choosing Image Annotation Tools
- 7 Top Open-Source Image Annotation Tools of 2024 - Reviewed
References
- Shohrukh Bekmirzaev. (Jan 4, 2024). 12 Best Image Annotation Tools of 2024 - A Comprehensive Review. Unitlab Blogs: https://blog.unitlab.ai/12-best-image-annotation-tools-of-2024-reviewed/
