Pricing options to serve your business needs


Ideal for early-stage startups and academics/researchers

Basic features

Annotation editors (image, video, audio, text, LLM, multimodal)
Team and project management
Cloud integrations
Data management and curation
Advanced insights and analytics
Python SDK
Email support
Up to 3 users
Up to 5000 items


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All of Free +

Automation tools (including SAM and BBox/Polygon tracking)
Natural language search
Similarity search
One-shot annotation
Pipeline orchestration
Pilot process
Annotation services


Best suited for well-established, recurring, and high-volume AI projects
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All of Pro +

Platform onboarding
Project and pipeline configuration
Custom scripts
Style guide fine-tuning
Workforce management
Guaranteed quality SLAs
Scaling support
Enterprise customer support
Subject-matter expert sourcing
Join hundreds of revolutionizing organizations in building disruptive AI products

Why leading organizations choose SuperAnnotate

Faster time to model
More accurate labels
More cost-efficient
SuperAnnotate’s platform is incredibly robust and easy-to-use. Their Data Operations team is very thorough, proactive, easy to engage, and acts as a valuable extension of Motorola Solutions’ data operations.
Jason Lohner
Senior Manager, AI Data at Motorola Solutions

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Annotation Software
Gen AI, LLM, and custom editor
Reinforcement learning from human feedback, instruction fine-tuning, instant feedback loop, question answering, image captioning, LLM comparison and evaluation, custom interface, and more.
One-shot annotation
With one-shot image annotation, you can annotate images in bulk, increasing the speed and accuracy of the annotation process.
Image editor (supports image, video, PDF, and DICOM upload)
Tagging, nested classification, point labels, bounding boxes, polygons, polylines, skeletons, cuboids, ellipses, rotated boxes, and segmentation (instance, semantic, and panoptic).
Image editor (supports high-resolution tiled and multilayer files)
Tagging, nested classification, point labels, bounding boxes, polygons, polylines, skeletons, cuboids, ellipses, rotated boxes, and segmentation (instance, semantic, and panoptic).
Video editor
Tagging, nested classification, interpolation and tracking of point labels, bounding boxes, polygons, polylines, and skeletons.
Text editor
Nested classification, sentiment analysis, named-entity recognition, entity relationship, text summarization, and translation.
Audio editor
Classification, nested classification, region segmentation, and transcription.
AI-assisted tools (Autotrack, OCR, SAM, etc.)
SuperAnnotate’s collection of AI-assisted tools enables faster and more accurate annotations for a wide range of AI applications.
PDF (document)
Document categorization and nested classification.
DICOM (including 3D volumetric)
3D view and grid view. Tools: summarization, angle detection, point labels, bounding boxes, and ellipses.
Time series
Time-series categorization and nested classification.
HTML categorization and nested classification.
Custom editor upon request
Get a multi-modal custom editor that can be designed to accommodate any use case.
Project and Quality Management
Team and role management
Get your annotations across different user roles with a multi-level process for a full quality assurance review. Assign a role to each user and limit their access within teams and projects.
Manage all your teams, team members, data, permissions, and billing in one environment.
Annotation quality management
Get a comprehensive overview of each of your projects using the analytics dashboards. Use queries to filter out low-quality annotations and correct them in bulk.
Project and performance management
Manage project and user performance. Assign projects or folders to annotators and QAs and track their progress using the analytics dashboard.
Advanced consensus
Customize the consensus score and set up custom triggers to avoid redundant annotations. Query the dataset based on the consensus score and compare the accuracy score of the annotators using the advanced dashboards.


Data filtering and query system
Filter and find relevant data based on the annotation metadata information and model predictions output (probability, intersection over union, etc.).
Data subseting and versioning
Create subsets from the filtered data, run queries in the existing subsets, version those subsets, and productize your ML experiment directly from the UI.
Item and instance view
Quickly check the filtered data on the grid. Use the instance view to zoom in on each object and curate data to correct labels 5x faster.
Advanced data insights
Understand the trends in the annotations and model predictions based on any variable, such as class names, annotators, and more. Compare the trends and analyze model performance based on accuracy, intersection over union, annotation time, and more.
Data and model comparison
Use your model predictions in SuperAnnotate to version and compare the accuracy of different models. Find edge cases using the query system, correct annotations in bulk, and improve your model accuracy.
Similarity search
Use similarity search to find similar items in your dataset and assign them to annotators. Visualize and find various clusters and outliers in your dataset.
Natural language search
Type a description in the search bar to find matching items and curate the right dataset for your model.
Random and smart sampling
Manage and subset your dataset by randomly sampling items based on a query. Use smart sampling to select the most diverse items in the dataset to make sure not to annotate similar items or duplicates.
Bulk actions
Assign items, change classes and attributes, add comments, approve/disapprove items, and more.


Python SDK
All functionalities available in the UI can be performed with the SuperAnnotate Python SDK. You can create projects, set up integrations, upload annotations, run predictions, filter and download datasets, and more.
Model training and auto inference
Create models using your annotated data. Fine-tune the model based on your dataset and class structure, and use the fine-tuned model to automate the annotation process.
Set up webhooks for changes done on items, folders, and projects. Use the webhook history to be informed of any changes in the platform.
MLOps toolkit
Use our orchestration platform to schedule trigger custom Python snippets and automate any complex MLOps pipeline. Use the resources of our MLOps engineers to streamline and automate your ML pipelines.


Expert annotation teams
No crowdsourcing! Work only with specialized, professionally managed, and trained annotation service workforces that can handle the most challenging annotation projects. Choose from a curated selection of over 400 annotation service companies.
SuperAnnotate annotation project manager
You don't have to manage the project yourself. We can organize all the data processes and setups and manage your annotation team.
Basic script writing
Our team can help your data engineers with all the conversion and automation setups so they can have more time to focus on ML algorithms instead of pipeline implementations.
Language support (18 languages)
Our vetted teams speak up to 18 languages and can support less popular European and Asian languages upon request.
Advanced QA
SuperAnnotate can provide you with advanced QA, including our proprietary QA methods.
Medical doctor annotators
We have over 300 medical doctors in the United States, Europe, and Asia that can handle various medical use cases such as radiology, dermatology, oncology, pathology, dentistry, and more.
Service-level agreements
We never leave our enterprise clients without SLAs. We work with you to better understand the annotation accuracy requirements and commit to meeting those requirements with guaranteed SLAs.
Pipeline engineering support
Our team builds ML pipelines daily. We can help you improve your existing ML pipelines to avoid future pitfalls when scaling your ML applications.
MLOps support
Based on thousands of successfully completed annotation projects, our team will help you set up the most efficient pipelines for your velocity, pricing, and quality requirements while avoiding common mistakes and pitfalls, significantly increasing the success rate of your ML projects.
Subject-matter expert sourcing
Hire a specialized annotation workforce to help you deliver high-quality datasets fast for building top-performing large language models.

Integrations and Security

Create an AWS integration to connect data from your AWS S3 buckets to SuperAnnotate. SuperAnnotate will have read-only access to your data.
Create a GCP integration to connect data from your GCP storage to SuperAnnotate. SuperAnnotate will have read-only access to your data.
Microsoft Azure
Create an Azure integration to connect data from your Azure storage to SuperAnnotate. SuperAnnotate will have read-only access to your data.
Custom integration
Integrate and import from any external data source of your choice. SuperAnnotate will have read-only access to your data.
Data on-prem
Integrate SuperAnnotate with your own cloud storage and never move the data from your own premises.
BigQuery and Redshift
"Connect your data warehouse to SuperAnnotate and sync the data between the platforms periodically."
Connect Snowflake to SuperAnnotate and sync the data between the platforms periodically.
Connect Databricks to SuperAnnotate and sync the data between the platforms periodically.
More integrations upon request
Enhance your MLOps pipeline with any AI tool. SuperAnnotate's MLOps experts are ready to assist you.
Two-factor authentication
All SuperAnnotate users can enable two-factor authentication to make their accounts even more secure.
Single sign-on
Manage employee access at scale with single sign-on.
Private user groups
Sort your team members into private groups to define the project data scope for members easily and manage task distribution more effectively for advanced data governance.

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Frequently asked questions

Does SuperAnnotate provide annotation services in addition to the tool?
Can I start a free trial of paid plans?
How is pricing determined for the tool?
How do you charge for the annotation services?
Do I need to move my data from my own premises to SuperAnnotate?
How does SuperAnnotate protect my data?