V7 VS 
AWS Sagemaker

Try the best Amazon SageMaker alternative!

Set up your custom ML pipelines, auto-annotate data, and train models in minutes. Solve any computer vision task 10x faster with V7.

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Maleeha Nawaz
Maleeha Nawaz
Manager of Quality and Data Curation at Imidex
After conducting an extensive research of annotation tools, we chose V7 as it fits our needs best due to its customizable workflows and automated QA.
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Raman Muthuswamy
Raman Muthuswamy
Director, Translational Research at Genmab
We use V7 to make our annotation and model training workflows more efficient. It's much easier to use than other software thanks to its intuitive UI.
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Ryan Watson
Ryan Watson
Segmentation Manager at Intelligent Ultrasound
We did a comparison when we started and noticed an increase in efficiency when we changed the workflow. Thanks to V7, we no longer have to waste time.
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ML pipeline

Build robust ML pipelines, deploy reliable AI faster

Automate labeling and gain unparalleled control of your annotation workflow. Scale your ground truth creation 10x today.

Use a model to label more data
Send edge cases back to be labeled
Collect Data
Label Data
Train Your Model
Manage Data
Deploy AI

Why should you choose V7 over SageMaker?

Easy setup and unlimited possibilities. Design your ML workflow, manage your datasets, and train models. The most intuitive solution for computer vision projects.

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Automate Data Pipelines

Eliminate manual tasks with automated data pipelines. Build workflows with custom stages, advanced logic, or webhooks.

Train and test models iteratively

Train models in the cloud. Test their accuracy and compare performance of different versions of your models with advanced tools.

Advanced Dataset Management

Get started quickly with a fast and easy setup process. Import data, create classes, and assign tasks with just a few clicks.

Integrate With Any ML Pipeline

Connect V7 to your existing ML framework. Integrate your datasets and models with external tools or platforms. We can help you create any workflow you need.

World-leading Customer Support

Our support team is always just a click away. Let us know about your idea or issue and we'll be there for you.

Auto Annotate Tool

Create annotation labels and segment objects with the most accurate auto-annotation tool on the market. Complete your annotation tasks 10x faster.


Use Python to streamline your data processing and model training. Use a flexible CLI & REST API to create advanced pipelines that meet all your needs!

SOC2, FDA & HIPAA Compliance

Protect sensitive information with SOC2, FDA & HIPAA compliant data storage and processing.

Easy to Use

Start labeling right away. Thanks to V7’s intuitive UI, you’ll get your bearings the moment you open the app.

Smooth Admin

V7’s dataset management tool was developed with users in mind. Clean interface, quick preview options, detailed stats—all these make a difference.

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Quick Setup

Plug in your data, set up a workflow, and start annotating. With V7, you’ll get your labeling project up and running in a matter of minutes.

Top quality support

You will never walk alone. If you experience any technical issues, our support teams are just a click away.

the data engine

Develop your AI training data in a single ML-Ops platform

Explore the features that world-leading AI companies take advantage of when building their AI products on V7.


Migrate Your Data From AWS SageMaker to V7 in a Snap

V7 supports SageMaker native file formats. See how easy it is to switch to V7 in minutes.

Step 1
Load it in our converter
Convert your project data into JSON format.
Step 2
Export to JSON
Darwin JSON is the default annotation encoding within the platform.
Step 3
You’re ready to use V7!
Once the files have been encoded in Darwin JSON format, you're good to go. If you need help, we’re a click away.
We chose V7 because we wanted to build new types of workflows.

We had our own system, but we wanted it to accomplish additional tasks, for example, create other annotations types, re-annotations, annotations on videos—activities that would be a lot of effort in development. V7 met our needs.

Andrew Achkar
Technical Director at Miovision
Try V7
Andrew Achkar
Technical Director at Miovision

More reasons to choose V7

Learn why 15.000+ ML teams chose V7 over Amazon SageMaker for their computer vision projects

User Roles & Permissions

Empower your team with control. Assign roles, monitor user performance, and set up your own quality control flows.

Control the data annotation process with user role management features.

Designed for Computer Vision

Tackle all types of visual datasets with confidence, from photos to CT scans and spectrograms.

V7 can handle all computer vision tasks and its unique challenges.

Build Complex Flows With Intuitive Tools

Streamline your work with V7's intuitive workflow designer. Add review stages, logic rules, custom triggers and more.

Speed up tasks and verify training data with model-in-the-loop tools.

Frequently Asked Questions
Reach out to our support team or contact us for further questions
What types of data can be processed by V7?

V7 can process various types of data, including images, medical imaging files, videos, volumetric series, and documents. The exact types of data that can be processed may depend on the specific use case and requirements. However, V7 supports the majority of visual data formats.

What programming languages and frameworks are compatible with the V7 platform?

You can use V7’s Darwin-py SKD to interact with the platform via CLI or use it as a Python library. The full documentation and API reference is available in the V7 resource hub.

What are the steps involved in model training?

If you decide to train your computer vision models on our platform, all you need to do is complete at least 100 annotations of a specific class. Then, you can pick the datasets and classes to train object detection, classification, or instance segmentation models with no additional steps.

What pricing plans does V7 offer?

V7 offers three pricing plans: Team, Business, and Pro. The team plan starts at USD 5,000/year. For detailed pricing and feature overview, see the V7 pricing page.

Can you handle large volumes of data for annotation?

Yes, V7 is equipped to handle large volumes of data for annotation. It offers efficient and scalable data management capabilities, making it a great solution for organizations with large datasets.

What kind of annotations can be performed using V7?

V7 can perform various types of annotations for tasks, including object detection, semantic segmentation, and image classification. There are multiple annotation classes, such as polygon masks, bounding boxes, keypoint skeletons for human pose estimation, etc.

What is V7?

V7 is a data training platform that focuses on automation and ease of use. It offers advanced machine learning capabilities, and V7’s key feature, Auto-Annotate, utilizes AI to quickly segment objects in an image, reducing the time required to make annotations by up to 10x.

What is the pricing for data annotation and custom model training services?

V7 uses a system of credits that are consumed when you use specific tools or perform operations such as model training. When it comes to data labeling services, the cost depends on several factors, such as the size of the dataset, the complexity of the annotation tasks, and your deadline. Therefore, it's best to reach out to V7’s team to discuss your requirements and get a quote.

What are other people's opinions about V7?

Customers who have used V7 have generally reported positive experiences with its automation and advanced machine-learning capabilities. V7 receives highly positive reviews on G2, a leading software review platform. Customers praise its features, ease of use, and overall effectiveness.

Is there a limit to in-house labeling when using V7?

There is no limit to the amount of in-house labeling that can be performed using V7. It is designed to be flexible and scalable to meet the needs of various organizations and projects.

Is it possible to use V7 for in-house data labeling?

Yes, V7 can be used for in-house data labeling as it offers advanced data annotation features and can be integrated into the machine-learning team's workflow. In-house labeling is the default mode. It is a flexible and efficient platform for managing your data labeling process. But if you need help, our team can provide professional data labeling services too.

How long does it take to train a custom model?

The time required to train a custom model depends on various factors, including the size of your data, the complexity of the model architecture, and the resources available for training. If you want to train or test V7 models on the platform itself, our Models feature allows you to train a model within several minutes.

How do you handle version control for models and annotated data?

V7 provides version control capabilities that enable you to manage and track changes to your models and annotated data over time. You can also use the export/import feature to revert to previous versions of your annotations if needed.

How do you handle the annotation of sensitive or confidential data?

V7 takes the security and privacy of sensitive or confidential data very seriously—it’s SOC2, HIPAA, and ISO27001 compliant. It provides robust security features and implements industry-standard encryption techniques to ensure the protection of your files. Additionally, it offers flexible access controls that enable you to manage who can view and access your training data.

Can I test V7 before making a purchase?

Yes, V7 offers a free trial version that allows you to test its features and capabilities before making a purchase. However, to unlock all the functionalities and all the potential that the platform offers, it is worth considering one of the paid plans. You can see the full feature breakdown and pricing of V7 here.

Can I get my data annotated without doing it myself?

Yes, you can use V7’s data labeling service. Alternatively, you can use our computer vision models for specific tasks. For example, V7 offers several models for document processing to annotate invoices, receipts, and other documents. You can also simplify the annotation process by utilizing V7's AI-powered feature called Auto-Annotate. This feature automatically segments objects in a selected part of your image, reducing the time required to make annotations.

Can you integrate the trained model into our existing system?

The V7 platform allows you to bring your own custom models, hosted on your own infrastructure. You can use them alongside the models trained using V7's own neural networks. The minimal requirements for the custom models are that they must be exposed via HTTP and make predictions in the form of JSON.

Can multiple people label the same asset in V7?

Yes, multiple people can label the same asset in V7, making it a powerful collaboration platform for your data labeling projects. V7 also includes comment tools, user permissions, or consensus stages that measure the level of agreement between different annotators, allowing you to quickly identify any discrepancies in annotations. These features help to improve the quality of your data labeling process and ensure that your annotations are accurate and consistent. With V7, you can manage large-scale data labeling projects with many collaborators.

Can V7 be used with data stored on my server?

Yes, V7 can be used with data stored on a server. V7 is designed to be flexible and can be integrated with various types of data storage solutions.

Gain control of your training data
15,000+ ML engineers can’t be wrong