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DATA ANNOTATION FREEMIUM CLOUD #1 in Data Annotation State of the Art

ActiveLoop Review — Efficient Dataset Management

Manage and annotate large-scale datasets for machine learning teams.

Updated May 24, 2026 automation data-engineering mlops
7.1 / 10
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Reviewed by Volvenix Editorial
ActiveLoop — preview
8.0
Volvenix Verdict
AI-powered editorial review
ActiveLoop
A robust tool for dataset management, ideal for machine learning teams.
PROS
  • Efficient management of large datasets
  • Seamless integration with ML frameworks
  • Unique Deep Lake format for unstructured data
CONS
  • Freemium model may limit extensive use
  • Less suited for advanced analytics needs

Is ActiveLoop Right for You?

A quick checklist to help you decide.

You need to manage large-scale datasets efficiently.
You need a fully free solution for extensive use.
You want seamless integration with ML frameworks.
You require advanced analytics features not focused on datasets.
Your team requires effective data annotation tools.
You prefer tools with extensive collaboration features.

Ideal for: This tool fits if you are a data scientist or ML engineer managing large datasets.

Less suited for: Skip this tool if you need extensive free usage or are not focused on dataset management.

Bottom line: The ability to efficiently manage and annotate large-scale datasets.

Editorial Review AI-generated
ActiveLoop excels in managing and annotating large datasets, making it a valuable asset for data scientists and ML engineers. Its unique Deep Lake format allows seamless storage and querying of unstructured data, enhancing workflow efficiency. However, users may find the freemium model limiting for extensive use, making it best suited for teams focused on dataset management.

AI-assessed from 3 sources.

Pros & Cons

Pros

Efficient dataset management
Seamless integration with ML frameworks
Unique storage format for unstructured data
User-friendly interface
Strong community support

Cons

Freemium model may limit extensive use moderate
Workaround: Consider upgrading to Pro for more features.
Less suited for advanced analytics needs moderate
Workaround: Use alongside other analytics tools.
Who Is It For & What Can It Do
AI Capabilities
Data Annotation
Key Features
Dataset management
Efficiently manage large-scale datasets.
Data Annotation
Tools for annotating datasets.
Deep Lake Format
Unique format for unstructured data.
ML Framework Integration
Integrates with popular ML frameworks.
Collaboration Tools
Features for team collaboration.
Best Use Cases
Managing large datasets for ML projects Annotating images and videos Versioning datasets Integrating with ML workflows
AI Models Used
Custom AI models by Unknown
Available Platforms
API / SDK Web App
Integrations
PyTorch TensorFlow
Inputs & Outputs
Otherinput Otheroutput
Supported Languages
English
Security & Compliance
Compliance Standards
GDPR
Privacy · EU
Pricing Plans

Free

Best for individuals

Free
 
  • Dataset management
  • Basic annotation tools

Pro

 

$20/mo
$20.00/mo billed annually
  • Advanced annotation tools
  • Enhanced storage options
Most popular

Team

For small teams

$30/mo
$30.00/mo billed annually
  • Collaboration features
  • Team management tools

ActiveLoop offers a free plan with limited features and paid plans for more extensive use.

Support Channels
Documentation
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Frequently Asked Questions
What is this tool?
ActiveLoop is a platform for managing and annotating large datasets.
How much does it cost?
ActiveLoop offers a free plan and paid plans starting at $20/month.
Does it have a free plan?
Yes, ActiveLoop has a free plan available.
What integrations does it support?
ActiveLoop integrates with popular ML frameworks.
Who is it best for?
It is best for data scientists and ML engineers.
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Last verified: May 24, 2026 Info sourced from public data & vendor website. Verify at activeloop.ai AI-generated · reviewed by editors Vendor? Manage listing

Scores are calculated algorithmically from feature coverage, pricing, user feedback & benchmark data — not influenced by commercial relationships. How we score →  ·  Vendor Data Policy

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