Software Alternatives & Reviews


The fastest annotation platform and services for training AI.

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SuperAnnotate Alternatives

The best SuperAnnotate alternatives based on verified products, community votes, reviews and other factors.
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  1. 42

    Build computer vision products for the real world


  2. 32

    Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.

  3. 25

    Human-powered Data Processing for AI and Automation

  4. 23

    Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.

  5. 24

    Seamless project management and collaboration for your team.

    Visit website $12.0 / Monthly (Per user)

  6. 19

    Supervisely helps people with and without machine learning expertise to create state-of-the-art...

  7. 18

    BasicAI combines the best of human and machine intelligence to provide high-quality annotated training data that powers the most innovative machine learning.


  8. 23

    Enterprise grade data platform for AI systems in development and in production.

  9. 11

    The platform for computer vision engineers and labeling teams to iterate between data labeling, model training and failure case discovery.


  10. 18

    Heartex Label Studio powers internal data labeling operations to achieve the most competitive and differentiated ML/AI models at scale.

  11. 16

    The World's AI


  12. Powerful and efficient Computer Vision Annotation Tool (CVAT) - opencv/cvat

  13. 16

    Translation productivity platform

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SuperAnnotate Reviews

External sources with reviews and comparisons of SuperAnnotate

Top Video Annotation Tools Compared 2022
In this blog, we’ll quickly explore annotation platforms and the features they offer to help improve the video annotation process. We’ll be looking closely at six big names in the video annotation market: Innotescus, Dataloop, Scale, V7, SuperAnnotate, and Labelbox.
Read all SuperAnnotate reviews →

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Author: | Publisher: SaaSHub
Categories: Productivity, Data Labeling, Project Management