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SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. With advanced annotation and QA tools, data curation, automation features, native integrations, and data governance, we enable enterprises to build datasets and successful ML pipelines. Partner with SuperAnnotateโs expert and professionally managed annotation workforce that can help you quickly deliver high-quality data for building top-performing models.
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Ok, so I tried comparing 4 of the better data annotation tools like dLabel.org, CVAT.com, SuperAnnotate.com and Labelbox.com . I tried them all as thoroughly as I could and I probably missed some things so apologies in advance for that! Let me know what I missed in the comment. Btw, I'm Amir and I've worked most of my data-labeling career at dLabel.org. Source: about 5 years ago
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
Labelbox - Build computer vision products for the real world
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.
Travis CI - Simple, flexible, trustworthy CI/CD tools. Join hundreds of thousands who define tests and deployments in minutes, then scale up simply with parallel or multi-environment builds using Travis CIโs precision syntaxโall with the developer in mind.
CloudFactory - Human-powered Data Processing for AI and Automation