Compare the Top Data Labeling Software for Linux as of October 2026

What is Data Labeling Software for Linux?

Data labeling software is a tool that assists in the organization and categorization of large datasets. Data labeling tools enable data to be labeled with relevant tags depending on the purpose such as for machine learning, image annotation, or text classification. Data labeling software can also assist in categorizing input from customers so businesses can better understand their needs and preferences. The software typically comes with different features such as automated labeling, collaboration tools, and scaleable solutions to handle larger datasets. Compare and read user reviews of the best Data Labeling software for Linux currently available using the table below. This list is updated regularly.

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    Datasaur

    Datasaur

    Datasaur

    Welcome to the best tool for managing your labeling team, improving data quality, and working 70% faster—all in one place.
    Starting Price: $349/month
  • 2
    CVAT

    CVAT

    CVAT

    Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. CVAT’s blazing-fast, intuitive user interface, was designed by working closely with real-world teams solving real-world problems. From medical to retail to autonomous vehicles, world’s most ambitious AI teams use CVAT as a part of their AI workflow every day. No matter what your input data or expected results are, CVAT is ready. It works great with images, videos, and even 3D. Bounding boxes, polygons, points, skeletons, cuboids, trajectories, and more. Annotate more efficiently with automated interactive algorithms like intelligent scissors, histogram equalization, and more. Gain actionable insights with metrics such as annotator working hours, objects per hour, and more.
    Starting Price: $33 per month
  • 3
    Sama

    Sama

    Sama

    We offer the highest quality SLA (>95%), even on the most complex workflows. Our team assists with anything from implementing a robust quality rubric to raising edge cases. As an ethical AI company, we have provided economic opportunities for over 52,000 people from underserved and marginalized communities. ML Assisted annotation created up to 3-4x efficiency improvement for a single class annotation. We quickly adapt to ramp-ups, focus shifts, and edge cases. ISO certified delivery centers, biometric authentication, and user authentication with 2FA ensure a secure work environment. Seamlessly re-prioritize tasks, provide quality feedback, and monitor models in production. We support data of all types. Get more with less. We combine machine learning and humans in the loop to filter data and select images relevant to your use case. Receive sample results based on your initial guidelines. We work with you to identify edge cases and recommend annotation best practices.
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