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Oxen.ai

AI data version control

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Data versioning
Dataset collaboration
Oxen.ai gives you Git-like version control built for large AI datasets. You can track changes across millions of files, branch and merge data just like code, and collaborate with your team without overwriting each other’s work. It handles images, videos, CSVs, and text files at terabyte scale.
Screenshot of the homepage of www.oxen.ai

AI tool Advantages icon Advantages

  • Handles millions of files fast
  • Open-source and free
  • Familiar Git-like workflow

AI tool disadvantages icon Disadvantages

  • Requires technical knowledge
  • Self-hosting needs setup
  • Smaller community than Git LFS

Plans and pricing icon Plans and pricing

  • Free (open-source)
  • 30 per month
  • $60 per month

Open Source

Yes

Most suitable professions

Use cases

  • Version control for ML training datasets
  • Tracking image and video dataset changes
  • Team collaboration on shared data repositories
  • Comparing data between model iterations

Target audience

  • Machine learning engineers
  • Data scientists
  • AI research teams
  • MLOps engineers

HDRobots review of the AI tool HDRobots review

Oxen.ai is a data version control system built from the ground up for AI and machine learning workflows. Unlike Git, which struggles with large binary files, Oxen uses Merkle trees, block-level deduplication, and compression to handle repositories with millions of files at terabyte scale.

The tool works a lot like Git. You init a repo, add files, commit changes, push to a remote, and create branches. But everything is optimized for data — CSVs with millions of rows, image folders, video collections, audio files. It indexes hundreds of thousands of files in seconds and keeps storage efficient through smart deduplication.

Oxen also includes built-in tools for data exploration. You can compare DataFrames between commits, run model inference directly on your data, search embeddings with nearest neighbor lookup, and edit data through the OxenHub web interface. The whole system is written in Rust with Python bindings, so it stays fast even at scale.

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