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Versioning built for
machine learning

The Xet Ecosystem

Integrates with ML Libraries & Platforms

ML Flow
Hugging Face
PyTorch
Tensorflow

XGBoost
Visualize Data

VegaLite
CSV Summaries

Netron
Streamlit

DtreeViz (soon)
Workflow Orchestration

GitHub Actions

Xet Actions

Flyte (soon)
Data Access
S3

Iceberg (soon)

DuckDB
Deployment
Docker
Kubernetes

Capsules
Accelerate your development
Reliable reproducibility
Never worry about managing your project dependencies again. A single source of truth for how your ML assets were generated.
Always know what happened
Store snapshots performantly with minimal cost. Access historical data just as quickly as current snapshots.
Master model management
Efficiently track ensembles and fine-tuned models for deduplicated uploads, downloads, and storage.

Built-in discoverability
Automatic summaries and visualizations for instant context and understandability within your repository.
Visualize everything
CSV sketch summaries for tabular data. Easy Streamlit or Gradio app deployments for everything else.
Reveal revisions
Time travel on your visualizations. See how your data and models have evolved over time.




What others are saying
“As we performed our technical evaluation of XetHub, we found that it scaled well as our repo sizes got larger. It was easy to adopt and required almost no training for the engineers on the team. The usage-based pricing model makes it easy to align our costs with system utilization, unlike some other models based on team size.”
