DagsHub
DagsHub provides a comprehensive platform for managing the entire AI lifecycle, from data curation and annotation to experiment tracking and model deployment.
Our verdict
Who it's for
Manage your entire AI lifecycle, from data to deployment
Who should look elsewhere
The free tier has limitations on private repository collaborators and tracked experiments.
Pros
- +Comprehensive platform covering the full AI lifecycle.
- +Strong support for multimodal data, including vision, audio, and LLM.
- +Seamless integration with popular ML tools like MLflow.
- +Facilitates collaboration among data science teams.
- +Offers flexible deployment options, including on-premise for enterprises.
Cons
- −The free tier has limitations on private repository collaborators and tracked experiments.
- −Advanced features like petabyte-scale data management are exclusive to enterprise plans.
- −Requires some familiarity with ML concepts and workflows for optimal use.
Key features
- ✓Multimodal data curation and annotation
- ✓AI-powered Human-in-the-Loop annotation workflows
- ✓Granular data filtering, sorting, and visualization
- ✓Data versioning and lineage tracking
- ✓Experiment tracking with MLflow compatibility
- ✓Notebook versioning and diffing
- ✓Model version management and deployment
- ✓CI/CD/CT integration
Pricing
| Plan | Price | Billing | Notes |
|---|---|---|---|
| Individual | $0 | month | Unlimited public repositories with unlimited collaborators; Unlimited private repositories for non-commercial use; Unlimited experiment tracking for public repositories |
| Team | $119 | month | Everything in Individual, plus:; Unlimited private repositories; Multimodal annotation and auto-labeling |
| Enterprise | — | month | Everything in Team, plus:; Petabyte-scale data management; Deploy models to your cluster |