DagsHub
DagsHub is a platform for managing machine-learning projects across data collection, dataset curation and annotation, experimentation, and model management.
What DagsHub is
DagsHub is a platform for managing machine-learning projects across data collection, dataset curation and annotation, experimentation, and model management. Its workspace can bring code, data, experiments, models, pipelines, and annotations together. It supports text, images, audio, video, documents, medical imaging, and binary files. Teams can compare experiments, view metrics and parameters, monitor progress as it happens, and support reproducibility. Data Engine adds tools for curation, visualization, quality review, lineage, hard-example mining, labeling, auto-labeling, and data streaming. Integrations include GitHub, Google Colab, DVC, MLflow, Jenkins, Label Studio, external storage, Google Drive, Weights & Biases, and Hugging Face, among others. It also supports the MLflow and Label Studio APIs for hosted projects. DagsHub hosts project data but does not supply compute, so users need local, cloud, or edge infrastructure for that work. Access options include web, API, and self-hosting.
Good
- Supports varied data, including medical imaging and audio.
- Compares experiments and visualizes metrics and parameters.
- Data Engine includes labeling and data quality tools.
- Integrates with GitHub, MLflow, DVC, and others.
- Free Individual plan and 14-day trial.
Watch out
- Does not provide compute resources.
- Free plan limits private collaborators to two.
- Free plan includes 20GB of storage.
Who it suits
DagsHub suits developers and teams managing machine-learning data, experiments, and models in one project workspace. It is a fit for users who can provide their own compute infrastructure.
Verdict
DagsHub brings data, experimentation, and model-management tools into a shared project environment. Keep in mind that compute comes from your own infrastructure, and the free plan has limits on private experiments, collaborators, and storage.
Plans and prices
From DagsHub's own pricing page, checked 15 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Individual | Free | Unlimited public repositories and collaborators · unlimited private repositories for non-commercial use · 100 private tracked experiments · 2 private-project collaborators · 20GB storage · $0 per user/month |
| Individual | Free | Unlimited public repositories and collaborators · unlimited private repositories for non-commercial use · 100 private tracked experiments · 2 private-project collaborators · 20GB storage · $0 per user/month |
| Team | $99 a month | Unlimited private repositories · multimodal annotation and auto-labeling · own-storage connections · Label Studio compatibility · team RBAC · priority support · 1TB or 2 million files · $99 per user/month |
| Team | $119 a month | Unlimited private repositories · multimodal annotation and auto-labeling · own-storage connections · Label Studio compatibility · team RBAC · priority support · 1TB or 2 million files · $119 per user/month |
| Enterprise | Priced on request | Petabyte-scale data · cluster model deployment · VPC/air-gapped on-premise installation · SSO/LDAP/OIDC RBAC · OpenShift · resource controls · SLA and enterprise support · Custom quote |
The facts
Each one read from DagsHub's own pages, with the date it was checked.
What it does
- Annotation
- The platform supports multimodal annotation and auto-labeling, with Label Studio compatibility on the Team plan.checked 15 Oct 2026
- API
- DagsHub publishes an API with interactive endpoint testing, token authentication and Basic Authentication using a username and token.checked 15 Oct 2026
- API support
- DagsHub offers full support for the MLflow and Label Studio APIs for projects hosted on DagsHub.checked 30 Sep 2026
- CLI
- The client supplies a dagshub command-line interface for login, repository creation, upload, download, DVC setup and version reporting.checked 15 Oct 2026
- Client licence
- The public DagsHub client repository is marked MIT licensed.checked 15 Oct 2026
- Compute limitation
- The documentation says DagsHub does not provide compute resources, so training and deployment run on infrastructure supplied by the customer.checked 15 Oct 2026
- Data and code versioning
- The product combines Git and DVC-based versioning so code and large data files can be managed together.checked 15 Oct 2026
- Data Engine
- Data Engine provides APIs and tools for connecting sources, enriching metadata, querying, visualizing, annotating and producing dataloaders.checked 15 Oct 2026
- Deployment options
- Enterprise installations can run on-premises, in a VPC, in air-gapped environments, and in OpenShift environments.checked 30 Sep 2026
- Documentation and support
- DagsHub provides quick starts, feature guides, API reference, Python client reference, CLI reference, tutorials, FAQ material and Discord/community support.checked 15 Oct 2026
- Enterprise security
- DagsHub states that it adheres to ISO 27001 and ISO 9001 standards and supports custom OIDC and LDAP authentication for SSO.checked 30 Sep 2026
- Experiment tracking
- Experiments can be tracked with Git, DVC experiments or MLflow, including metrics, parameters and artifacts.checked 15 Oct 2026
- Funding
- CB Insights reports $4.5 million raised across five rounds, including a $2.5 million seed round dated March 1, 2022.checked 15 Oct 2026
- Generated API clients
- DagsHub links auto-generated clients for multiple languages but warns that they have not been fully tested.checked 15 Oct 2026
- GitHub synchronization
- GitHub repositories can sync through webhooks, while GitHub pull requests and issues are shown in DagsHub and vice versa.checked 15 Oct 2026
- Hosted scope
- DagsHub hosts data but does not currently provide compute resources, relying on the user's local, cloud, or edge infrastructure.checked 30 Sep 2026
- Independent API limitation
- The same evaluation reported that MLflow run information stored in DagsHub could not then be retrieved programmatically through a Python API.checked 15 Oct 2026
- Independent documentation finding
- The evaluation described the getting-started guide and Discord as useful but said users often need DVC and MLflow documentation as well.checked 15 Oct 2026
- Independent performance finding
- A university evaluation reported that logging 1,000 MLflow metrics to DagsHub took 291 seconds, or 11 seconds in batch mode.checked 15 Oct 2026
The company
- Company founders
- Crunchbase names Dean Pleban as co-founder and CEO and Guy Smoilovsky as CTO and co-founder.checked 15 Oct 2026
- Company headquarters
- LinkedIn lists San Francisco as headquarters, while Crunchbase lists Tel Aviv, Israel.checked 15 Oct 2026
- Company legal name
- Crunchbase identifies the legal entity as DagsHub Inc.checked 15 Oct 2026
- Company size
- LinkedIn lists DagsHub as privately held with 11–50 employees.checked 15 Oct 2026
Money
- Free-plan limits
- The Individual plan allows up to 100 tracked experiments in private repositories, up to 2 private collaborators, and 20GB of DagsHub Storage.checked 30 Sep 2026
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