DagsHub
dagshub.comSummary
DagsHub is an MLOps platform designed to help data scientists and teams manage the entire lifecycle of AI models, from data collection and curation to experiment tracking and model deployment. It specializes in handling multimodal data and offers tools for data versioning, annotation, and model management, integrating with various open-source ML tools.
Features4/13
See allMust Have
3 of 5
API Access
Fine-Tuning & Custom Models
Enterprise Solutions
Conversational AI
Safety & Alignment Framework
Other
1 of 8
Multimodal AI
Image Generation
Code Generation
Research & Publications
Security & Red Teaming
Synthetic Media Provenance
Threat Intelligence Reporting
Global Affairs & Policy
PricingTiered
See allIndividual
- Unlimited public repositories with unlimited collaborators
- Unlimited private repositories for non-commercial use
- Unlimited experiment tracking for public repositories
- Data versioning and lineage
- Annotations workspace for public repositories
- Notebook versioning & diffing
- CI/CD/CT integration
- Interactive pipelines
- Community support
- Up to 100 tracked experiments in private repositories
- Up to 2 collaborators in private projects
- 20GB of DagsHub Storage
Team
- Everything in Individual, plus:
- Unlimited private repositories
- Multimodal annotation and auto-labeling
- Connect your own storage
- Label Studio compatible
- Team RBAC
- DagsHub priority support
- Up to 1TB of data or up to 2 million files
Enterprise
- Everything in Team, plus:
- Petabyte-scale data management
- Deploy models to your cluster
- Full VPC/Air-gapped on-premise installation
- SSO/LDAP/OIDC RBAC
- OpenShift compatible
- Organizational resource control
- Enterprise SLA & support
Rationale
DagsHub is an MLOps platform that helps manage the lifecycle of AI models, particularly focusing on multimodal data. While it doesn't directly offer conversational AI or generative models like OpenAI, it provides the infrastructure for developers and enterprises to build, manage, and deploy their own AI models. It offers API access for integration, supports fine-tuning and custom models through its data and experiment management features, and has a dedicated enterprise solution with advanced security and deployment options. The platform explicitly mentions managing 'multimodal AI' data and models.