Valohai

Model Store Overview

Vendor Name	Valohai
Stand-alone vs. Platform	Part of a broader platform
Delivery Model	Primarily managed cloud service
Clouds Supported	AWS Azure GCP
Pricing Model	Seat-based license pricing
Service Level Guarantees	For enterprise clients only (per agreement)
Support	No
SSO, ACL	SSO available (Okta, SAML, Azure AD)
Security and Compliance	User access management features

Setup	All models trained on Valohai are automatically stored and can be deployed via Valohai deployments. Valohai is installed by our success team (i.e. no infrastructure setup) and to store artifacts write them on the disk in the container (i.e. minimal code setup).
Flexibility, Speed, and Accessibility	Can store any artifacts and any key-value pairs as metadata. All of these can be accessed via API, CLI, and GUI.
Model Versioning, Lineage, and Packaging	All artifacts are automatically versioned and traceable to the executions and pipelines that generated them.
Log and Display of Metadata	Anything printed by the code is automatically logged and versioned. All logs are live. Key-value pairs can be visualized live. All parameters, docker images, git commit, input sources are automatically stored and versioned.
Comparing Experiments and Models
Organizing and Searching Experiments and Models	Both experiments and artifacts can be filtered and sorted by any custom parameter, metrics, tags. Experiments can be visualized and compared. Experiments and models are organized in projects.
Model Review, Collaboration, and Sharing	Currently no audit workflows built-in. Models can be tagged per your process.
CI/CD/CT Compatibility	Supports continuous integration with triggers and scheduling. Valohai API can be called from any third-party such as Github actions, Airflow.
Integrations	Specifically designed to be language and user-workflow agnostic. Supports and integrates with anything through API and CLI.

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