Artifact Management for AI, Machine Learning, Data Science

Secure artifact management for AI, machine learning and data science teams

Secure your AI projects, while improving reproducibility and efficiency. Build a single, observable source of truth for models and datasets, packages and containers. Cloudsmith is fully-managed software supply chain built for innovative teams working in AI, machine learning and data science. We are the fully-managed alternative to JFrog Artifactory and Sonatype Nexus.

The problemFragmentation: You have a difficult path to productionize your work. Your models, datasets, and software artifacts are scattered.
Cloudsmith solutionSingle source of truth: Gain a single, highly-observable home for all of your models, datasets, packages and containers. Speed up your time to production with one, integrated platform.
The problemNo governance over access or data residency: You are out of compliance because you can't effectively limit access to your work or ensure it remains under control.
Cloudsmith solutionFull control: Store your work in a specific region, and grant access to your work to specific teams or users.
The problemMassive artifacts and wasted resources: Managing multiple versions of large models is resulting in high storage costs and productivity bottlenecks.
Cloudsmith solutionIntelligent retention policies: Use programmable retention rules to preserve production models while pruning redundant versions automatically. Cloudsmith's global infrastructure delivers your critical artifacts at high speed.
The problemUsing restrictive licenses: Training datasets contain restrictive licenses that prevent commercial usage.
Cloudsmith solutionPolicy-as-code: Create policies to block artifacts with unapproved licenses, preventing them from hitting your training clusters.
Hackathon

Hack the AI Stack • Cloudsmith x Chainguard

Tuesday 24th February, 2026 • 11am EST / 4pm GMT

A single source of truth for models, datasets, software artifacts

With Cloudsmith you gain a single home for all of the models, datasets, packages and containers demanded by your teams and projects. Control, secure, distribute and observe your AI assets in a single platform.
  • Store and manage packages and AI models side-by-side using multi-format repositories.
  • Proxy and cache models from upstream sources, like Hugging Face, so artifact pulls originate in Cloudsmith, providing visibility and control.
  • Maintain strict compliance and visibility with real-time audit trails for every action.

Enterprise governance for AI workflows

Machine learning models are critical to modern engineering workflows, but enterprises often struggle to control and secure them within their software supply chain. Cloudsmith extends artifact management to AI/ML, giving your teams a central registry for models and datasets. Developers simply point their projects to Cloudsmith as they would to a canonical ML registry, while enterprises gain governance, security, and global delivery at scale. With proxying and caching for Hugging Face and other public sources, organizations can adopt external models confidently and build on them securely.
    The single source of truth for your machine learning models and datasets
    Secure your publicly-sourced and private ML models and datasets alongside 30+ other binary formats. Cloudsmith lets you manage every artifact in one trusted registry, for consistent governance, security, and delivery.
    Use Cloudsmith just like HuggingFace.co
    Push and pull models with the same commands you use on Hugging Face. Configure projects to source models directly from Cloudsmith, or integrate via CLI and API for seamless workflows.
    Control access to proprietary models
    Your ML models may represent years of R&D and be based on sensitive data. Cloudsmith gives you fine-grained control over who can access and distribute them, protecting IP while ensuring compliance.
    A flexible, developer-friendly approach to software repositories
    Structure repositories to match your process - store models alongside containers and packages, or separate them into dev, staging, and production. Cloudsmith adapts to the way your teams work.
    Safely share models with customers and partners
    Grant access to your models and datasets using tightly-scoped, read-only entitlement tokens. These are perfect for enterprises who rely on shipping models to customers.
security and governance

Built-in security for AI/ML artifacts

With Cloudsmith you gain a single, highly-observable home for your models and data sets. Use our log data to drive efficiencies. Use policy-as-code to block packages that don't meet your standards, ensuring only trusted models move towards production.

Security & quality signals

Analyze AI artifacts for vulnerabilities and licensing issues.

Policy-as-code

Build policies in OPA Rego syntax to control what packages get to your teams and pipelines, and what packages are blocked.

Observability suite

Keep track of every change and download request with our suite of logging and observability tools.

G2 Momentum Leader Winter 2026

G2 recognized Cloudsmith in its Winter 2026 Momentum Grid for Repository Management Software, reflecting sustained momentum driven by customer adoption, product velocity, and market relevance.

Frequently asked questions

Here are some of the questions we get from AI, machine learning and data science teams who are considering Cloudsmith as their artifact management platform.

  1. Yes. Cloudsmith is built for global scale. We serve the needs of massive global enterprises, providing the infrastructure to support multi-GB artifacts. With a distributed edge network of 600+ points of presence, Cloudsmith ensures high-speed access for distributed teams and customers regardless of their location. Our infrastructure scales with no intervention on your part, and if problems occur in specific regions, we route traffic to the nearest available region. We are truly cloud native.

  2. You can configure fine-tuned retention policies to balance accessibility with cost-efficiency. This allows you to preserve specific versions for your customers while automatically purging transient experiment data or outdated legacy versions.

  3. There are several ways to ensure you remain in compliance. First, you can configure your repositories to use storage in a specific region. You can configure GEO/IP rules to prevent access to artifacts from specific territories. You can use our read-only entitlement tokens to distribute models and datasets to specific users, with fine-grained restrictions.

  4. Yes. Cloudsmith integrates directly with Identity Providers (IDPs) like Okta and Azure AD. Through SCIM Deprovisioning, access is revoked instantly across the entire organization the moment a user leaves, ensuring your internal environment remains secure.

  5. Cloudsmith’s allows you to use OIDC (OpenID Connect) Authentication. This allows you to connect your CI/CD workflows using short-lived, ephemeral tokens instead of permanent, long-lived API keys. By moving away from fragile credentials, you significantly reduce the risk of credential leakage.

  6. Cloudsmith offers a fully-auditable trail over your models and datasets via client logs, audit logs and our observability suite.

Talk to us

Let us help you accelerate and secure your AI-enabled workflows and machine learning projects.