Controlled Supply Chain Solution

Internal Artifact Supply Chain

A governed supply-chain pattern for AI applications where teams build and run from approved internal images, packages, prompts, tools, models, and checksums.

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Outcomes

What this solution should deliver

The solution is designed around practical delivery outcomes, not only a demo interface.

Avoid direct public dependency pulls during restricted builds and runtime.

Create approved internal sources for base images, Python wheels, prompts, and tools.

Record checksums, approvals, and artifact provenance.

Support repeatable offline builds for RAG, ML, and agent services.

Architecture

Architecture areas

These are the main architecture pieces to design, deploy, and operate.

Connected import zone

Security and approval gate

Internal container registry

Local Python wheelhouse

Prompt, tool, and model manifests

Offline build factory and audit evidence

Available kits

Implementation kits and resources

Start with these SovAIHub kits or resources, then adapt the implementation to your environment.

Primary kit

SovAI Air-Gap Internal Artifact Hub

Local registry, wheelhouse, prompt/tool manifests, approvals, checksums, and sample offline build.

Open

Flagship solution

Air-Gapped Sovereign AI Platform

See how artifact supply chains fit into the full air-gapped platform architecture.

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Contact

Artifact Hub Planning

Discuss how to adapt the artifact hub pattern for your internal platform environment.

Open

Governance

Controls to plan from the beginning

For enterprise and sovereign AI environments, governance needs to be part of the architecture, not an afterthought.

Approved artifacts should be immutable or versioned.

Builds should install from internal sources only.

Checksums and approval records should be retained.

SBOMs, signatures, and vulnerability scans should be added for enterprise use.

Contact

Need this solution adapted for your environment?

Share your data environment, model strategy, deployment constraints, and governance requirements to map the right implementation path.

Solution planning

Turn the solution pattern into a deployable plan.

The right path depends on your data sensitivity, runtime restrictions, platform stack, artifact supply chain, and operating model.

Contact SovAIHub