Declare the boundary.
Define where workloads may run, what data they can access, and which actions require approval. Make the operating rules explicit.
Intelligence can propose. Your policy decides.
We’re building an open source trust layer that keeps your systems within approved boundaries, controls what AI can do, and produces evidence of every change.
Read reality.
Detect the drift.
Explain the finding.
Propose a repair.
Permit only the
exact approved action.
Apply the change.
Stay within scope.
Check the result.
Preserve the record.
Security tools identify problems. AI can suggest a fix. Nomiarch is being designed to connect the decision, the action, and the proof—so you can see why a change was allowed and whether it worked.
Define where workloads may run, what data they can access, and which actions require approval. Make the operating rules explicit.
Let AI investigate and propose. Use independent authorization and a scoped executor to govern what can actually change.
Verify the deployed state. Connect observations, approvals, changes, and results in an evidence package you can inspect and retain.
The long-term design spans public cloud, sovereign platforms, and disconnected environments. Your infrastructure stays in place. Nomiarch provides the policy and evidence layer across it.
Explore the deployment planBegin with Azure and containerized services on a Linux VM.
Extend policy to location, administration, keys, and egress.
Local models, controlled artifact import, and offline evidence.
The first milestone is deliberately specific: detect an Azure Storage account that allows anonymous blob access, propose a repair, authorize it, and verify the result.
// Azure Storage account configuration
allowBlobPublicAccess: trueallowBlobPublicAccess: falseDesign target · No runnable release yet
Compare actual configuration with declared policy and identify the source that owns it.
Generate a bounded repair. Bind independent policy and human approval to that exact change.
Apply through scoped access. Read the deployed state again to check that the condition changed.
Record the decision and result, with a verifiable local export for recovery and review.
Start with a clear design. Build a narrow proof. Make it reproducible. Publish what works and what still needs to be tested.
Trust model, service boundaries, VM deployment, and acceptance criteria for the first proof.
Read the architectureConnect observation, local AI, policy, approval, execution, and verification in a test environment.
A versioned bundle, tested installation guide, refusal tests, and a recovery walkthrough.
Beyond the first proof: more infrastructure adapters, AI tool admission, sovereignty profiles, and disconnected operation.
An open source project building a trust and authorization layer for enterprise infrastructure and AI. The goal is to keep systems within their approved operating boundaries and generate evidence of the decisions and changes made.
Platform engineers, security teams, and technology leaders responsible for sensitive systems. The initial focus is Canadian government and regulated enterprise use cases, with policy profiles designed to expand over time.
There is no runnable release yet. The architecture and deployment plan are available now. The first release is intended to package containerized services for a supported Linux VM, with tested installation and recovery instructions.
Nomiarch is being designed to enforce declared controls and produce evidence for review. Authorization and certification remain decisions for the responsible organization. Sovereignty also depends on hosting, jurisdiction, administration, keys, and dependencies.
No. The scope includes conventional infrastructure and AI across connected, restricted, and disconnected environments. Fully air-gapped operation is a planned deployment mode, with controlled artifact import and no external service dependency in the internal runtime.
Explore the vision. Inspect the design. Follow the first proof.