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Deterministic AI Infrastructure for Regulated Systems

MLNavigator builds compliance-first AI runtime technology

designed for auditable, offline, and high-assurance environments.

The Problem with Today’s AI Systems

  • Non-deterministic execution makes audit evidence unreliable
  • No verifiable execution trail linking outputs to inputs and configuration
  • Cloud-dependent runtimes are incompatible with air-gapped and classified environments

Core Technology: adapterOS

Deterministic Execution

Policy-scoped controls over quantization, stop conditions, and kernel selection produce repeatable inference runs.

Cryptographic Receipts

Hash-chained execution receipts link inputs, configuration, and outputs into audit-ready evidence.

Offline Deployment

Runs without outbound network calls, license servers, or telemetry. Designed for air-gapped and classified networks.

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Designed for Regulated Environments

Aerospace & Defense

ITAR, CMMC, and air-gapped deployment requirements

Critical Infrastructure

Offline operation in energy, transport, and utility systems

Regulated Finance

Audit trails and model governance for compliance teams

Government & Public Sector

Sovereign data, classified networks, and FedRAMP-aligned controls

Latest Research & Engineering Notes

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Feb 11, 2026

Verification Scope

What adapterOS verification covers, what it does not cover, and where human oversight applies.

Feb 11, 2026

MLNavigator and adapterOS

Company and product overview: market need, product scope, validation status, and business model.

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