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MLNavigator is the company behind adapterOS.

adapterOS is MLNavigator’s current product: offline AI for sensitive operations, with proof built in.

Our mission

Organizations in regulated and high-assurance environments need AI that can work over sensitive records without cloud data movement or untraceable answers.

adapterOS is our answer: a managed on-prem/offline AI system that turns private records into cited answers, proof packets, and reviewable work. MLNavigator supports pilot deployment, validation, and ongoing operation.

MLNavigator

MLNavigator is the company behind adapterOS. The company builds governed offline AI systems for sensitive environments where data classification, regulatory compliance, or operational policy requires local control and reviewable evidence.

Patent applications have been filed covering core aspects of the adapterOS system. Public materials describe outcomes, artifacts, and proof surfaces without exposing proprietary implementation details.

Company facts

EntityMLNavigator
FoundersJames KC Auchterlonie, Donella Cohen
FocusGoverned offline AI for sensitive environments
IPPatent applications filed
StatusAvailable for pilot engagements
Support modelManaged deployment with annual maintenance and direct support

Why adapterOS

  • Evidence-producing. The receipt and proof architecture makes offline AI reviewable work rather than an untraceable answer box.
  • Governance-first. The workflow model keeps object, action, state, policy, and proof tied together at the artifact level.
  • Locally controlled. Managed on-prem/offline deployment is the wedge for customers who cannot accept cloud data movement.

Investor-safe defensibility

The public story is the wedge and proof surface, not proprietary implementation details.

Offline deployment wedge. Sensitive customers need capability without cloud data movement.
Evidence architecture. The product centers receipts, proof packets, and review outcomes.
Governed workflow model. Object, action, state, policy, and proof stay tied together.
Operational know-how. Pilot deployment, validation, and support are part of the product.
Policy and audit surfaces. Buyer-safe artifacts make the system legible to reviewers.
Patent applications filed. Public claims stay at outcome level; implementation specifics stay protected.

Patent pending

Patent applications covering core aspects of the adapterOS system have been filed with relevant patent authorities. The applications relate to methods and systems for managed AI deployment in controlled environments.

Inventors: James KC Auchterlonie and Donella Cohen. For IP inquiries, contact legal@adapteros.com.

Contact

See how it works

The briefing covers capabilities, evidence model, security approach, and engagement structure.