securitydatacompliancedraft
2026-01-08Proprietary Data Exposure in AI Systems
Public abstract only. This working paper surveys enterprise data-exposure risk in AI adoption, while detailed pathways and mitigation designs remain withheld.
Read note →Working Papers
Public abstracts and working paper summaries from MLNavigator. Technical appendices and detailed methods remain private unless separately released.
verificationofflinegovernancedraft
2025-11-12Offline Inference Verification for Air-Gapped Environments
Public abstract only. This working paper examines reviewable offline AI operations for air-gapped environments, while technical details remain withheld.
Read note →energymeasurementdraft
2025-09-20Energy Measurement Methodology for Local AI
Public abstract only. This draft concerns disciplined energy measurement for local AI deployments, but the detailed method is not being released publicly at this stage.
Read note →Start with a fixed-scope field deployment
One workflow, your environment, hardware included — roughly 4–8 weeks from kickoff. Local, offline-capable, and priced by scope — not by the token. You leave with a review record you can show security and compliance, whether or not you proceed.