Wagoner Enterprises, LLC
Classified and air-gapped AI, authorization evidence automation, and AI assurance for federal and defense programs.
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What we do
Classified AI operations
Deployment and lifecycle management of large language models built for air-gapped, Sensitive Compartmented Information Facility (SCIF), and high-side environments: signed release bundles, offline evaluation, policy-based promotion gates, and adversarial testing.
Authorization & evidence automation
Continuous generation of SBOMs, SHA-256 audit trails, NIST RMF control mappings, POA&M-ready findings, and signed Evidence Packs as a byproduct of the delivery pipeline.
AI assurance & governance documentation
AI-BOMs, model cards, data cards, transparency checklists, evaluation suites, and risk registers aligned to federal AI governance expectations.
Data classification & Zero Trust execution
Policy-driven sensitive data classification without external data egress, and translation of Zero Trust policy into enforceable, continuously monitored configurations.
Disconnected & high-side deployment engineering
Containerized, Kubernetes-deployable systems built for file-based ingestion and controlled export as the default operating mode, with no mandatory SaaS dependency.
Why us
- Evidence-native by design: artifacts are cryptographically bound and assessor-ready at the moment they are produced
- The same workflow runs connected or fully disconnected, so an enclave deployment is not a separate product
- No vendor lock-in: open standards, portable data, and a documented written exit path
- Government-led evaluation supported, including independent testing and source code review under agreement
- We publish what can be published and withhold what would aid an adversary, and we say which is which
- We do not retain, train on, or access customer operational data
Registration and maturity
Ten solutions across four capability families.
Classified AI Operations
Authorization & Evidence
Data & Policy Automation
Mission Platforms
Frameworks we build to
How to reach us
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