The AI Governance Layer for National Security
AAyeAye delivers secure, transparent, and mission-ready AI infrastructure for defense and government. Our flagship AI Guardian platform enforces policy compliance, auditability, and trust at the point of inference—ensuring that artificial intelligence always answers to you.
AI Infrastructure & Governance
Modular Intelligence, Governed by Design
We deliver the building blocks of secure, mission-aligned AI — from infrastructure to enforcement — with transparency at every step.
ML Infrastructure Consulting
Architect, deploy, and optimize production-grade ML systems using Seldon Core, MLFlow, Argo Workflows, Ray, and more. We specialize in building Kubernetes-native platforms with auditability and scaling in mind.
AI Governance & Rule Enforcement
Define and enforce constraints on model behavior through our custom rules engine layer — set confidence thresholds, restrict actions, log high-risk inferences, and ensure compliance with mission-aligned policies.
RMF & ATO Automation
Accelerate authorization workflows with tooling that auto-generates ITCSC templates, control mappings, and STIG overlays from SysML or MBSE models. Ideal for ISSOs and AOs seeking faster ATO without cutting corners.
Interested in a partnership?
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Mission-Ready AI
Built for Oversight, Engineered for Scale
SentinelAI helps government and defense teams deploy, govern, and secure AI systems — with confidence, auditability, and compliance from the start.
- Model Rules Engine
- Enforce thresholds, restrict unsafe outputs, and audit inference behavior with a lightweight, policy-driven AI governance layer.
- ML Platform Engineering
- Design and deploy scalable, secure ML platforms using Seldon, MLFlow, Ray, and Argo — tailored for hybrid cloud and air-gapped needs.
- RMF & ATO Acceleration
- Automate RMF Steps 1–3 with system model ingestion, control mapping, and machine-readable documentation outputs.
- Audit-Ready Monitoring
- Track model activity, configuration drift, and compliance status across environments — from edge agents to core systems.