Our Core Innovation
Traditional security asks who is acting. We ask why. This single shift changes everything about how AI agents are governed.
the differentiation.
Intent as a Security Primitive
Role-based access control was designed for humans with stable job functions. AI agents need something fundamentally different.
Traditional IAM
Grants broad, static permissions based on identity alone.
// Role-Based Access Control
if (agent.role == "FinanceAnalyst") {
grant(ALL_FINANCIAL_DATA)
}
Ignores why an agent is accessing data
Over-provisioned permissions by default
Vulnerable to prompt injection
intellectual property.
Purpose-Built for AI Security
Four USPTO applications covering the foundational architecture for AI agent governance.
#19/403,811
AI Agentic Control Plane
Utility – Nonprovisional
Key claims: Non-bypassable governance sidecar, Unified Intermediate Representation, Behavioral Fingerprinting, Vendor-neutral enforcement layer
#63/932,782
Purpose-Aligned Zero-Trust
Systems & Methods
Key claims: Intent-Aware Elevation Engine, Semantic Intent Vectors, Time-bounded purpose-scoped credentials, Policy graph evaluation
#19/436,183
Behavior-Aware Storage Governance
Utility – Nonprovisional
Key claims: Semantic Copy Attribution, Recovery Feasibility Analysis, Policy-driven optimization for AI-managed storage
#19/438,384
Intent-Aware Judicial Evaluation
Utility – Nonprovisional
Key claims: Judicial evaluation frameworks, Intent interpretation, Response governance systems
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Transform AI governance from cost center into competitive advantage.