VectorCertain LLC today disclosed its comprehensive 55-patent intellectual property portfolio — the first AI safety architecture built on a governance-first, permission-to-act paradigm that spans autonomous vehicles, cybersecurity, healthcare, financial services, blockchain/DeFi, energy infrastructure, manufacturing, satellite systems, content moderation, and government AI certification.
Of the 55 patents in the ecosystem, 21 have been filed (7 in December 2025, 12 in January 2026) with the remaining 18 in active development and scheduled for filing through 2026. The portfolio encompasses over 500 claims, with every filed application scoring 10.0/10 on independent quality assurance review.
“Artificial intelligence systems do not self-authorize. All AI decisions are subject to independent, runtime governance determining whether they may be trusted, relied upon, or acted upon. This is the core paradigm that unifies our entire 55-patent ecosystem,” said Joseph P. Conroy, Founder & CEO of VectorCertain LLC.
Unlike bolt-on safety layers or post-hoc auditing frameworks, VectorCertain’s patents are architected from the ground up around a single principle: AI must earn permission to act, every time, through mathematically verifiable independent governance. This paradigm replaces model-centric safety, optimization-centric AI, and retrospective validation with governance-first, permission-to-act safety.
The portfolio is organized in a three-layer hub-and-spoke architecture where authority flows from governance hubs down through application spokes. Layer 1 comprises Core Safety Governance Hubs that define what is allowed, including patents for epistemic trust governance, numerical admissibility governance, and execution governance. Layer 2 is a Domain Governance Sub-Hub for blockchain safety, extending core governance under adversarial conditions. Layer 3 includes 22 application spokes across 12 industry verticals that apply governance without redefining safety.
VectorCertain validated its technology against more than 50 catastrophic failures spanning 2000–2024 across 11 industries, demonstrating that $1.777 trillion in losses were preventable. For example, in autonomous vehicles, the technology would have provided 8.3 seconds of advanced driver warning in Tesla highway fatalities and reduced collision energy by 78%. In financial fraud, Healthcare Claims Processing patent HC-PROV would have identified a $500 million compound medication fraud scheme within 72 hours versus the actual 36-month discovery timeline.
The architecture natively addresses 47+ regulatory frameworks, including ISO 26262 (ASIL-D) for autonomous vehicles, FDA 21 CFR Part 11 for healthcare, OCC SR 11-7 for financial services, and the EU AI Act for content moderation. Compliance is not a periodic audit function but a continuous, real-time property of system operation, with every inference generating auditable evidence automatically.
Analysis of 1,600+ AI governance patents from IBM, 5,000+ AI patents from automotive OEMs, and portfolios from Google/DeepMind, Microsoft, and NVIDIA reveals consistent gaps where VectorCertain’s governance-first ensemble claims are novel. The hub-and-spoke structure prevents terminal disclaimer sprawl and obviousness collapse while enabling flexible licensing for specific industries.
VectorCertain LLC is a Delaware corporation headquartered in Maine, founded by Joseph P. Conroy, a 30-year AI systems veteran. More information is available at www.vectorcertain.com.
