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.
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 includes core safety governance hubs such as the HCF2-SG Epistemic Trust Governance patent, which determines whether an AI decision is trustworthy through four-layer independence verification. Layer 2 comprises a domain governance sub-hub for blockchain safety, including patents like DeFi-SG for financial risk governance and ZKML-SG for cryptographic AI verification. Layer 3 consists of 22 application spokes spanning 12 industry verticals, with 7 filed as provisional patent applications including healthcare claims processing (HC-PROV) and electronic trading systems (ETS-PROV).
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 GD-CSR patent’s no-blind-spot guarantee prevents sensor degradation failures, and MRM-CFS tail-event detection identifies rare distribution-edge scenarios where perception systems fail. In financial fraud, the HC-PROV patent’s emerging billing pattern detection would have identified a $500 million exposure within 72 hours vs. the actual 36-month discovery timeline.
The real-time compliance capability is a critical differentiator. Every inference generates auditable compliance evidence automatically, addressing 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 NERC CIP for energy infrastructure. The architecture provides 24-hour regulatory detection vs. 2–4 weeks for manual review.
Analysis of 1,600+ AI governance patents from IBM, 5,000+ AI patents from automotive OEMs, and comprehensive searches across Google/DeepMind, Microsoft, and NVIDIA portfolios reveals consistent gaps where VectorCertain’s governance-first ensemble claims are novel. The hub-and-spoke structure prevents terminal disclaimer sprawl and enables licensing flexibility, allowing industry-specific bundles without requiring unrelated IP.
VectorCertain LLC is a Delaware corporation headquartered in Maine, founded by Joseph P. Conroy, a 30-year AI systems veteran who built mission-critical AI systems for the EPA, DOE, and Boeing.
