FERZ Intellectual Property Portfolio

MRCF is a theoretical framework that defines how language and cognition evolve in recursive loops. It provides the philosophical scaffolding for all FERZ innovations, emphasizing the role of linguistic precision in enabling sophisticated reasoning.

Its value lies in orienting FERZ's architecture around expressibility as a precondition for intelligence—a foundational premise largely absent from conventional AI design paradigms.

DELIA is a flat-constraint governance engine that transforms AI-generated language into compliant, domain-specific output using stateless, single-pass processing. Its architecture enables deterministic transformations through declarative constraints—delivering high-speed, auditable results suitable for legal, medical, financial, and operational content.

DELIA supports hybrid execution paths and structured validation without the complexity of multi-tier rule propagation, making it ideal for regulated industries requiring both speed and compliance.

LASO(f) is a deterministic AI governance framework that controls both what AI systems say and do. Its integrated 17-tier architecture combines eight linguistic tiers for transforming language into compliant, auditable output with nine action tiers that validate AI-initiated decisions for safety, authorization, and compliance.—from syntax to discourse.

Through its Semiotic-Aware Architecture (SAA), LASO(f) also governs the structure of meaning—Sign, Object, Interpretant—to preserve symbolic coherence, cultural sensitivity, and intended audience interpretation. Designed for high-stakes sectors like healthcare, finance, defense, and law, LASO(f) delivers mathematically guaranteed precision, sub-200ms performance, and cryptographically signed audit trails, ensuring AI outputs are accurate, safe, and aligned with human and regulatory expectations.

STRATA-G defines the recursive logic spine for AGI oversight across regulated, adversarial, and high-stakes environments. By coordinating six modular layers—from constraint enforcement and cultural integration to safe self-modification—STRATA-G enables deterministic adaptation without sacrificing speed or interpretability. It governs how AGI systems reason and adapt, supporting real-time explainability, triage coordination, and jurisdictional constraint integration.

The Constitutional Blockchain is a deterministic governance substrate enforcing a tripartite structure—Legislative, Executive, and Judicial branches—within AGI ecosystems. It codifies policy into immutable chains, blocks unconstitutional actions at runtime, and enables legal-style precedent adjudication using BFT consensus and hardware-integrated emergency triggers. Designed for domains like healthcare, finance, defense, and civil infrastructure, it ensures AGI action remains within transparent, jurisdictional bounds.

The FERZ Behavioral Engine™ is a runtime adaptation system that modifies AI responses based on computed user behavioral trajectories rather than immediate inputs or static preferences. Using the proprietary Formula of Fate™ mathematical framework, it tracks effort, constraint, and support signals across behavioral domains to deliver consequence-based interactions that challenge avoidance patterns and enforce accountability. Its deterministic vector modeling enables predictive intervention 3-5 steps earlier than sentiment-based systems, making it valuable for applications requiring sustained behavioral change or decision acceleration.

CausaCore is a patented orchestration framework that unifies four specialized engines—deterministic, probabilistic, neural, and agent-based—to deliver transparent causal inference across medical, economic, political, and scientific domains. By combining multi-LLM coordination with mathematical validation protocols, it ensures that causal links are not only discovered but formally verified and auditable.

Unlike single-domain or black-box models, CausaCore enables organizations to tackle complex, cross-domain causality problems with explainable outputs suitable for regulated industries. Its architecture supports EU AI Act–compliant governance, automated engine selection, and deterministic validation, making it an essential foundation for research, business intelligence, and compliance-driven decision support.

SCM reduces language complexity without losing meaning, enabling high-fidelity summarization, compression, and reformulation for regulated or knowledge-dense contexts.

Unlike generative summarizers, SCM maintains semantic and causal traceability, preserving logical integrity and enabling downstream validation.