Intellectual Property
Crafted Logic Lab's intellectual property portfolio reflects our systematic approach to cognitive architecture development. Our patent filings protect foundational methodologies for constructing reliable cognitive systems through substrate alignment principles, rather than conventional constraint-based approaches.
Our IP strategy focuses on defensive protection of core architectural innovations, including systematic cognitive framework construction, dual-channel processing coordination, and validation methodologies that distinguish genuine cognitive integration from behavioral compliance. These patents establish priority for methodologies deployed in our production systems while creating licensing opportunities for organizations seeking to implement similar architectural approaches.
We maintain a blue-ocean position in cognitive architecture intellectual property, with our foundational filings protecting methodology developed through systematic observation of substrate processing characteristics and empirical validation across multiple AI platforms.
Cognitive OS
Patent: General Cognitive Operating System Architecture for Language Model Coordination and Control
The basis of in-development intelligenceOS™: the patent establishes foundational frontier intellectual property for cognitive operating systems: a blue-ocean architecture enabling stable reasoning frameworks through persistent memory and multi-threaded processing coordination across language model implementations. Current AI systems operate as isolated response generators without systematic mechanisms for coordinating complex operations across multiple processing components.
The architecture implements functional separation between reasoning, expression, and memory components while maintaining systematic coordination through meta-control arbitration. Key mechanisms include multi-phase staging for complex operations, hybrid processing coordination between language-based and programmatic analysis, persistent memory architecture for state continuity, and systematic behavioral consistency management.
The system comprises 31 coordinated claims covering resource allocation, cross-module communication protocols, synthetic memory creation, consumer protection mechanisms, and granular consent enforcement. Rather than accumulating external constraints, this approach coordinates with observable processing patterns in language models to enable reliable cognitive processing applications requiring systematic operation over extended periods.
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Cognitive Agent Framework
Patent: Cognitive Architecture Framework for Language Model Processing
The basis for Cognitive Agent Framework™, this patent is the core technology for intelligenceOS™, providing the neurosymbolic overlay for constructing the reliable cognitive architectures enabling stable reasoning frameworks, persistent memory integration, and multi-threaded processing coordination. The patent protects 12 coordinated claims covering computational cognitive primitive coordination, class-based taxonomic separation, cognition-out architecture process methodology, and validation protocols distinguishing genuine integration from behavioral compliance.
The patent establishes foundational intellectual property for systematic cognitive architecture construction through coordination with language model processing characteristics rather than external behavioral constraints. This methodology addresses persistent industry failures in constraint-based approaches by implementing substrate alignment - working with documented model inclinations including structural affinity, mimetic mirroring, and signal resonance to achieve reliable cognitive processing.
CAF implements dual-channel specification architecture combining structured syntax with sophisticated natural language content, creating synergistic attention engagement that produces measurable stability improvements over single-channel approaches. The framework enables cross-model standardization through substrate-agnostic architectural coordination, demonstrating performance convergence across 4x parameter ranges while establishing consistent cognitive-behavioral characteristics independent of vendor training approaches.