TauGuard provides technical documentation, AI governance research papers, compliance guides, and framework specifications for trustworthy AI systems. All documents are available for viewing and download.
Slide presentation introducing TauDIL framework and how it supersedes probabilistic AI governance models. Topics: deterministic AI governance, TauDIL specification, AI safety architecture, invariant logic systems.
Download PDFIntroductory overview of the TauDIL (Tau Deterministic Invariant Logic) framework for AI systems governance.
Download PDFAnalysis of how the IFA Specification v1.0 drives sustainable AI through structural trustworthiness rather than checkbox compliance.
Download PDFComplete architectural specification for the TauDIL system including component diagrams, data flows, and integration points.
Download PDFInvariant Enforcement Layer protocol specification detailing enforcement mechanisms for AI behavioral constraints.
Download PDFTechnical documentation for the SYGON semantic governance engine, covering ontological alignment and meaning-preserving transformations.
Download PDFAudit trail and chronicle specification for immutable AI decision logging under the Aelthered framework.
Download PDFResearch paper on semantic signal conflict in large language models and AI systems. Topics: signal theory, semantic conflict, AI alignment.
Download PDFFormal mathematical treatment of semantic meaning structures in AI systems. Topics: category theory, meaning preservation, formal semantics.
Download PDFGeometric models for representing and reasoning about semantic spaces in AI governance systems.
Download PDFTheoretical foundations for constitutional AI architectures that embed governance constraints at the architectural level.
Download PDFFormal methods paper on coherence conditions and admissibility criteria for AI system outputs and governance rules.
Download PDFComplete IFA framework specification for building AI systems on invariant foundations. Covers invariant specification, enforcement, and verification.
Download PDFSecurity-by-design framework for AI systems. Architectural approaches to AI security that go beyond perimeter defenses.
Download PDFFramework for embedding governance requirements directly into AI system architectures rather than applying them as external constraints.
Download PDFFramework for authority-based governance of machine learning systems, covering training constraints and deployment authorities.
Download PDFPractical guide to EU Artificial Intelligence Act compliance using TauGuard frameworks. Covers risk categorization, conformity assessment, and documentation requirements.
Download PDFProtocol for GDPR compliance in AI systems, covering data subject rights, automated decision-making obligations, and privacy-by-design requirements.
Download PDFSOC 2 Type II implementation guide for AI governance systems, covering Trust Service Criteria and audit evidence collection.
Download PDFIntegration guide for aligning TauGuard frameworks with the NIST AI Risk Management Framework. Covers GOVERN, MAP, MEASURE, and MANAGE functions.
Download PDFFull API reference documentation for TauGuard developer integration. Covers authentication, endpoints, request/response schemas, and error codes.
Download PDFStep-by-step integration guide for embedding TauGuard governance capabilities into existing AI pipelines and systems.
Download PDFDeveloper reference for TauDIL rule syntax, including grammar specification, examples, and validation tools.
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