Where the universe of the official NAPE documentation resides. This includes How-To's, Tech Docs, and much more.
A demonstrative workbench for institutional governance engineering. Enables mechanical governance and traceability from policy intent to technical production.
The source code repository for the core nape software
A Management-Methodology Approach to Quality Assurance in AI-Assisted Software Development
Governance-as-code engine for AI platforms. Define policies in YAML, map to compliance standards (SOC 2, EU AI Act, ISO 27001, PCI-DSS, GDPR, HIPAA, NIST), evaluate decisions, run dry-runs to estimate blast radius, produce audit-ready ledgers. Third piece of the AI Platform Engineering trilogy.
Local-first governance tool for assessing the long-term sustainability, maintainability, resilience, and organisational impact of AI-supported systems, workflows, curricula, and research projects.
The central repo which contains every build, deploy, and release workflow for all NAPE software.
AI Capability Studio : offline-first, static structured workflow tool for generating AI Workflow Records using the AI Capability Framework. No AI calls. No accounts. Governance-ready exports.
Local-first governance tool for recording, analysing, and learning from AI-related incidents, failures, near misses, and hallucinations through structured review, root-cause analysis, mitigation tracking, and governance-ready reporting.
Governance-first design tool for creating, analysing, and documenting AI-supported workflows with explicit human oversight and accountability.
Ethical AI governance framework for multi-model alignment, integrity, and enterprise oversight.
Governance-first tool for analysing risk, fragility, and oversight gaps in AI-supported workflows
Local-first governance tool for structured ethical review of AI-supported systems, workflows, and outputs using configurable frameworks, transparent scoring, evidence capture, and governance-ready reporting.
Governance-first tool for assessing organisational readiness and maturity in governing AI-supported systems
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