AI quality-control frameworks

Structure behind the work.

Four frameworks for giving AI-assisted work a clear brief, defined responsibilities, and meaningful checks. Each addresses a different part of the path from an idea to a reviewed deliverable.

Reference library and authoring engine

THE SWIGH Canon and Master Engine

Turn a real objective into a structured assignment.

A reference library paired with a Python and SQLite engine that assembles task packets, checks submitted work against requirements, and keeps review separate from authoring. The engine releases work only when its authority and evidence checks pass.

What it includes

  • A 153-page reference with 66 templates
  • An offline Brief Builder and task-packet engine
  • Submission checks, trusted review, and controlled exports

Relevant when AI-assisted work needs clearer instructions, ownership, and review before the result is used.

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Verification and release-control system / UEC

Universal Execution Control

Check the work, not just the completion message.

A standalone control system for Codex and other language-model projects. It connects an inspectable work contract to actual checks, evidence records, and review. Its local export gate blocks a release when required evidence is missing or out of date.

What it includes

  • Check profiles for software, websites, research, writing, and business work
  • A Python check runner and SQLite evidence records
  • Self-tests, a working demonstration, and benchmark scenarios

Relevant when a team needs a traceable way to decide whether work meets its requirements.

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Website-building framework / AWCF

Axiom Website Creation Foundry

Connect a website brief to a build-and-review process.

A Codex skill package that classifies the website mission, selects relevant requirements, creates project files, and guides rendering, inspection, repair, and handoff. It includes 16 website Family Packs and 560 requirement rows.

What it includes

  • Website-specific requirements and capability contracts
  • Context-selection, integrity, and project-scaffolding helpers
  • A delivery workflow covering visual review, repairs, and run instructions

Relevant when website creation needs a consistent process across different project types, not just a first draft.

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AI governance blueprint

Axiom Runtime Governance Specification

Define how an AI system should be controlled.

A governance specification developed through three versions into a 29-file bundle. It sets out runtime control structures through escalating scenarios involving compliance governance, sovereign intelligence, and healthcare AI governance.

What it includes

  • A versioned governance specification
  • Three scenarios for examining higher-consequence decisions
  • A blueprint for runtime controls and oversight

Relevant when an AI project needs explicit responsibilities and control rules. A governance blueprint is not a regulatory certification.

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These project summaries describe the scope and deliverables recorded in our systems portfolio. Detailed materials are shared during qualified discussions, with proprietary methods and client information protected.