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Enterprise AI Framework

Vendor-neutral Enterprise AI architecture for government, public-sector, and regulated organizations.

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Enterprise AI Framework

Why this framework exists

Treating model selection as the architecture causes AI adoption to fail. Enterprise outcomes depend on a wider system: legal authority, mission context, data rights, human accountability, semantic grounding, integration boundaries, security controls, operational feedback, and evidence of performance.

The Enterprise Context Architecture (ECA) makes those dependencies explicit and traceable. AI needs authoritative enterprise context.

Explore the framework

  • Architecture

    Perspectives, layers, context boundaries, capabilities, and integration patterns.

    Explore architecture

  • Governance

    Decision rights, policies, risk tiers, assurance gates, and accountable operation.

    Explore governance

  • Delivery

    Specification-driven delivery, shifting roles and accountability, team topologies, and a reference implementation.

    Explore delivery

  • Security

    Zero trust, data protection, threat modeling, resilience, and incident response.

    Explore security

  • Compliance

    Traceable, non-certifying mappings to widely used frameworks and obligations.

    Explore mappings

  • Blueprints

    Reusable, risk-aware reference designs for common regulated use cases.

    Explore blueprints

Adoption steps

  1. Establish mission outcomes, legal authority, affected parties, and prohibited outcomes.
  2. Define the system boundary and classify impact and risk.
  3. Select architecture capabilities and assign accountable owners.
  4. Tailor governance, security, privacy, and assurance controls.
  5. Implement with traceable requirements and evidence.
  6. Evaluate before release and continuously monitor production behavior.
  7. Record residual risk, authorization decisions, incidents, and lessons learned.

Scope of guidance

Use the framework as architecture guidance. Legal compliance, certification, authorization to operate, and fitness for a particular purpose require separate validation by qualified authorities.

Document lifecycle

Content progresses through Draft, Public Review, Candidate, Stable, and Deprecated. Draft material may change without backward compatibility guarantees.