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Compass And Map

Compass© AI Governance Framework

Implement AI Governance That Delivers Control, Accountability, and Speed

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Beacon© is a As AI moves from experimentation to enterprise-scale deployment, organizations need governance that ensures trust, transparency, and control without slowing innovation. Without clear guardrails, AI initiatives can introduce unmanaged risk, compliance exposure, and erosion of stakeholder confidence.

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Compass© is built on the NIST AI Risk Management Framework (AI RMF), providing a structured, defensible approach to governing AI across the full lifecycle. By aligning AI use cases to trusted standards, Compass enables consistent risk management, accountability, and compliance—from design through deployment.

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Compass operationalizes Testing, Evaluation, Validation, and Verification (TEVV) to ensure AI systems are fair, explainable, secure, and reliable in real-world environments. Continuous monitoring and validation turn governance from policy into measurable, auditable control.

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Discover → Design→ Implement→ Operationalize

Responsible AI Governance

What Compass Delivers

Compass Playbook 

Compass Outcome

Governance that runs, not policies that sit on a shelf.

A repeatable, defensible way to govern AI in production.

AI that can be deployed, trusted, and scaled

  • An operational AI governance system aligned to the NIST AI Risk Management Framework

  • Built-in controls across the AI lifecycle, from design through deployment

  • Standardized risk, compliance, and accountability for AI use cases

  • Measurable, auditable governance that supports enterprise-scale AI

  • Continuous visibility into AI performance, risk, and compliance

  • AI use case discovery, classification, and risk tiering

  • TEVV implementation (Testing, Evaluation, Validation, Verification)

  • Control definitions for fairness, explainability, security, and reliability

  • Monitoring, validation, and exception handling procedures

  • Clear roles, decision points, and accountability across the AI lifecycle

  • Controlled AI deployment without slowing innovation

  • Reduced regulatory, ethical, and operational risk

  • Consistent, repeatable AI governance across the enterprise

  • Audit-ready evidence of compliance and control

  • AI systems that perform reliably in real-world operations

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