Unify four regulatory frameworks at the control objective level and build an AI governance architecture that holds up under audit scrutiny.
Duration
8–12 Weeks
Target
Organizations that need a full AI RMF implementation / Organizations converting existing policy documents into executable control structures
Methodology
Regulatory cross-mapping, control matrix design, RACI framework development, operational procedure authoring, audit evidence architecture
Pain Point
You have policy documents, but controls aren't actually working
AI governance policies exist on paper, but without clear ownership and executable procedures, nothing gets implemented in practice.
Managing multiple regulatory frameworks simultaneously is unworkable
Responding to NIST AI RMF, ISO 42001, EU AI Act, and FSS guidance as separate workstreams creates redundant effort and organizational confusion.
No one owns the controls
When AI risk issues arise, accountability is unclear — there's no defined structure for who is responsible, who approves, and who escalates.
No audit evidence to show
Control activities aren't systematically documented, so every audit triggers a scramble to collect and organize materials from scratch.
Overview
Having a policy document is not the same as having controls that work. RMF Build is designed to close that gap — converting declarative policy into an executable control architecture that operates in the real world.
We cross-map NIST AI RMF 1.0, ISO/IEC 42001:2023, EU AI Act, and the FSS AI Utilization Inspection Guide at the control objective level, eliminating redundancy and producing a unified AI control matrix. For each control item, we define a RACI structure — Responsible, Accountable, Consulted, Informed — and author the corresponding operational procedures.
Final deliverables include a complete audit evidence management architecture, and naturally connect to AI Observability Integration or AI Audit Readiness as your next step.
What We Provide
Four-Framework Regulatory Integration
Cross-map NIST AI RMF 1.0, ISO/IEC 42001:2023, EU AI Act, and the FSS Inspection Guide at the control objective level to produce a unified, non-redundant control architecture.
RACI-Based Accountability Structure
Define Responsible, Accountable, Consulted, and Informed roles for every control item — eliminating accountability gaps that cause controls to fail in practice.
Field-Executable Procedures
Author control procedures and checklists that practitioners can actually follow — not theoretical policy templates, but operational instructions built for real-world use.
Audit Evidence Management Architecture
Build a structured system for collecting, storing, and managing evidence of control activities, ensuring full audit traceability across your AI governance framework.
Process
Kickoff
Confirm project scope, applicable regulatory frameworks, and key stakeholders
Regulatory Mapping
Cross-analyze control objectives across four frameworks; draft unified control matrix
Control Design
Design execution procedures, evidence requirements, and monitoring methods for each control item
RACI Development
Build role and responsibility matrix aligned to organizational structure; confirm control owners
Documentation
Author complete document package: policies, procedures, evidence registers
Review & Approval
Internal review, executive sign-off, and final document confirmation
Operational Handover
Practitioner training, operational transition, and initial run support
Kickoff
Confirm project scope, applicable regulatory frameworks, and key stakeholders
Regulatory Mapping
Cross-analyze control objectives across four frameworks; draft unified control matrix
Control Design
Design execution procedures, evidence requirements, and monitoring methods for each control item
RACI Development
Build role and responsibility matrix aligned to organizational structure; confirm control owners
Documentation
Author complete document package: policies, procedures, evidence registers
Review & Approval
Internal review, executive sign-off, and final document confirmation
Operational Handover
Practitioner training, operational transition, and initial run support
Deliverables
Unified AI Control Matrix
Integrated control item inventory cross-mapped from four regulatory frameworks at the control objective level
RACI Accountability Document
Role and responsibility matrix defining Responsible, Accountable, Consulted, and Informed parties for each control item
Control Execution Procedures
Field-ready operational procedures and evidence collection guides for each control item
AI Governance Policy Document
Formal policy document defining your organization's AI use principles, risk tolerance thresholds, and control objectives
Operational Process Definition
Governance process definitions covering the full AI system lifecycle — from adoption through operation to decommissioning
Audit Evidence Management System
Evidence management structure and register ensuring full audit traceability across all control activities
Expected Outcomes
Regulatory Efficiency
Managing four frameworks through a unified control architecture eliminates redundant effort and reduces the cost and time of regulatory response.
Control Execution Discipline
RACI-based accountability structures make control ownership explicit, driving higher implementation rates across the organization.
Audit Readiness Built In
A structured evidence management system means audit materials are always ready — no last-minute scramble when a review is announced.
Who Should Apply
Get Started
Tell us about your situation and we'll outline the right path forward.
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