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    REIGN · REGULATORY ALIGNMENT

    Reign maps to the regulatory frameworks your function is asked to answer for.

    Continuous Operational Assurance for Enterprise AI, pre-mapped to the regulations your CISO, Chief Risk Officer, General Counsel, and Chief Compliance Officer are accountable to.

    Regulators are not converging on a single AI rulebook. They are converging on a single underlying control discipline. Reign ships pre-mapped to the six frameworks that carry the most regulator weight across the geographies and industries your enterprise operates in. The evidence Reign emits is the evidence your regulator already accepts.

    Or apply for a focused pilot →
    Frameworks
    EU AI Act · SR 26-2 · DORA · NIST AI RMF · ISO 42001 · FDA PCCP
    Geographies
    Europe · United States · Canada · Global
    Output
    Submission-ready evidence, regulator vocabulary
    Pilot intake
    Design partner motion. Limited intake.
    What Reign supports

    Reign supports compliance readiness, auditability, continuous monitoring, and control evidence for enterprise AI agents. It does not by itself guarantee regulatory compliance.

    The callout sets the boundary for everything below it. Reign maps to the frameworks. The accountable function inside the customer carries the compliance opinion. Reign carries the evidence chain that opinion is built on.

    One control discipline, six vocabularies

    The frameworks talk. Reign translates.

    The regulators your function reports to do not coordinate the language. EU AI Act says one thing. The Fed says another. DORA, NIST, ISO, and FDA each carry their own vocabulary and their own evidentiary expectations. Underneath the language, the control discipline is largely the same. Identity-bound runtime decisions. Tamper-evident audit chains. Independent challenge. Submission-ready evidence on demand.

    Reign was architected against that underlying discipline. The platform delivers it once. The output is then expressed in the vocabulary each regulator already accepts.

    Six frameworks. Three geographies. One evidence chain.

    Framework

    EU AI Act

    Articles 9, 10, 12, 14, 15

    European single market

    Read the mapping
    Framework

    SR 26-2

    Federal Reserve MRM

    US-supervised institutions

    Read the mapping
    Framework

    DORA

    Digital Operational Resilience Act

    EU financial services

    Read the mapping
    Framework

    NIST AI RMF

    Govern, Map, Measure, Manage

    US cross-cutting organizing model

    Read the mapping
    Framework

    ISO/IEC 42001

    AI Management System

    Global

    Read the mapping
    Framework

    FDA PCCP

    Pre-determined Change Control Plan

    US life sciences

    Read the mapping
    Framework 1 of 6

    EU AI Act. Articles 9, 10, 12, 14, 15.

    The EU AI Act sets binding obligations on providers and deployers of high-risk AI systems across the European single market. The core obligations land in Article 9 (risk management), Article 10 (data and data governance), Article 12 (record keeping), Article 14 (human oversight), and Article 15 (accuracy, robustness, and cybersecurity).

    Reign delivers risk classification per model and per agent at the gateway, with continuous risk assessment running against the evidence chain. The audit chain satisfies Article 12 record-keeping requirements at the population level. Human oversight handoffs are policy-enforced at the gateway under Article 14. Drift detection and robustness testing run continuously against Article 15.

    The customer leaves with submission-ready evidence packets framed in EU AI Act vocabulary. Deep reference at /reign/eu-ai-act.

    GeographyBinding on any AI system placed on the EU market or whose output is used in the EU.
    Framework 2 of 6 · Footnote 3 wedge (secondary surface)

    SR 26-2. Reign is the playbook.

    The Federal Reserve's revised model risk management guidance, SR 26-2, supersedes SR 11-7 and remains the foundational expectation for model risk at supervised institutions. At footnote 3, the guidance carves out generative and agentic AI from the prescriptive SR 11-7 playbook and instructs supervised institutions to govern these systems using existing model risk management practices.

    The carve-out creates a regulator-named obligation with no regulator-prescribed playbook. Supervised institutions are accountable for the outcome without a step-by-step procedure to point to during an examination.

    Reign is the playbook.

    The platform delivers the four controls SR 26-2 expects, expressed in the vocabulary the Fed already accepts. Approved-model registry with risk classification. Independent challenge as a continuous artifact, not a quarterly document. Tamper-evident change records on every model change. Examination-ready evidence on demand. Deep reference at /reign/for-mrm and /reign/model-risk-validation.

    GeographyUS-supervised institutions under Federal Reserve oversight. Canadian D-SIBs reading OSFI E-23 face a substantially parallel obligation, mapped from the same evidence chain.
    Read the SR 26-2 wedgeSee for Model Risk Management
    Framework 3 of 6

    DORA. ICT risk, third-party risk, and the operational resilience surface AI now sits inside.

    The Digital Operational Resilience Act binds EU financial-services entities to a single ICT-resilience regime. The obligations land in five domains. ICT risk management. Incident reporting. Digital operational resilience testing. ICT third-party risk. Information sharing.

    Agentic AI now operates inside every one of those domains. A misbehaving agent is an ICT incident. An external model provider is a critical ICT third-party. A model that drifts under load is an operational resilience failure under stress testing.

    Reign instruments the AI layer against each DORA domain. Agent actions and model invocations are captured at the gateway and time-stamped for incident reconstruction. The evidence chain feeds the resilience-testing program. Third-party model and tool dependencies are catalogued and continuously assessed. The output is submission-ready in the format your DORA examiner is already preparing to consume.

    GeographyEU financial entities under DORA's scope. Binding on US and UK subsidiaries that operate in the EU.
    Framework 4 of 6

    NIST AI RMF. Govern, Map, Measure, Manage.

    The NIST AI Risk Management Framework is the voluntary US standard most enterprises adopt as their internal organizing model. The four functions, Govern, Map, Measure, and Manage, each carry sub-categories that show up inside enterprise AI governance policies, board reports, and internal audit programs.

    Reign delivers the runtime substrate that the NIST functions describe. The audit chain is the measurement layer. The gateway is the management layer. The approved-model registry and risk classification surface are the mapping layer. The policy framework and access controls are the governance layer.

    For organizations using the NIST AI RMF as the connective tissue across their AI program, Reign is the operational layer that gives the framework something concrete to point to.

    GeographyUS enterprises by default. Increasingly referenced by Canadian, UK, and Asia-Pacific functions as the internal organizing model.
    Framework 5 of 6

    ISO 42001. AI Management System.

    ISO/IEC 42001 is the first certifiable AI management system standard. Like ISO 27001 for information security, 42001 specifies the management system, not the controls themselves. A certified organization runs an AI management system that identifies AI risks, sets objectives, monitors performance, and continuously improves.

    Reign provides the operational substrate that the management system runs against. The audit chain produces the monitoring data the AIMS reviews. The approved-model registry is the AI inventory the standard requires. Independent challenge and continuous drift detection feed the corrective-action loop.

    For organizations pursuing 42001 certification, Reign accelerates the certification audit by giving the auditor a continuous, queryable evidence chain instead of point-in-time snapshots.

    GeographyGlobal. Increasingly required by procurement and partnership contracts across regulated industries.
    Framework 6 of 6

    FDA PCCP. The life-sciences regulated-AI on-ramp.

    For AI/ML-enabled medical devices, in-vitro diagnostics, and pharmaceutical manufacturing systems, the FDA's Pre-determined Change Control Plan framework allows pre-authorized modifications to a regulated AI system without re-submission, provided the change is inside the PCCP envelope and the supporting evidence holds up.

    Reign delivers the PCCP-aligned change record on every model change. The approved-model registry tracks the envelope. The audit chain captures the actual change with provenance, reviewer, validation results, and impact assessment. The output is the artifact the FDA submission process is built to consume.

    Deep references at /reign/life-sciences and the FDA PCCP framework card.

    GeographyUS life sciences. Also referenced by EMA and Health Canada under broadly parallel change-control thinking.
    Where each framework applies

    Geographic and industry axes.

    Europe

    EU AI Act and DORA. Binding on EU-resident entities and on US, UK, and Canadian operations that touch the EU market or EU customers.

    United States

    SR 26-2 for Federal Reserve supervised institutions. NIST AI RMF as the cross-cutting organizing model. FDA PCCP for life-sciences regulated AI.

    Canada

    OSFI E-23 for federally regulated financial institutions. Mapped from the same evidence chain that satisfies SR 26-2.

    Global

    ISO/IEC 42001 as the certifiable AI management system standard.

    Industry-specific

    FDA PCCP for life sciences. FINOS AIGF for capital markets. SR 26-2 for banking. DORA for EU financial services. EU AI Act for any high-risk system regardless of industry.

    The engagement funnel

    What is the next step.

    Four stages. The Executive Assurance Briefing walks through the frameworks your function is on the hook for and the highest-risk gaps to address first. The Runtime Risk and Governance Assessment scopes the agents and workflows already in scope against those frameworks. Pilot proves runtime evidence at a fixed scope. Platform Rollout is where Reign goes into steady-state production. Most enterprises start at Stage 1.

    Schedule an Executive Assurance BriefingStart a Runtime Risk Assessment
    Or apply for a focused pilot →
    Six frameworks. Three geographies. One evidence chain.
    EU AI Act
    SR 26-2
    DORA
    NIST AI RMF
    ISO/IEC 42001
    FDA PCCP