Docs

Appearance

AI Systems ​

AI Systems are the unit of execution in Modulos. An AI System defines a governance scope and contains the frameworks, Controls, Evidence, and monetary risk quantification needed to make that scope auditable.

What this is ​

An AI System is a boundary that keeps governance work consistent:

  • one scope statement an auditor can understand
  • one set of frameworks and Requirements that apply to that scope
  • one audit trail for Controls, Evidence, reviews, and risk decisions

AI Systems and the organization AI System ​

The AI Registry lists two kinds of entry, distinguished by Type: AI Application or Organization. They map to how compliance and audits work in practice.

AI Systems ​

An AI System governs one deployed AI system or use case in its real deployment context. The AI Registry lists it with Type AI Application.

An AI system is not just a model. It includes the full socio-technical system that produces and uses AI outputs.

AI system definitions

EU AI Act definition:

"AI system" means a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.

NIST AI RMF definition, adapted from OECD:

The AI RMF refers to an AI system as an engineered or machine-based system that can, for a given set of objectives, generate outputs such as predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy.

AI Systems are the default choice for frameworks that are system-scoped, such as the EU AI Act.

The organization AI System ​

One organization AI System holds organization-wide governance programs and management systems:

  • policies and processes that apply across teams
  • shared Controls that support multiple compliance programs
  • certification-style audits where scope is the organization, not one system

It is listed with Type Organization in the AI Registry and is the home of organization-scope frameworks (OFF-x) such as ISO 42001 and ISO 27001.

The AI Registry does not create new organization AI Systems; if your organization does not have one yet, contact Modulos support before rolling out organization-scope frameworks.

Where in Modulos ​

  • AI Registry → AI Systems to view all AI Systems and register a new one; AI Registry → My Submissions for the ones you registered, including Drafts
  • AI System → Overview for the registration record: intended purpose, EU AI Act classification, owners, state, scopes, and its own Comments and Logs
  • AI System → Dashboard to see progress and signals for one AI System
  • AI System → Graph to visually explore frameworks, Requirements, and Controls
  • AI System → Requirements, Controls, Evidence, Risks, Runtime Inspection to execute work inside an AI System
  • AI System → Settings to configure frameworks, user access, and Sources

Who can do what ​

Permissions

  • AI System Owners configure the AI System, assign AI System roles, and manage settings.
  • Editors implement Controls, attach Evidence, and keep work items up to date.
  • Viewers have read-only access focused on traceability.

Organization admins typically have full administrative access across AI Systems in the organization. Use AI System roles to grant the minimum needed access to non-admins and to preserve separation of duties.

How it works ​

AI Systems unify execution across governance areas: governance, risk quantification, and runtime inspection all live inside the same scope boundary.

That shared structure is what allows traceable exports and audit-ready reviews.

What lives in an AI System ​

Depending on your organization setup, an AI System may include:

  • frameworks, Requirements, Controls, and Evidence
  • risks and monetary quantification runs
  • runtime inspection Sources, tests, schedules, and results
  • assets and supporting documents
  • notifications and object-level comments and logs

How to use it ​

Important considerations ​

  • Keep AI Systems narrow. Registering one AI System per deployed system or use case keeps Evidence and risk quantification defensible.
  • Treat the AI System description as your scope statement. It should survive staff turnover and audit scrutiny.
  • Reserve the organization AI System for shared Controls and policies.
Register an AI System

Register an AI System and assign roles and frameworks

AI System Dashboard

Interpret progress signals and what is blocking completion

Compliance Graph

Visual map of frameworks, Requirements, and Controls

AI System Settings

Configure frameworks, access, EU AI Act scoping, and Sources