Comply · International standards
ISO/IEC 23053:2022 — Framework for AI using ML
A framework for AI systems using machine learning.
ISO/IEC 23053:2022 establishes a framework and common terminology for describing AI systems that use machine learning — their components, functions, and lifecycle — providing a shared reference model that supports governance, documentation, and communication.
Who it applies to
Teams that need a standardized reference model and vocabulary for ML-based AI systems.
Key obligations
- Describe AI/ML systems using the standard framework
- Use consistent terminology for components and lifecycle
- Document system architecture and data flows
How Maetra maps agents to ISO/IEC 23053
Maetra's structured agent records and evidence align with the framework's components and lifecycle vocabulary. (Licensed standard — activated on demand.)
In practice, Maetra:
- Scans and fingerprints each agent. Discover reads the agent’s code — its tools, data access and sensitivity, actions, model, and environment — into an evidence-backed profile tied to the exact file and commit.
- Decides what applies. That profile determines whether ISO/IEC 23053 is in scope for the agent and which of its requirements apply.
- Auto-detects controls and surfaces gaps. Controls your code already satisfies are detected automatically from the scan; the rest become a clear list of gaps, each tied to the requirement and the evidence it still needs.
- Proves it and keeps it current. Close gaps with linked evidence or generated documents — reused across every framework the same control supports — and Maetra re-checks on each rescan and flags evidence that has gone stale.
Related frameworks
Prove ISO/IEC 23053 compliance with Maetra
Classify your AI agents once and Maetra maps them to ISO/IEC 23053 and every other framework it supports — generating the evidence and documentation, tracking gaps and deadlines, and sealing every decision in an immutable audit trail.