Comply · International standards
ISO/IEC 5338:2023 — AI system life-cycle processes
AI system life-cycle processes.
ISO/IEC 5338:2023 defines the life-cycle processes for AI systems, extending established software and systems-engineering lifecycle standards to address AI-specific activities such as data management, model training, evaluation, and continuous operation.
Who it applies to
Engineering and governance teams that want a rigorous AI system lifecycle process model.
Key obligations
- Apply defined lifecycle processes to AI systems
- Manage data, training, evaluation, and operation stages
- Maintain traceability across the lifecycle
How Maetra maps agents to ISO/IEC 5338
Maetra preserves versioned history and evidence across discovery, classification, and operation — traceability that maps to the lifecycle processes. (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 5338 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 5338 compliance with Maetra
Classify your AI agents once and Maetra maps them to ISO/IEC 5338 and every other framework it supports — generating the evidence and documentation, tracking gaps and deadlines, and sealing every decision in an immutable audit trail.