Model Lifecycle
14 resources in this section
AI Agent Measurement — Evaluation Beyond Model Testing
Definición técnica AI agent measurement refers to the systematic evaluation of agentic AI system behavior, performance, safety, and compliance — going beyond the testing of individual models to…
AI Robustness — Resilience Testing and Requirements for AI Systems
Definición técnica AI robustness refers to the ability of an AI system to maintain its intended performance and behavior under a range of challenging conditions — including noisy…
AI Safety — Technical and Governance Requirements for Safe AI Systems
Definición técnica AI safety refers to the set of technical and governance measures ensuring that AI systems behave as intended, do not cause unintended harm, remain within operational…
Audit Trail — Traceability and Accountability in AI Systems
Definición técnica An audit trail in AI systems is a chronologically ordered, tamper-evident record of events, decisions, and actions taken by or involving an AI system — sufficient…
Continuous Assurance — Ongoing AI Governance Monitoring
Definición técnica Continuous assurance in AI governance refers to the ongoing, systematic process of monitoring and evaluating AI systems and governance controls in real time or near-real time,…
Hallucination: where the model confuses fluency with truth
Hallucination is structural to generative AI, not a bug. Zertia audits mitigation controls under ISO 42001 + EU AI Act Articles 13 and 14.
Model Card — Standardized AI Model Documentation for Transparency
Definición técnica A model card is a structured documentation artifact that provides concise, standardized information about a machine learning model: its intended use, performance characteristics, evaluation results across…
Model Drift: where documented performance stops matching operational reality
Model drift produces silent AI failures over time. Zertia audits drift detection under ISO 42001 + EU AI Act Article 72.
Model Interpretability — Understanding AI Decision Mechanisms
Definición técnica Model interpretability refers to the degree to which the internal mechanisms of an AI model can be understood by humans — specifically, the extent to which…
Model Lifecycle Management — Governance Across the AI Model Pipeline
Definición técnica AI model lifecycle management is the structured governance framework that oversees an AI model from its initial conception through development, validation, deployment, operation, monitoring, retraining, and…
Model Testing — Comprehensive AI System Evaluation Requirements
Definición técnica Model testing in AI systems is the systematic process of evaluating AI model performance, behavior, robustness, fairness, and safety against defined criteria before deployment and throughout…
Model Validation — Pre-Deployment AI System Evaluation
Definición técnica Model validation is the structured process of evaluating whether an AI model meets its intended purpose, performs within acceptable parameters, and is suitable for deployment in…
Post-Market Monitoring — Ongoing AI System Compliance Surveillance
Definición técnica Post-market monitoring (PMM) is the systematic, ongoing process of collecting, documenting, and analyzing data about the performance, reliability, and behavior of AI systems after they have…
Technical Documentation — EU AI Act Annex IV Requirements
Definición técnica Technical documentation, in the context of the EU AI Act, refers to the comprehensive set of documents that providers of high-risk AI systems must prepare and…
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