Function
Evaluate system behavior
Assess behavior against stated criteria and document the evidence.
Studio / Area
Set constraints, examine behavior, and make accountability visible.
How is the system constrained, observed, evaluated, and held accountable?
Start with the outcome
Function
Assess behavior against stated criteria and document the evidence.
Function
Use a structured framework to identify, measure, and manage AI risks.
Function
Emit traces, metrics, and logs from a running system for later analysis.
Function
Toolkit for instrumenting systems and exporting traces, metrics, and logs.
Function
A voluntary framework for managing risks in AI systems.
Function
Collect signals that help explain what the running system did and where it failed.
Function
Identify and manage risks in the context of an AI system’s intended use.
Function
Identify spans or fields that may contain personal or other sensitive information.
Function
Use recognizers to find possible sensitive entities before review or masking.
Function
Open-source components for sensitive-data detection and anonymization.
Function
Run representative inputs and score application outputs against defined criteria.
Function
Open-source CLI and library for LLM application evaluation and red teaming.
Function
Record request-level model, retrieval, and tool steps as linked observations.
Function
Application tracing platform for LLM calls, retrieval, and tool steps.
Function
Developing conventions for recording generative-AI spans, metrics, and events.
Function
A cross-sectoral profile for applying the AI Risk Management Framework to generative AI risks.
Function
Evaluate request context against explicit policy to return a permission decision.
Function
Evaluate structured requests against declarative policy outside application business logic.
Function
Open-source engine that evaluates structured input against policy and returns decisions.
Representative paths
approach
Use a structured framework to identify, measure, and manage AI risks.
framework
A voluntary framework for managing risks in AI systems.
approach
Emit traces, metrics, and logs from a running system for later analysis.
implementation
Toolkit for instrumenting systems and exporting traces, metrics, and logs.
approach
Use recognizers to find possible sensitive entities before review or masking.
implementation
Open-source components for sensitive-data detection and anonymization.
approach
Run representative inputs and score application outputs against defined criteria.
implementation
Open-source CLI and library for LLM application evaluation and red teaming.
approach
Record request-level model, retrieval, and tool steps as linked observations.
implementation
Application tracing platform for LLM calls, retrieval, and tool steps.
standard
Developing conventions for recording generative-AI spans, metrics, and events.
framework
A cross-sectoral profile for applying the AI Risk Management Framework to generative AI risks.
approach
Evaluate structured requests against declarative policy outside application business logic.
implementation
Open-source engine that evaluates structured input against policy and returns decisions.
Across the Studio
Governance applies across every area, rather than as a final stage.
Last reviewed 2026-09-29