Turn AI risk into an architecture teams can implement.
AI Patterns connects system analysis, implementation-grade patterns, control placement and evidence so architecture and governance teams can move from policy intent to a governed design.
Which AI systems need an architecture decision?
Prioritise systems by material risk, regulatory obligation, sensitive data, autonomy and control gaps—then see the patterns and decisions required to make them governable.
One chain from system risk to implementation control.
Start with the system architecture and obligations. Select the implementation pattern, place the control, assign ownership and keep the required evidence connected to the governed target state.
Know what proves the control—not just what the policy says.
Obligations, patterns, control decisions and evidence stay connected so reviewers can trace why a control exists, where it belongs and what demonstrates that it is implemented.
See the evidence model →Bring one real AI system.
Start with one material AI use case or architecture. Use AI Patterns to turn it into a defensible target design, control set and evidence chain before considering estate-wide adoption.
About AI Patterns →