TA-14 AI Governance Exchange
GovernanceBefore Execution
Build the route. Prove the evidence. Bind the authority. Test the controls. Preserve the determination. Then, and only then, permit execution.
Main entrances
Choose how you want to govern
Architecture Library
Explore every registered AI governance architecture, including runtime execution, model evaluation, data provenance, agent tools, human oversight, policy controls, risk, decision, compliance, security, and outcome assurance.
Open library
Governance Playground
Test a governance route against evidence, authority, scope, controls, dependencies, intervention, execution, outcome, and replay requirements.
Enter playground
Build a Route
Create a bounded governance route before execution and preserve the exact claim, evidence, authority, controls, determinations, and conditions.
Build a route
My AI Routes
Return to saved governance routes, preserved runs, replay packages, determinations, and continuing-validity records.
View my routes
Architecture entrances
Test the exact governance layer
Runtime Execution
Govern the boundary where an approved decision becomes a consequence-bearing action.
Model Evaluation
Test model identity, evidence, thresholds, limitations, change, and deployment conditions.
Data Provenance
Trace source, custody, transformation, authority, quality, and downstream reliance.
Agent and Tool Governance
Govern delegated authority, tool calls, permissions, side effects, intervention, and receipts.
Human Oversight
Test meaningful review, intervention, stop authority, escalation, and accountability.
Policy and Controls
Bind policy claims to enforceable rules, controls, evidence, testing, and execution behavior.
Governing chain
Reality → Record → Continuity → Admissibility → Binding → Commit → Execution → Outcome
The Exchange does not treat governance as a policy document placed beside execution. It makes governance inspectable at the exact point where evidence, authority, controls, and decisions become real-world action.
Start with the question you need to prove
From AI governance question to inspectable execution evidence
You do not need to adopt TA-14 terminology before examining a consequential claim. Start with the problem in plain language, inspect the evidence boundary, then decide whether a bounded professional examination is warranted.
AI execution evidence
What evidence supports what the system was allowed to execute, what actually executed, and what outcome followed?
Examine the question →
AI agent audit trail
What should an agent audit trail prove beyond ordinary logging?
Examine the question →
AI agent authorization
Can you prove this specific agent action had valid authority when it executed?
Examine the question →
Changed authorization
What happens when approval or authority changes before consequence?
Examine the question →
Logs vs execution evidence
When are logs useful evidence, and what may they still fail to establish?
Examine the question →
Proof of blocking
Can you prove a protected consequence was actually prevented rather than merely denied on one path?
Examine the question →
Across the Exchange
Continue into the governance infrastructure
Governed Records
Build, upload, interpret, review, preserve, and export governed records.
Open →
AI Governance Registry
Review dated, attributable, challengeable architecture and governance records.
Open →
EU AI Act
Test provider and deployer obligations against evidence and execution routes.
Open →
Marketplace
Post a need, locate governance capabilities, and connect bounded work to qualified providers.
Open →