Platform / RiGi Group
AI Auditing
Capture a reviewable decision trail for investigation, replay, and oversight.
WWAIOS / AI Auditing
The role of ai auditing in a governed workflow
Capture a reviewable decision trail for investigation, replay, and oversight.
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Capabilities
What the layer is designed to handle
Support reconstruction of how a decision was reached.
Export scoped records for authorized review.
Operating pattern
A control path you can inspect
- 01Define the input, context, and authorized purpose.
- 02Preserve key inputs, control versions, actions, and outcomes.
- 03Support reconstruction of how a decision was reached.
- 04Capture the result, exception, and owner for review.
Questions for architecture review
What would change your decision?
Ask which evidence is current, which control actually executes, who owns an exception, and where a human must approve an action.
Explore
Adjacent layers
AI HarnessBind model interactions into a defined runtime with shared controls and observable behavior.↗AI Decision EngineDescribe decision paths, policy conditions, and approval points as explicit workflow rules.↗AI GuardrailsApply runtime checks around sensitive data, unsafe requests, and output constraints.↗AI Knowledge BaseConnect retrieval to governed sources so answers can point back to what supports them.↗
A closer look / AI Auditing
From question to evidence to decision.
Use this framework to discuss the actual workflow and the proof needed to move forward.
01 / Situation
A decision trail that cannot be reconstructed is of little use during an incident or review.
02 / Approach
Capture bounded events for input, context, versioned controls, tool effects, approvals, and outcomes with access controls.
03 / Evidence
Reconstruct a sampled run and show what is observed, inferred, unavailable, or intentionally excluded.
04 / Next decision
Set retention, access, redaction, and export rules with the relevant data owner.