KnowhowyourAIisbehaving
AsAImovesintobusinessprocesses,oversightneedstomovewithit.Ushyakuhelpsorganizationsestablishtheownership,evaluationandoperationalcontrolsneededtodeployandmanageAIwithcleareraccountability.
Turnpoliciesintodecisionsyourteamscanapply—andevidencetheycanreview.
KeepresponsibilityvisibleasAIexpands
An inventory of models is useful, but it does not explain who approves a use case, what an acceptable failure rate looks like or when a release should be stopped. Those decisions need to be made before issues become incidents.
We help translate organizational expectations into practical controls across AI design, release and operation. The work connects product owners, engineers and risk stakeholders around documented responsibilities, meaningful evaluations and an agreed response when performance changes.
Frompolicytoproductioncontrols
Use-case and risk assessment
Document intended use, affected users, data dependencies and potential failure consequences to inform proportionate oversight.
Evaluation and release gates
Define task-specific tests and acceptance criteria, including quality, security and fairness considerations where they apply.
Access and safeguards
Implement appropriate tool permissions, data controls, review checkpoints and defenses against identified misuse patterns.
LLMOps and monitoring
Track model, prompt and configuration changes, monitor production behavior and support rollback, investigation and improvement.
Governanceyourdeliveryteamscanuse
Clear ownership
Responsibilities for approval, monitoring and incident response are assigned rather than left between teams.
Controls that match the use
Oversight reflects the application's role and consequences instead of applying the same process everywhere.
Evidence at decision points
Evaluation results and change records support practical release and operational decisions.
Ongoing attention
The approach accounts for new data, changed models and shifting usage after the first deployment.
PracticalusecasesforAIGovernance
AI portfolio oversight
Document use cases, owners and assessment requirements across departments.
Release assurance
Assess a proposed model or prompt change against agreed acceptance criteria.
Operational review
Investigate a decline in quality and identify corrective action or rollback.
FrequentlyAskedQuestions
Make your next AI release easier to account for
Review a planned or existing AI application and identify the controls, evidence and ownership needed to operate it responsibly.
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Managed Support
Connect AI monitoring with application operations and incident response.
Explore Managed Support