Change without effect review
A change enters the workflow without sufficient criteria for assessment.
MLOps and LLMOps
Set the operational controls your AI system actually requires
Structure controls for change, evaluation, traceability and accountability in AI systems.
Operational pain
Risks that emerge after first delivery
Incident without an owner
The team does not know who decides on reversal, communication or correction.
F.A.L method
Controls proportional to risk
- 01
Inventory operating assets
We identify components, dependencies, owners and change points.
- 02
Define review cycles
We establish criteria for changes and observed deviations.
Delivery
AI operating structure
Control matrix
Controls linked to risks and accountable decision owners.
Operating procedures
Routines for reviewing changes, evidence and exceptions.
Fit
When operational controls are needed
- AI already affects a recurring process
- More than one person or system changes the flow
- Risk requires review evidence and accountability
Frequently asked questions
Does MLOps guarantee compliance?
No. Controls help operate and evidence decisions; applicable obligations need contextual assessment.
Is it needed before every experiment?
The control level should match risk, scope and intended use.
Does your AI operation have the right controls?
Request fit triage to assess operational risk, ownership and necessary controls.