Kaivex AI Governance Framework.
Governance only works when it shows up in the operating cadence. Six pillars, the artifacts each one owns, and the meetings that make them real — designed for organizations that want responsible AI without grinding delivery to a halt.
Risk
Classify, contain, and rehearse the things that can go wrong.
Artifacts owned
- Risk taxonomy by use-case class
- Tiered review thresholds
- Failure-mode register & playbooks
Security
Treat AI systems as production software with adversarial inputs.
Artifacts owned
- Secrets & identity standards
- Prompt-injection & data-exfil controls
- Threat-model review per system
Compliance
Map systems to obligations and prove it under audit.
Artifacts owned
- Regulatory map (EU AI Act, sector regs)
- System cards & model documentation
- Evidence trail for decisions
Human Oversight
Make human review explicit, instrumented, and respected.
Artifacts owned
- Review-in-the-loop design per system
- Override and escalation rules
- Kill-switch authority & rehearsal
Data Privacy
Govern personal and sensitive data across the AI lifecycle.
Artifacts owned
- Lawful-basis mapping per use case
- Minimization & retention policy
- Vendor data-processing review
Ethical AI
Decide what the organization will and will not build.
Artifacts owned
- Use-case acceptance criteria
- Bias evaluation & mitigation plan
- Stakeholder & customer impact review
Governance lives in the calendar.
A policy is a document. A cadence is a habit. These are the meetings every Kaivex governance engagement stands up — with the right authority in each room.
Risk classification + governance gate before funding.
Operational review of incidents, drift, and escalations.
Portfolio review with sponsors — outcomes, cost-per-outcome, sunsetting.
Policy calibration, regression evaluation, and audit pack refresh.
Stand up AI governance that delivery teams respect.
A four-week engagement to define the pillars, the cadence, and the authority lines — and rehearse the first incident before it happens.