Policies and usage rules
We define clear criteria for data, users, tools, human approvals, and autonomy limits.
- Allowed and prohibited use
- Data classification
- Roles and responsibilities
- Human escalation
AI Governance
Operational governance for generative AI
We design policies, controls, traceability, and evaluation criteria so organizations can adopt AI without creating operational risk.
Governance is not a static document. It is how an organization decides which AI systems can be used, under which conditions, with what evidence, and with what human responsibility.
Deliverables
AI risk matrix
We map impact, probability, data exposure, operational dependency, and minimum controls per use case.
- Operational risk
- Data risk
- Reputational risk
- Compliance risk
Evaluation and traceability
We design metrics, test datasets, acceptance criteria, logs, and evidence for internal audit.
- Output evaluation
- Decision records
- Prompt versioning
- Approval evidence
Reference frameworks
NIST AI RMF
We use Govern, Map, Measure, and Manage as reference functions to structure risk and controls.
ISO/IEC 42001
We help prepare operations, evidence, and controls aligned with an AI management system; we do not certify ISO.
Real operation
We translate frameworks into workflows, owners, metrics, and limits that a team can sustain.