Governance only works when it is easier to follow than to ignore. We translate policy intent into workflow-level guidance: what is in bounds, what needs review, and how to escalate when uncertainty hits. Proportionate means different rules for different risk contexts — not one undifferentiated rulebook that teams work around.
How we typically help
- ·Responsible use policy design
- ·Workflow-level governance integration
- ·Risk boundary definition and escalation design
Outcomes we work toward
- ·Policies and guardrails people actually reference in daily work
- ·Clear escalation paths that reduce “shadow” AI use
- ·Audit-ready traceability without paralysing innovation
How engagements typically run
Engagements often combine legal, risk, IT, and business stakeholders in working sessions so governance is co-owned, not dropped on one function.
Example engagements
Representative situations where organisations apply this service — patterns we see across sectors and geographies.
- ·Tiered model: low-risk drafting assist vs. high-risk decisions requiring human sign-off and logging.
- ·Partner with legal to turn “no training on client data” into concrete tool configurations and DLP rules.
- ·Incident playbooks when a model outputs protected data — who gets paged, what gets preserved.
Indonesia and ASEAN context
OJK-supervised fintech with Bahasa and English customer traffic
Marketing wants fast gen-AI for campaigns; compliance needs traceability and PII handling aligned with local expectations. We co-create a short responsible-use guide in Indonesian for front-line staff, map which prompts require legal pre-check, and define retention and escalation aligned with your risk appetite — so teams stop using personal ChatGPT accounts for regulated work.