← AI Strategy & Implementation
Overview
Governance isn’t bureaucracy for its own sake - it’s how you keep AI from becoming an unowned production system. Clear policies make it obvious what data may enter a model, who approves high-stakes outputs, and what you log when a customer complains.
Where this helps
- Regulated or risk-aware industries needing defensible processes, not vibes
- Leaders rolling out AI to customer-facing channels
- Security and IT asked to “allow AI” without a definition of allowed
What we focus on
- Data rules - Classification, redaction, retention, vendor subprocessors
- Human review - When it’s mandatory; UX that makes review feasible at scale
- Safety patterns - Prompt injection awareness, tool allowlists, output filtering where appropriate
- Incidents - Detection, rollback, communication templates
How we work
We meet you where you are - light-weight policies for internal pilots, deeper controls before external launch. Governance pairs with strategy and implementation so rules map to actual system behaviour.