AI Governance
AI features on CampusWay are designed to be useful, bounded, and supervised. This overview describes how we approach responsible AI in an enterprise context.
Design principles
- AI features are grounded on institution-approved content
- Scope and tone are configurable by administrators
- Human oversight is available where it matters
- AI is a supplement, not a replacement, for institutional voice
Data handling
AI features respect the same data minimization principles as the rest of CampusWay. Institution content used to ground AI features is treated as institutional data.
We do not use customer data to train foundation models. Where third-party AI services are used, we select vendors that meet our enterprise expectations and disclose them to customers under standard practice.
Guardrails
- Topic, tone, and escalation controls
- Auditable response history for administrators
- Rate and abuse protections
- Continuous evaluation of model outputs against institutional expectations
Human oversight
AI features can escalate to human staff, defer sensitive topics, and hand off to institutional resources. Administrators can review activity, tune scope, and disable features at any time.
AI is deployed to save time and reduce friction — never to replace judgment where judgment matters.
Explore CampusWay with our team.
Request a prototype demonstration or apply to the pilot program. We work directly with a small number of forward-thinking institutions as the platform matures.