Illustrative workspace
University AI governance
The control
layer for
university AI.
RedAPPL helps universities shape how AI works across institutional, course, and assignment contexts—while keeping instructor intent and student learning in view.
- Assignment-level control
- Institutional governance
- Built for higher education
RedAPPL GovernanceSample workspace
Use cases
Built for every layer of the university.
Illustrative workspace
Illustrative workspace
Institutional visibility
Create a clearer view of how AI is configured across the institution.
Learn moreWhy RedAPPL
Built by students. Informed by educators.
RedAPPL began with firsthand student experience of how AI is changing education. The product direction is being informed through conversations with educators and higher-education stakeholders.
The goal is straightforward: make AI genuinely useful while preserving instructor intent and the conditions for meaningful learning.
Our StoryFrom intent to experience
- 01Instructor Intent
- 02Assignment Policy
- 03AI Behaviour
- 04Student Learning
Governance by design
Built for institutional control.
Universities need more than access to AI. They need a thoughtful way to govern how it is configured and used.
Institutional Controls
Configure AI behavior across appropriate institutional, course, and assignment contexts.
Data Boundaries
Keep relevant context inside intentionally governed workflows.
Model Flexibility
Support institution-approved AI providers as requirements evolve.
Auditability
Create clearer visibility into how AI is configured and used.
Shape what comes next
Help shape the future of university AI.
RedAPPL is looking for educators and institutions interested in shaping responsible AI adoption and future pilot workflows.