No. Eudemonic AI is a decision-support and insight tool — not a diagnostic system. It does not diagnose mental illness, generate clinical assessments, or replace professional judgement. The platform helps institutions understand cohort-level patterns of academic stress and wellbeing, supporting better-informed institutional planning. All outputs require human interpretation and professional review before any action is taken.

The platform is designed with anonymisation as a central principle. Analytical outputs are produced at cohort level, not individual level, by default. Role-based access controls limit who within an institution can view different levels of data. Full data governance arrangements are agreed with each institution as part of the pilot and deployment process. The institution retains data controllership throughout.

Yes — and we actively encourage it. Eudemonic AI is available for structured pilot engagement, allowing institutions to evaluate the platform’s survey, analytics, and reporting outputs within a defined scope before committing to wider deployment. Pilot discussions include a review of the dashboard, survey instrument (under NDA where appropriate), and analytical methodology.

Eudemonic AI has been designed for the full range of UK educational institutions — including universities, further education colleges, schools, and multi-academy trusts. The platform’s survey and reporting framework can be contextualised for different student populations and institutional settings. We welcome enquiries from student wellbeing leads, safeguarding teams, academic quality teams, directors of student experience, and institutional research partners.

The full survey instrument is not published publicly — to protect the research integrity of the methodology and intellectual property. The survey methodology is research-informed and has been developed through academic collaboration. The full questionnaire is available for review as part of formal pilot discussions, typically under a non-disclosure agreement.

Dashboard configurations and reporting formats can be discussed as part of pilot and deployment planning. While the core analytical framework is standardised to maintain research integrity, the presentation of outputs — including which cohort segments, time periods, and wellbeing dimensions are prioritised — can be tailored to institutional needs.

Sensitive wellbeing data requires careful governance, and we take this seriously. The platform has been designed with UK GDPR principles in mind, has undergone professional software penetration testing, and is built around role-based access controls and cohort-level anonymisation. No automated safeguarding or disciplinary actions are generated. Human oversight is required at every stage.

Eudemonic AI has been developed through academic engagement with eight UK universities: Essex Business School (feasibility study), University of Brighton (ML model testing), Brunel University London (research and ASP.NET C# engineering), University of the Arts London (pilot study, 800+ students), London South Bank University (Streamlit dashboard framework), Manchester Metropolitan University via CDI (accelerator and penetration testing), Lancaster University via CDI (Figma UX/UI design), and UCL EdTech Labs (evidence-based validation for market readiness). These represent research engagement and innovation programme involvement — not formal endorsement, adoption, or certification.