Developed through academic collaboration and innovation engagement
Eudemonic AI has been developed through sustained academic collaboration with eight UK universities — spanning feasibility research, machine learning model testing, software engineering, an 800+ student pilot study, visual dashboard design, UX/UI development, software security testing, and evidence-based market readiness validation.
Selected academic collaboration, pilot, and innovation programme engagement — logos are placeholders pending institutional permission. Engagement does not imply endorsement, adoption, or certification.
University of the Arts London
Pilot-informed development drawing on 800+ student responses — demographic analysis, academic stress reporting, open-ended question metrics, and K-means ML cluster analysis. Academic reports produced alongside data collection.
Essex Business School
Early-stage feasibility analysis evaluating the product concept, market context, and viability of AI-supported student wellbeing as an institutional decision-support tool.
University of Brighton
Testing and refinement of the machine learning model underpinning stress pattern detection and cohort classification within the platform’s analytical engine.
Brunel University London
Software engineering of the student survey in ASP.NET C#, alongside academic research contributions informing the survey’s design, structure, and theoretical underpinning.
London South Bank University
Streamlit-based visual dashboard framework designed around student wellbeing data — including a 119-student dataset from Rai University, India — informing cross-context dashboard design.
Manchester Metropolitan University
Concept maturation through the CDI accelerator programme — including professional software penetration testing to underpin the platform’s security assurance framework.
Lancaster University (CDI)
UX and UI design collaboration via Lancaster University’s CDI, using Figma to evolve the student-facing survey experience from functional form-filling toward guided, reflective interaction.
UCL EdTech Labs
Evidence-based validation research through UCL EdTech Labs — contributing to market readiness assessment, evidence requirements, and responsible EdTech commercialisation framework.
Shaped by real student data from a structured field study
A foundational element of Eudemonic AI’s development was a structured pilot study at the University of the Arts London — one of the UK’s leading creative higher education institutions.
The pilot generated a dataset of over 800 students, encompassing demographic analysis, academic stress reporting, open-ended qualitative responses, and K-means machine learning cluster analysis. Academic reports were produced alongside the data collection process.
The insights directly informed the platform’s survey structure, analytical methodology, reporting framework, and usability direction — providing a rigorous, student-grounded basis for product development rather than theoretical assumption.
This engagement represents pilot-informed product development. It does not constitute formal adoption, endorsement, or institutional deployment by the University of the Arts London.
Designed for guided reflection, not clinical form-filling
The student-facing survey experience has been significantly strengthened through UX and UI design collaboration conducted via Lancaster University’s Centre for Digital Innovation (CDI).
Using Figma, the CDI design engagement evolved the student experience from a functional data-collection form toward a carefully structured, guided reflective journey — one that feels supportive and purposeful rather than transactional or clinical.
A thoughtfully designed experience improves response rates, increases response depth, and reduces anxiety around sensitive wellbeing questions — directly improving the quality of institutional insight.
Figma-Led UX/UI Prototyping
Professional interface prototyping and usability-tested design flows developed through Lancaster University’s CDI engagement.
Guided Reflection Framework
Survey questions are contextualised and sequenced to support honest, reflective responses rather than performative or rushed answers.
Accessibility-Conscious Design
Inclusivity and accessibility are central to the student experience — ensuring the survey is welcoming across diverse student populations.