Racehorse health monitoring, built from scratch with AI-assisted domain research. High fidelity in a completely unfamiliar domain.
High-fidelity prototype delivered in an unfamiliar domain. Client reaction exceeded expectations. They described the session as leaving them speechless.
VitalHoof came to IVI with an idea for a racehorse health monitoring application. The brief was to design a mobile-first platform for trainers and vets to track equine health data (vitals, exercise history, treatment records, and session notes) in one place.
I had no prior knowledge of equine health, racehorse training, or the workflows of trainers and vets at racing yards. Before I could design anything, I needed to understand the domain: who the users were, how they worked, what data mattered to them, and what the stakes of getting it wrong looked like.


I used AI-assisted research to rapidly build domain knowledge, pulling together veterinary terminology, training terminology, and the mental models of equine health professionals. This gave me enough context to design with credibility, even without direct access to users in the industry.
From there, I built an information architecture that organised the app around what matters most to a trainer at the start of a training day: the current health status of each horse, recent sessions, and any flags raised by the vet. The design prioritised scanability over depth. Most users would be checking in quickly, not doing detailed analysis.


The high-fidelity prototype was delivered within the IVI project timeline. When presented to the client, their reaction was one of the strongest I've had in this role. They described it as leaving them speechless. The depth of domain knowledge embedded in the design, built in a matter of weeks with no background in the field, is what I think landed hardest.
10 interviews, two user types, one prototype that landed in an investor pitch deck.
Read case study → 03A new feature for a 3-year-old product, designed and shipped in one week.
Read case study → 04Research that reframed the problem before design could begin.
Read case study →