Luniby

Overview

Project Overview

Luniby is an AI-powered petcare platform designed to reduce clinic burnout, streamline triage, and improve pet wellbeing. The platform connects pet owners, veterinary nurses, and clinics in one intelligent ecosystem.

Problem

The Challenge

Clinic burnout, fragmented triage, and anxious pet owners create systemic pain points across the petcare ecosystem.

• Pet owners experience high anxiety (8.2/10 avg) during symptom discovery with no immediate reassurance
• Veterinary clinics spend 40% of consultation time on triage that could be pre-screened
• Multiple disconnected touchpoints create poor continuity of care
• No unified system connecting early detection, triage, and follow-ups

Goals

Design Goals

• 1Design clear, guided triage experience for anxious pet owners
• 2Create actionable Health Notes system for clinic staff to reduce triage burden
• 3Orchestrate multi-user experiences across owners, nurses, and clinics
• 4Build trust through transparent AI reasoning and empathetic design
• 5Establish continuity of care from triage to consultation to follow-ups

Research

Research Summary

Conducted comprehensive research across multiple stakeholder groups to understand systemic pain points:

Insights & Pain Points

What We Learned

“My dog started limping and I panicked — is it an emergency or can I wait? I called three clinics and they were all fully booked. I just needed someone to tell me if this was urgent.”

— Jessica T., 28, Pet Owner (Auckland, December 2024)

Key Insights

• Multiple user types require orchestrated experiences: Anxious owners need clarity and reassurance, clinics need actionable data
• High anxiety during symptom discovery: Pet owners experience 8.2/10 average anxiety, creating demand for immediate guidance
• 40% of clinic time spent on pre-screenable triage: Time-motion study showed significant efficiency opportunity
• Early detection builds trust: Pilot testing showed 28% reduction in non-urgent bookings
• Empathy-driven UX reduces anxiety: A/B testing showed empathetic language reduced anxiety by 34%

User Flow Diagram

User Journey Mapping

Mapped complete user journeys across three user types: pet owners, veterinary nurses, and clinic administrators. Flow shows: Symptom entry → AI triage assessment → Health Notes generation → Clinic integration → Consultation booking → Follow-up care

Information Architecture

Structural Design

Wireframes

Low → Mid Fidelity

Design Decisions

Key Design Choices

Final UI Screens

High-Fidelity Designs

Accessibility + Usability

Inclusive Design Decisions

• WCAG 2.1 AA Compliant: All text meets contrast requirements, tested with screen readers
• Large Touch Targets: Minimum 44×44px for all interactive elements (tested on 5 device sizes)
• Clear Error States: Helpful error messages with recovery actions
• Offline Capability: Service worker caching ensures access during emergencies
• Keyboard Navigation: Full keyboard support for all interactions
• Simple Language: Flesch-Kincaid Grade Level 8 for all user-facing text
• Progressive Disclosure: Complex information revealed gradually to avoid overwhelming users

Outcome & Learnings

Impact & Reflection

Key Learnings

• Multi-user design requires orchestration: Each user type needs distinct experiences while sharing data seamlessly
• Empathy reduces anxiety: Supportive language and clear guidance measured 34% anxiety reduction
• Co-design with stakeholders is essential: 6 workshops with nurses produced far better Health Notes design than solo iteration
• B2B validation shifted strategy: Clinics preferred embedded API over standalone platform — pivoted roadmap accordingly
• Transparency builds trust in AI: Showing confidence levels increased user trust scores from 6.2 to 8.7