Overview
GARY is an AI-powered aging-in-place ecosystem built at an international hackathon. It helps older adults remain independent in their own homes by translating everyday mobility and safety signals into concrete, prioritized home-improvement recommendations for the resident, their family, and their care network.
Problem
Aging-in-place is the preference for most older adults, but families and caregivers lack a structured way to know which home modifications actually reduce risk, in what order, and at what cost, decisions are often reactive, made only after a fall or health scare.
Solution
GARY combines a lightweight in-home assessment with an AI recommendation engine that prioritizes modifications by risk reduction and cost, and coordinates the resident, family, and service providers through one shared plan.
My Role
Product & strategy lead. I designed the service blueprint, stakeholder ecosystem, and implementation strategy, and shaped how the prototype communicated recommendations to non-technical users.
Process
- 01
Stakeholder mapping
Mapped residents, families, caregivers, and service providers to understand incentives and friction points.
- 02
Service blueprint
Designed the end-to-end service blueprint from initial assessment to completed home modification.
- 03
User journey
Detailed the resident and family journey to identify moments that needed the most trust-building.
- 04
Prototype
Built a working prototype demonstrating the AI recommendation flow.
- 05
Roadmap
Defined an implementation strategy and roadmap for post-hackathon development.
Deliverables
- , Service blueprint
- , Stakeholder ecosystem map
- , User journey map
- , Interactive prototype
- , Implementation roadmap
Results
International hackathon
Format
Aging-in-place / HealthTech
Focus
“GARY pushed me to design for a user I don't share a generation with, the biggest unlock was treating the family and caregiver as co-users of the product, not just the older adult.”
