Product Design · AI · Climate Tech
The Challenge
As extreme weather events grow more frequent, most homeowners lack a clear, actionable plan for preparing their homes. Insurance is reactive. Government guidance is generic. And most digital tools exist in silos — a flood map here, an energy audit there, nothing that brings it all together around a person's actual home.
The challenge was to design a product that meets homeowners where they are: anxious, time-poor, and in need of a guide that speaks plainly about what to do, in what order, and why it matters for their specific property.
The Product
MAJA is an AI-powered home resilience app that helps homeowners assess climate risk, build a prioritized improvement plan, and track progress over time. Using a conversational AI interface, MAJA translates complex property and climate data into clear, personalized guidance — making resilience planning something any homeowner can actually act on.
The Approach
The product needed to earn trust fast. Climate risk is personal, and homeowners are skeptical of tools that oversimplify or alarm without context. The design approach focused on building credibility through specificity — using the user's actual address, property type, and local hazard data to make recommendations feel grounded rather than generic.
A conversational AI layer was designed to handle the complexity that traditional forms cannot — letting users describe their home in natural language while the system builds a structured resilience profile in the background. Each recommendation is tied to a specific project, cost range, and risk reduction benefit.
The Outcome
The outcome was a fully interactive prototype demonstrating the end-to-end homeowner journey: onboarding, risk assessment, AI-generated project recommendations, and a progress tracker. The GPT-powered chat interface was designed to feel like a knowledgeable friend rather than a form — asking good questions and surfacing the right information at the right moment.
The prototype validated core assumptions around user engagement and the willingness to share property data in exchange for personalized guidance, forming the foundation for a market-ready product.