Wildfires are growing more severe, and the people caught in the middle—homeowners, insurers, and fire professionals—need better tools to manage risk.
My role
As Perch’s founding product designer, I led the end-to-end design process during a pivotal product shift. I translated raw research into product direction, defined the platform’s structure, and designed a lo-fi prototype—all while collaborating closely with the algorithm team as the data model evolved.
Wildfires are becoming more severe.
Insurance policies are being cancelled.
Perch began as a wildfire detection sensor startup, but after years of research, the team realized the space was saturated. By the time I rejoined the team in 2024, it was clear that space had matured — the technology worked, but the real problem hadn’t been solved.
Homeowners across California were being dropped from their insurance plans without warning, insurance companies were relying on outdated wildfire risk models, and fire departments lacked the tools to model how fires would move through communities.
Everyone was operating with incomplete information.
Helping people act on wildfire risk — not just observe it.
We decided to pivot. Perch is now building a wildfire risk analysis platform — a SaaS product that helps insurers, homeowners, and fire departments assess property-specific risk using a layered scoring system.
Our platform breaks risk into three major categories, each with sub-factors and supporting data points:
Predict
Use structure-level data to predict fire risk before it spreads
Prevent
Get tailored recommendations homeowners can act on now
Protect
Support safer communities with shared data and clear priorities
The process
Pivoting from sensors to software
I joined just as the team was defining this new direction. I began by reviewing existing interview recordings and joining new ones across all user groups. Throughout this process, I:
Synthesized themes
Shared insights with the team
Helped shape the product strategy.
Designing without a finished product
While our data science team worked to develop the algorithm that would drive the platform, I was designing the interface that would present its results. That meant building layouts, hierarchies, and interaction patterns without knowing exactly what the final data would look like.
To manage this uncertainty, I focused on:
Flexibility in structure — designing layouts that could scale with evolving outputs
Tight collaboration with the algorithm team — checking in frequently to align on direction and assumptions
Rooting every design decision in user needs — ensuring clarity and actionability for both technical and non-technical users
Lessons from designing in motion
Take ownership early
In a fast-moving startup, no one’s handing you a roadmap—you have to make one.
Use what you have
Even without finalized data, I found ways to prototype, test, and move forward.
Stay flexible
Working alongside an evolving algorithm meant every layout needed to continuously adapt.
What’s ahead for Perch
We’re now gearing up to test the prototype with fire professionals and insurance reps to validate comprehension and utility. Their feedback will help shape our next iteration and inform the high-fidelity designs we’ll use for pitching and piloting.