Overview
I created an AI-driven Chrome extension that helps people who are moving to NYC for the first time easily access trustworthy neighborhood insights without switching tabs. Built through vibe coding and Gen AI tools, the extension consolidates scattered information from rental contracts to community safety into a clear, accessible experience.
My Role
Duration
3 Months
Team
1 Product Designer
1 Motion Designer
Tool
Figma, Figma Make, Cursor, Base 44, Chat GPT, Google Map/Places API, Open AI API, Reddit API
Highlight
Helping NYC newcomers make confident moving decisions with AI-powered insights that turn scattered data and local knowledge into clear, trustworthy answers.
Overview
Impact
13
97%
Reduced API costs by 97% through prompt optimization and backend caching.
300+
Covers 300+ neighborhoods in all 5 boroughs in NYC with AI-powered local insights.
Discover
Background
Research Insights
Too much data, no clarity. People can’t synthesize 20 tabs of scattered info.
Cultural and language barriers block access
Raw numbers fuel fear; users need context to interpret safety confidently.
A person moving to NYC for the first time
Strategy & System Thinking
Design Principles
Connecting to NYC Open Data & Reddit for factual trust.
Explaining data with visual and readable charts and everyday language.
Visuals meet WCAG AA color contrast, with readable typography.
Making the experience feel instant and reliable.
Design Exploration
Designing For Clear And Bite-Sized Neighborhood Data
I explored several layouts for presenting live neighborhood data on the Find Area, focusing on clarity and scanability. Each direction had trade-offs, so I validated them through quick user testing and design critiques to understand which version actually helped people interpret the information faster.
Deliverables
Find Where to Live. No Guesswork, Just Data
Users can discover NYC neighborhoods that fit their budget, safety preferences, and commute time.
They can search by specific neighborhoods or addresses to get instant, data-driven results powered by Open AI, NYC Open Data, Google Maps and reddit communities.
Each result visualizes safety scores, rent, noise levels, and commute times, allowing users to filter, compare, save neighborhoods, and set alerts for issues they want to track.
Users can ask anything about moving or living in New York, from cafes and gyms to commutes and neighborhood vibes, and get precise, real-world answers. Responses stream in real time and sound conversational, like chatting with a local who knows every corner of the city.
The Budget Tool gives users an honest view of what they can actually afford. Calculate by income or rent using NYC’s 40x rent rule ($75K = $1,875/mo). It also shows guarantor requirements (80x rule), rent-to-income ratio, and introduces third-party guarantor options common in NYC.
No sugar-coating, just clear numbers based on real rental standards.
Real NYC Conversations, Organized
The Community section pulls live posts from NYC-focused subreddits. Users can filter by living situation or keywords to find relevant discussions from real residents, just honest advice and shared experiences.
Reflection
Takeaways
Designing Get Set NYC reinforced how important clarity is when people are making high-stakes decisions. Improving hierarchy, refining how safety is visualized, and restructuring AI responses noticeably increased trust and comprehension. Small details such as a clearer address interaction or a calmer budget layout also made users feel more confident using the product.
What I learned
Check API costs early, tune AI carefully, and test small interactions often. These details shape whether a product feels trustworthy.
