Budgie On A Budget

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Inspiration

We were inspired by how overwhelming and fragmented the moving process can be. When someone is looking for a new place to live, finding an affordable home is only the first step. They also have to consider things like the cost of living, neighborhood safety, accessibility, transportation, nearby amenities, and whether there are activities and events that match their interests. We realized that this information is often spread across different websites and platforms, forcing people to piece everything together themselves. We wanted to bring these pieces into one place, leading us to create Budgie on a Budget.

What it does

Budgie on a Budget is a housing and neighborhood discovery platform designed to make moving easier and more affordable. Users can explore neighborhoods based on their budget, lifestyle preferences, and location, while also discovering nearby events and community activities. Our goal is to make relocation feel less stressful, more personalized, and more community-focused by helping people find not just a place to live, but a place where they can feel at home.

How we built it

To create the map and neighbor-matching engine, we developed the front end using React and Vite, leveraging the @vis.gl/reac-google-maps library, which enables the rendering of an interactive Google Map, consisting of unique markers and information windows. The core experience of this project is powered by the Google Maps JavaScript API for the map, the Google Places API for the location search and finding nearby amenities, and the Google Routes API for the actual travel times between the user's workplace or school and nearby ZIP codes. In order to provide the neighborhoods with more content, we also integrated the Ticketmaster Discovery API for the real events happening in the neighborhood, the RentCast API that provides live listings of rentals or houses for sale, and the Google Gemini API to make automatic comparisons between the listings.

Because quite a few of these APIs need secret keys that cannot be revealed to the web client, we created a small Node.js and Express backend to safely relay calls to Google Routes and RentCast, which also includes an in-memory cache for commute times and a long-term cache for RentCast listings to stay within the limits of its free requests. Apart from the live APIs, we also converted some public data sets into lightweight JSON files that the application can load in no time: the US Census Gazetteer for zip code coordinates, NCES public school records for school counts of each ZIP code, county health rankings report (as this was combined with census ZIP-to-county cross-reference) for safety score calculation, etc.

Challenges we ran into

Syncing multiple APIs (Ticketmaster, Zillow housing dataset, Google Routes, and Gemini AI) onto a live Google Map was challenging because the data formats didn't match. Public geocoding APIs also frequently returned P.O. Boxes instead of real residential neighborhoods, which we solved by combining Gemini AI with OpenStreetMap reverse-geocoding to power our map and ElevenLabs voice advisor.

Accomplishments that we’re proud of

We are particularly proud of deploying a fully interactive map powered by real-time data from multiple live APIs, giving users an immediate, verified look at neighborhood rent, safety, and commute conditions. We pushed beyond our original scope by designing a community platform and a specialized AI assistant that helps local small businesses publish and spotlight their events for newcomers. Above all, our team takes pride in the hours of debugging and cross-environment problem-solving that turned technical hurdles into an adaptable, polished relocation product.

What we learned

During this project, we learned how to integrate existing housing and state tax datasets directly into an interactive web application and live map interface. We also learned how to implement AI safely and responsibly, using strict prompt guardrails, structured JSON validation, and environment key security, so that Gemini AI and ElevenLabs work reliably alongside our Google Maps, Ticketmaster, RentCast, and OpenStreetMap APIs without hallucinating data or exposing credentials.

What’s next for Budgie On a Budget

Next for Budgie On a Budget, we plan to launch a Side-by-Side Property Comparison tool that lets users compare two specific homes or apartments in their target state across rent, square footage, commute times, and utility costs. We also plan to integrate K–12 School District Ratings directly onto our interactive map to help families evaluate local education quality. Finally, we want to expand Alberdy with a Moving Day Mileage & Truck Cost Estimator and an AI Hidden-Fee Scanner that detects extra lease expenses like HOA dues, parking, and pet rent before users sign a lease.