Real Estate Genius is an app that uses a ton of data to tell you how much a house (or apartment or abode or mansion or shack or hovel) is really worth. The results may surprise you!
Anyone who’s ever lived in New York City can attest to the frustrating real estate market and the racket that is the broker industry (15%? Are you serious?!). Enter Real Estate Genius, an app that takes the expertise traditionally owned by a few people and makes it widely available to the general public!
Real Estate Genius analyzes publicly available data provided on a real estate property and compares it to all the data from past transactions. This includes analyzing images of homes to help evaluate their price! The tool can use all this data to estimate the price of a property within a certain margin, thereby helping the general public understand the “real” general worth of the home they wish to sell, purchase, or rent.
You can try the app live or download all the code from Github.
WHY WE ❤ IT
As resident New Yorkers, we’re always concerned with skyrocketing real estate prices so Real Estate Genius is an app that hits close to our hearts. I mean, I voted for “The rent is too damn high” party, didn’t you? (You think I’m joking.)
HOW YOU DO IT
The geniuses behind Real Estate Genius – Felix La Rocque Carrier, Mathieu Gamache, Anthony Garant, and Sam Snow – are a bunch of engineering students from Polytechnique Montreal who love hackathons and entrepreneurship. Here’s what they had to say about hacking with the Clarifai API!
Clarifai: What inspired your idea for Real Estate Genius?
Real Estate Genius Team: We are always searching for the “Next Big Thing” in the software world to help us start our own company. We wanted to work on developing an A.I. that could analyze a problem way better than a human. The real estate industry was an awesome gateway to this challenge because it’s a market where the expertise is owned by few people and the general public is easily afraid of it. We were inspired by the quantity of data available for real estate and the fact that price approximations were still done by hand.
C: How did you build your app?
R: We used the Clarifai API to help us process pictures of homes and get tags on certain characteristics that help evaluate the price of each home. All of that information is then processed with machine learning to correlate between existing selling prices and the resulting approximate price.
We used Azure machine learning features with an AWS backend to provide the machine learning and the web interface to a potential client. We also mined data from various sites to get the real estate information.
C: What was your favorite thing about the Clarifai API?
R: The API is one of the simplest we worked with. Usually with APIs, you need to search for a platform specific SDK or else the communication is bloody hard. Clarifai API is literally just two API calls and you get the result you want.
Thanks for sharing, geniuses!
To learn more, check out our documentation and sign-up for a free Clarifai account to start using our API – all it takes is three lines of code to get up and running! We’re super excited to share all the cool things built by our developer community, so don’t forget to tweet @Clarifai to show us your apps.
