Our team was expressing discontent for the apartment hunting process. In order to get the "perfect" place, it's almost necessary to connect with a real estate agent to leverage their knowledge and connections. But why not automate that entire process and use a voice assistant to simplify the heavy time investment? All the data is out there; we just need to aggregate, filter, and present those property recommendations in a palatable way.

What it does

The user initiates conversation with Alexa by requesting a residence with certain criteria like price, location, etc. The MLS real estate list is queried with the defined criteria. After some data processing, the user is presented with the ideal 3-5 residences.

How I built it

It is hosted on AWS Lambda, written using Node.js. Details of properties is queried with the Zillow API. We use the Twilio API to send a link to the resulting properties.

Challenges I ran into

There is no free API for public property listing data. The data that was available was not granular enough to our liking.

Accomplishments that I'm proud of

We have an Alexa Skill that solves a real world problem. We were able to integrate multiple services like Zillow and Twilio in our product.

What I learned

We learned a lot about the real estate business and how to leverage different software tools to facilitate the interaction.

What's next for Realty R Us

We want to utilize a more complete listings database. We want to further develop our product by adding more criteria and data to narrow down better results. We also want to implement a business plan that scales to the entire nation and and implement a pricing plan.

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