ReCompIQ started as a data science research project studying apartment trends in NYC. We realized that while tens of thousands of listings are posted on the internet at any given time, these listings are missing key data needed to truly evaluate how an apartment compares with the rmarket.

To solve this we developed a proprietary machine learning model that can analyze floorplans and extract crucial information that isn't available in listings. By identifying every component of the plan and studying their relationship to each other, our model can accurately determine square footage, the size / shape of each individual room and key details like kitchen layout and window exposure.

By running this process against over thirty thousand listings we were able to build a truly advanced database that has immense potential for brokers, investors, policymakers and even apartment searchers. The ReCompIQ platform allows you to run this same exercise on any floorplan and instantly see how it stacks up against the rest of the city.