An all-in-one automation interface built to meet the specific needs of a real estate investment corporation seeking to become more competitive in the aggressive market of NYC. Leveraging web-scraping capabilities to automate the research and first-pass filtration of properties, this program laid out promising leads for further analysis by agents.

This was a high-impact project which freed up hours of time for agents on a weekly basis, allowing them to directly speak with homeowners instead of sorting through massive amounts of data in search of a story.

The exact decisions on how to filter data were driven by extensive interviews held to determine the various factors that come together to make a property viable and interesting. Using the wealth of information publicly available, the generated leads brought our agents to the doors of sellers right as they were coming to the decision to sell, before anyone else.

Built with Python, Selenium, and Beautiful Soup 4, featuring robust logging for usage tracking and error handling, with a flexible configuration system to tailor settings and behavior.