Foresite's data is collected from hundreds of primary sources across the web. This data is then fed through our machine learning algorithm to identify time-series trends related to the input parameters. We test our algorithm on a holdout sample of historical data to determine accuracy and normalize the data to provide guidance on forecasted price trends. Finally, the data and forecasts are pushed to our sophisticated geo-visualization platform to help you understand the trends that matter.
Our intuitive map-based interface allows you to understand statistical and geospatial trends within a given market without any GIS experience. Powerful filters allow for granular control over the output while automated analysis helps you understand what matters. Foresite can even plug into your data, allowing you to leverage the data you collect from operations.
Foresite makes complexity simple.
Foresite's founding team is composed of three members with varied experience in data science, commercial real estate, machine learning and operations:
Bo is a former architect and recent graduate of Duke's Fuqua School of Business. He has 5 years of experience in architecture and development, including at two of the nation's largest firms--Hines and Perkins+Will--where he specialized in the application of data science techniques towards real estate.
Matt is a data scientist with deep expertise in machine and deep learning. Prior to his current position at Foresite.ai, Matt worked at Saffron, a deep learning startup based in San Francisco. He began his education in machine learning while developing tools to discover the Higgs Boson particle at the CERN lab in Switzerland.
Victor is a former Army Ranger and Captain, and recent graduate of Duke's Fuqua School of Business. A decorated combat veteran, Victor spent 8 years leading combat units of varying sizes. Last summer, he worked in product management at Magic Leap.
Our open platform accepts any data--ours, yours and even third-party data. Foresite's data is aggregated from dozens of datasets across the web, automatically cleaned and aggregated to a simple, easy-to-use format. You can also plug in proprietary data and even data from third-party sources. This allows you to get the complete picture of the trends that are moving a market.
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