Traditional commercial real estate valuations are done manually by appraisers that rely more on experience with similar properties than on a complete view of the data. Geophy’s Evra platform corrects that human bias by using data science to derive valuations on demand using data from thousands of sources. Using data from adjacent property values, to the number of concerts held within the neighborhood, Evra can create the most accurate valuation at scale.

However, real estate data is notoriously messy, and ML models are only as good as the data that goes into them. Buildings have more than one address, locations that are on top of each other have the same coordinates, records are kept in different formats between different counties and states. Geophy cleans and unifies that data using business rules and integrity constraints before it can be used by the Machine Learning models. Using ML, Geophy automatically derives a valuation for commercial real estate properties and, because of full data traceability, the factors that contribute to that valuation.

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