Machine Learning

Unlocking Troves of Disparate Data

Our machine learning algorithms bring together the previously disparate world of commercial real estate to provide property intelligence.

Machine Learning header image

Machine Learning & the Reonomy ID

Commercial real estate data has remained siloed and disparate without a common language to standardize information collection and sharing.

Our machine learning algorithms take data from any source and restructure it using our own universal language: the Reonomy ID.

Now, you can simultaneously resolve disparate records and augment your database with the same technology.

The Key To Building Your Source of Truth

Backed by Artificial Intelligence, the Reonomy ID can unlock the true value of your commercial real estate database by mapping all records, including those lost, to the correct source using a clear identifier, allowing you to discover new depths to the data you already have.

AI and Predictive Analytics

Our algorithms go beyond connecting data. From predicting what will sell next to determine if a roof needs repair, our platform leverages artificial intelligence to provide you with predictive analytics.

Revolutionary Proprietary Algorithms

Our algorithms are unmatched in experience. After 6 years in market, they have been trained on billions of unique data points and feedback from thousands of users.

Jonathan Bernstein, Meridian Capital Group
Company Logo

"No other company takes in that volume of data and uses a measured, quantitative approach to make sense of it."

Jonathan Bernstein, Meridian Capital Group

Machine Learning Algorithms

1

Our property resolution algorithms enable property data from any data set to be stitched together and attached to it's unique Reonomy ID.

2

Our company algorithms pierce the LLC to illuminate the TrueOwner and draw a string across all related LLCs with the same TrueOwner.

3

Our people resolution algorithms scour billions of different contact records to connect TrueOwners with accurate phone numbers, emails and mailing addresses.