– A predictive tool to analyze commercial real estate growth – A predictive tool to analyze commercial real estate growth



Legal Name:, Inc.

Location: New York City, New York

Founded: 2018

Founder(s): Bo Steadman, Matt Fisher, Victor Franco


Social media: 22 followers on LinkedIn, 9 followers on Twitter

Industry: US Commercial Real Estate Market

Size: $16T in 2018 (Source: Nareit)

Introduction helps investors accurately identify the best commercial real estate investment opportunities with a predictive analytics-powered SaaS platform called Ranked #12 in the competitive accelerator program AngelPad, the startup also offers geo-visualization to commercial real estate investors. 

The Product makes it easy to measure commercial real estate value in order to detect those with the potential of delivering high returns on investment. What this AI-powered tool does is aggregate datasets at a neighborhood and package level to forecast pricing trajectories. Being an open platform, collects and cleans data, from scores of web-based sources and the client database, and incorporates it into an easy-to-consume report format. 

The portal’s machine learning algorithm and sophisticated geo-visualization platform reveal the property price trends.

It even generates detailed property reports in real-time, allowing real estate investors to analyze otherwise scattered datasets and visualize geography-specific trends.

Origin and Founding Team

Bo Steadman, a licensed architect and MBA from Duke University, had a pet peeve. According to the startup’s LinkedIn page, he felt that it was near impossible to get good quality analyses of real estate value. One time, while working in the architecture and development space, he spent two weeks to generate a report to map the feasibility of a high-rise project for a client. But at the end of the day, they ignored the data and went with their gut instinct. A couple of years later, he spent an entire summer cleaning, accumulating, and analyzing data and trying to help a large real estate developer predict what property they should invest in.

Such troublesome instances led Steadman to build a tool that would enable analysts and investors to quickly ascertain price-growth potential for any real estate.

While he was studying at Duke University, Steadman joined forces with Victor Franco, who currently serves as the COO of The two connected with Matt Fisher, a deep learning and machine learning expert, to tackle the problem of understanding and forecasting real estate growth. And thus, was born.

Performance and Trends secured Angelpad seed investment of $120,000 in March 2019, according to a TechCrunch article.

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