Skyline AI, a technology company based out of Tel Aviv, plans to upend the real estate investment market with it’s machine learning software that predicts future property values.
Recently, they received $3 million in seed funding from power house Silicon Valley VC, Sequoia Capital. Per TechCrunch, this money is to be used to build up its tech platform and hire experts in data science and machine learning.
Below is an excerpt from the Tech Crunch article that specifically addresses Skyline AI’s value proposition.
“Skyline AI wants to take the guesswork out of investment decisions by training its technology on what it claims is the most comprehensive dataset in the industry, drawing on more than 130 sources and analyzing over 10,000 attributes on each data asset for the last 50 years. Skyline AI’s tech then compiles all information into a data lake and cross-references everything to find discrepancies and figure out what information is the most accurate.”
With this product, I’m most excited to test how “comprehensive” this “comprehensive dataset” really is.
Naturally I would expect this software to be able to pull primary market information:
- Historical vacancy
- Rents
- Absorption
- Sale Comps
- Total supply
- Employment rates
- *insert any high level basic market information blah blah blah*
But the website also leads to me think that this data set could pull secondary information such as:
- Neighborhood walk scores
- Traffic reports
- Demographics
- Refurbishment prices
- Wired scores
- REIT performances
- Crime reports
- Infrastructure
- Zoning codes for redevelopment purposes
- Historical construction costs
Given this, I believe the value of this software will come by pairing the secondary information with the primary information.
Last week I requested a demo of the product. After the demo, I’ll be sure to follow up with my findings.
Below are the two articles I’ve read about the company.
CRE Tech & Trends 
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