US-Israeli Startup uses AI to revolutionize real estate industry

The AI technology collects information from billions of data points and transforms them into selectable attributes for prospective homebuyers.

Real estate market (photo credit: Courtesy)
Real estate market
(photo credit: Courtesy)
Artificial intelligence is poised to revolutionize the real estate industry and make the homebuying process much more transparent, AI-driven startup Localize believes.
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Headquartered in New York City, Localize was founded in Israel in 2012 and also has offices in Tel Aviv. The startup, which operates in Israel under the name Madlan, launched in the United States in 2019 and began working with real estate agents and brokerages earlier this year.
It has developed an AI- and big data-based platform that enables both buyers and brokers to streamline house-hunting, a traditionally low-tech process. 
“Our goal is to reinvent homebuying,” Localize President and Chief Operating Officer Omer Granot told The Media Line. “We introduced AI and big data to create transparency and trust with homebuyers that I think is just lacking in today’s market.”
The platform collects information from billions of data points and transforms them into selectable attributes for prospective homebuyers, including proximity to popular stores, future construction projects, building violations, complaints and even natural light.
Buyers can also tailor their searches via the startup’s hybrid human-AI adviser called Hunter, which creates a highly curated, ranked listing of properties that are then refined as users respond to suggestions.
According to Granot, more than 40% of those who purchase homes wind up regretting their decision due to a lack of information.
“There really is no place to find all these things out, except Localize,” he asserted, calling the real estate industry’s current process “extremely outdated.”
Other real estate firms have also begun to incorporate high-tech solutions such as machine learning and AI algorithms into their products and services.
One of these is the Seattle-based Zillow, an online real estate giant founded by former Microsoft executives that has more than 135 million homes listed on its platform. Zillow uses machine-learning models to simplify the real estate transaction process and provide customized searches and home valuations.
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Similarly, New York-based firm Skyline AI uses machine learning to analyze data from a number of sources to find optimal real estate deals that take into account a property’s condition and access to public facilities.
Localize on Wednesday announced that it had raised $25 million in a Series C funding round led by venture capital firm Pitango Growth, with additional financing from Israel’s Bank Mizrahi-Tefahot and other existing investors. So far, the company has raised $70 million.
Series C financing is the fourth stage of startup financing, and typically the last stage of venture capital financing.
Despite the COVID-19 pandemic, the startup has experienced rapid growth in the NYC marketplace.
“We now have north of 40,000 people who have signed up for the service,” Granot said.
On the other end of the real estate spectrum, Localize also works with realtors and brokerages. While buyers can use the platform for free, agents pay a subscription fee for access to the system and the technology.
“Today, agents do much of the work manually,” Granot said. “The agent gives you a call, and they start to go through this process of asking you questions, profiling you, trying to find the right apartment for you, and sending you recommendations.”
Following the latest funding round, Chemi Peres, managing partner and co-founder of Pitango, is slated to join Localize’s Board of Directors. 
Like Granot, he emphasized how cutting-edge technology can revolutionize the real estate sector.
“Buying a home is one of the most important financial and life decisions many people make,” Peres said in a statement shared with The Media Line. “The ability to use tools that automate and digitalize this process, combined with insights that are produced using algorithms which run on massive amounts of data, makes the results quick, accurate, and fully fitted to the client’s needs.”