As in many fields, real estate professionals may be experiencing uncertainly about how artificial intelligence tools could disrupt the industry or replace jobs. But one startup is flipping that on its head by employing AI to help agents do their jobs more effectively.
First, a Durham, NC-based startup, has raised a $5 million Series A round from over 30 investors to continue development of its AI and machine learning platform that helps agents predict which contacts they need to reach out to to drive deals. The platform houses data on all U.S. homeowners and learnings based on all of its current agents to drive its relationship management solution.
“We serve the top agents that have large networks, thousands of relationships and hundreds of past deals,” explains Mike Schneider, co-founder and CEO. According to Schneider, home selling is a particularly concentrated business, with the top 10 percent of agents doing 90 percent of the deals.
“They have the network, they just don’t have the time to keep up with all of them. Our whole system is a really simple, big recommendation engine for where they should spend their time building those one-on-one relationships,” Schneider says. He cites that, from the company’s research, 70 percent of deals come from personal relationships.
Unlike a traditional CRM platform, First aggregates data from the entire population of homeowners about things like life events, income, property and 
mortgage information and more to drive its algorithm. It works with the agent’s current contacts list to suggest who they should call or catch up with — basically, which of those thousands of contacts are likely to soon be putting their home on the market.
The intelligent platform also uses historical data gleaned from how its predictions have been successful in the past. “For every agent that comes on board, it actually learns from each of them and has been trained by the ones who come before them,” says Schneider, whose interest in data and machine learning stems from his former career in venture capital, where he evaluated and invested in AI companies.
“I became very convinced that the next wave of machine learning companies were going to be all predictive focused,” he says.
After about two years since inception, First has close to 1,000 agents already on the platform and is starting to partner with larger brokerages. They have been venture-backed from the beginning, garnering a $750,000 pre-seed round from Durham’s Idea Fund Partners and a $2.5 million seed round from a number of investors.
This latest $5 million will largely be spent doubling down on product, says Schneider. They’re at above 30 employees now and plan to grow to 40 by end of year.
They’re also rolling out a new dimension of the platform which will look at agents’ past communications — emails, phone calls, etc. — to determine how robust your relationship is with any given contact.
Those insights will be cross-referenced with the current algorithm — so, if you know two people are twice as likely as any random contact to sell their home soon, and you also know one of them two times better, that makes your chances of landing that client four times better.
“The combination of our data analytics with relational depth is pretty powerful,” says Schneider.
“We’re the first company, at least in this industry, that is starting to understand what your relationships look like, and that’s our real differentiator.”
Photos via First
