Orchard raises $69 million to develop machine learning for buying and selling homes

Venture BeatThis post was originally published by Chris O'Brien at Venture Beat

Orchard has raised $69 million to further simplify the process of buying a home. Revolution Growth led the round, which included money from FirstMark, Navitas, Accomplice, and Juxtapose.

Orchard has now raised a total of $138 million, a sign investors are bullish on its algorithms’ potential to disrupt the real estate market. The company offers services that enable the entire experience — including listing a home, searching for a home, making an offer, and closing the sale — to be handled virtually.

This has the potential to eat into a legacy business riddled with paperwork and brokerage firm idiosyncrasies. But it’s even more appealing during the COVID-19 crisis, when the ability to travel and view homes is sharply curtailed.

Traditional real estate firms and startups have been racing to respond to the pandemic with more aggressive digitization efforts. In March, real estate brokerage company Redfin said requests for video-based home tours had increased 494% in just one week. Zillow reported a 533% increase in 3D home tour creations between February and March, and it later announced new tools that allow renters to sign leases virtually.

Orchard is targeting the entire home buying chain. Founded as Perch in 2017, the company rebranded to Orchard earlier this year. Its overall mission is to digitize the real estate market, with a focus on one of the trickiest aspects: helping customers who are trying to sell their current home while simultaneously buying a new one. Lining up both of these transactions can be a massive headache. But Orchard has developed a solution that mixes machine learning, rapid human assistance, and some financial products to help bridge any potential gap.

Orchard brings machine learning into play primarily through its search function. Back in March, the company launched Home Match and Photo Switch to personalize the search for homes. Home Match uses an algorithm that creates a more robust personalized search service covering a wider parameter of features. Beyond just looking at the number of rooms, for instance, someone can search for more specific kitchen amenities, a type of floor plan, and a back yard or other features. The results for an area are ranked by how well they correspond to the buyer’s wish list.

This feature is complemented by Photo Switch, which uses computer vision and machine learning to scan interior and exterior photos of a home and add precise details to the database. This also allows additional visual comparisons in the search engine. Once a buyer finds a property, the entire bidding and closing process is digitized, including the title transfer and mortgage. To help with financing, in July Orchard launched a financial product called Orchard Home Loans. In a trial of the loan product, the company said 50% of customers in Texas opted to use the service.

To help those simultaneously buying and selling, the company also offers a 120-day financial instrument called Move First. Orchard essentially agrees to buy the old home so customers can satisfy the requirements of getting a new mortgage. Most of the houses then sell to new buyers during the 90-day window.

Orchard operates in Texas, Colorado, New York, and Georgia and has recently moved into the Denver and Atlanta markets. The latest round will be used to continue product development and gradually expand into new territories.

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This post was originally published by Chris O'Brien at Venture Beat

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