Orchard raises $69 million to develop machine learning for buying and selling homes
Orchard has raised $69 million in venture capital to continue the development of its machine learning technology that aims to make buying a home less complicated. Revolution Growth led the round of funding, which also included money from FirstMark, Navitas, Accomplice, and Juxtapose.
The company has now raised a total of $138 million, a sign that investors are bullish on the potential of its algorithms to disrupt the real estate market. Orchard offers services that enable the entire experience — including listing a home, searching for a home to buy, making an offer, and closing the sale — to be done virtually.
That has the potential to eat into a legacy business that still can be a complicated slog for buyers and sellers as they navigate the intricacies of paperwork and the idiosyncrasies of brokerage firms. But it’s even more tantalizing during the Covid-19 pandemic when the ability to travel and view homes is sharply curtailed.
Indeed, the real estate industry, both traditional 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% increase in just one week. Zillow reported a 533% increase in 3D home tour creations between February and March, and subsequently 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. A big focus remains one of the trickiest parts: Those customers who are trying to sell their current home while simultaneously buying a new one. Typically, trying to line up both of these transactions can be a massive headache.
To solve the issue, Orchard has developed a solution that mixes machine learning, rapid human assistance, and some financial products that can help bridge that complex buying-selling conundrum.
The machine learning part comes into play primarily with the 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 that covers a wider parameter of features. So, for instance, beyond just looking for the number of rooms, someone can search for more specific kitchen amenities, the style of the floor plan, the specific feature of a back yard. The results for an area are ranked by how well they correspond to the buyer’s desires.
That is complemented by Photo Switch which uses computer vision and machine learning to scan photos of each home, both interior and exterior, to add more precise details about the property to its database. This allows additional visual comparisons in the search engine.
Once a buyer finds a property, the entire bid and closing process is digitized, including the title and mortgage. To help with financing, Orchard launched in July a financial product called Orchard Home Loans. In a trial of the loan product, the company said 50% of customers in Texas opted for its service to help facilitate the transaction.
To help those buying and selling, the company also offers a 90-day financial instrument called Move First. Orchard essentially agrees to buy the old home using its money so customers can satisfy the requirements to get a new mortgage. Most of those houses then sell to new buyers during that window.
Orchard is now operating in Texas, Colorado, New York, and Georgia. More recently, it has moved into Denver and Atlanta. The latest fundraising will be used to continue for product development and eventually to help expand into new territories.
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