Alex Ruber practically grew up thrifting. His mother, an immigrant who escaped communist Romania and moved to Italy, then Canada, often brought him along to secondhand stores and Sunday flea markets when he was a child. Together, mother and son would hunt for unique items. “I remember getting my first piano literally from a flea market,” he says. “For me, it was like a treasure hunt.”
Fast forward 20 years, and Ruber, a former Apple software engineer now based in San Francisco, is the cofounder of a new AI-powered search engine platform designed to replicate the thrill of thrifting, but online. The site, called Encore, aggregates items from hundreds of resale websites and helps shoppers find esoteric and unique items—the proverbial needles in the haystack. What makes Encore different is that the site doesn’t just search for terms on Facebook Marketplace or eBay, but rather it asks the user to describe what they’re looking for in the same way they would describe it to a friend.
Thanks to its large language model technology, Encore lets shoppers run really specific searches, with queries such as: “dress like the one Carrie Bradshaw wore in season 6, episode 12, in a size 0 or 2.” Or “mid-century modern dining table in walnut finish but it has to have leaves to accommodate eight guests or more.” Shoppers can edit their search and type a follow-up prompt like “rectangular table only” or “under $1,500.” And if the site draws a blank, the user can toggle a button and search for new items.
The ultimate goal? “To become the Perplexity of online shopping,” says Ruber, who cofounded Encore with former Twitter and Asana engineer, Parth Chopra.
Shopping Spree
Everyone who loves to buy things secondhand has a reason for doing so. Some are looking for a bargain, others want to reduce the carbon footprint associated with big polluters like the fast-fashion and fast-furniture industries. Others yet enjoy the lower barrier to entry for luxury items. As a result, the global resale market is booming.
Encore launched in June and has 50,000 searches per month, with 25 percent month-on-month growth for searches. It is one of many companies trying to make secondhand shopping easier and more fun by providing a more refined user experience than the search aggregators that have come before. The Beni app, for example, lets you type “checkbeni.com/” in front of any product URL to see whether a secondhand version exists on various resale marketplace websites. Meanwhile, the Berlin-based Faircado has built a browser extension that lets you browse for items as you normally would, and pops up with “pre-loved” alternatives when they’re available. (The Encore team started with a website so anyone could access the site from any device, but they are also launching an app in the next few months.)
Encore is using a blend of GPT-4 and its own computer model, which is a fine-tuned version of GPT that the company trained on some fashion and ecommerce datasets so it could recognize various brands, styles, and aesthetics. People using the free version get 30 to 40 results per search; chronic shoppers willing to pay $36 a year (there are currently a few hundred of them) get twice as many results per search and a few other perks. But unless your query is overly convoluted (think “boxy bomber jacket, with elastics on sleeves, and make it like the one Tom Cruise wore in Top Gun 2), Ruber says free users will get the same—albeit fewer—results as paying customers.