“An opportunity to choose chance.”
That’s what social platform startup 222 claims to offer its members. It isn’t a dating app—there’s no swiping, and, more notably, there’s no actual choosing of who you might be meeting.
Instead, an AI-driven algorithm does it for you.
“We wanted people to be out and meeting each other. It was [based] on this whole idea of the death of third places, and that people aren’t just running into each other anymore,” says 222 cofounder and chief operations officer Danial Hashemi. “There’s no more chance encounters, so the whole [algorithm] has always been about engineering chance.”
A backyard origin story
In 2021, twenty-something-year-old friends Keyan Kazemian, Arman Roshannai, and Hashemi came up with the idea for 222 as part of an independent “research project.”
They created a personality questionnaire and asked friends and strangers to complete it. Participants were grouped based on their answers, then invited to Kazemian’s backyard for wine and food. Afterward, the trio would assess how well everyone got along.
“It convinced us of two things: one, it is possible to solve the social isolation problem by using machine learning and AI, and two, that even at its [initial] stage, with just us randomly assigning people, they enjoyed it so much,” Hashemi says.
Social isolation isn’t a new problem in our increasingly digitized lives, but it remains a persistent one. Despite access to every niche thought, community, or subreddit imaginable, society is, statistically, lonelier than ever.
According to a 2023 report from the Department of Health and Human Services, we are experiencing an epidemic of loneliness. Between 2003 and 2020, time spent alone increased by 24 hours per month nationwide. Over the same period, time spent engaging with others dropped by 10 hours per month.
In 2018, only 16% of Americans felt connected to their communities.
So, can AI truly be the cure to social isolation? Hashemi thinks it can—through 222, which he believes can “deepen relationships” and “connect people” to their cities.
How it works
The name 222 comes from the street address in Los Angeles where the idea was first developed. The platform is accessible via both app and website. There are no profile photo uploads, and the experience begins with what feels like the final boss of personality quizzes.
With prompts ranging from favorite movies to political views to “how likely would you be to do cocaine?”, the algorithm gathers input through a labyrinth of questions. These span categories like identity, interests, and media, shaping each user’s “curation profile.”
Eventually, users receive curated invite cards to activities like “dinner and a comedy club” or “pickleball and lunch,” matched to their algorithmic personality type.
To accept—and to help fund the app alongside its investor backing—users can pay a per-event curation fee of $22.22, subscribe monthly for the same price, or choose a discounted three-month or annual plan.
“We’re not trying to be some novel experience that someone tries one time and then doesn’t come back,” Hashemi says. “We’re trying to build the lasting product that people build their social infrastructure on top of.”
After each group event, users can give feedback on whether they’d like to hang out or date specific individuals. This helps fine-tune the algorithm and increases the “retainment factor,” according to Hashemi—either deepening existing connections or making space for new ones.
“It just feels like we’re more divided than ever and there’s more echo chambers than ever,” Hashemi says. “All of these social media platforms are only showing you what you love and aren’t challenging you.”
Originally launched in L.A., 222 has since expanded to New York City, San Francisco, and most recently, Chicago. To date, 222 has raised $3.6 million in seed and angel investments from the likes of General Catalyst, Y Combinator, Upfront Ventures, and the 1517 Fund.
On July 2, the platform will become available internationally for the first time, launching in Toronto, with London and D.C. to follow later in the month.
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