Gen Z Dating App Ditto Replaces Swiping With AI Matchmaking and Real-World Dates

Gen Z dating startup Ditto is using AI to match college students and arrange weekly real-world dates, moving away from traditional swipe-based dating apps.

Aug 8, 2026 - 01:29
Aug 8, 2026 - 01:35
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Gen Z Dating App Ditto Replaces Swiping With AI Matchmaking and Real-World Dates
IMAGE CREDITS: DITTO

Gen Z dating startup Ditto is taking a different approach to online dating, replacing the endless swiping and messaging of apps like Tinder and Hinge with AI-powered matchmaking and real-world dates.

Ditto was founded by Allen Wang and Eric Liu, who left UC Berkeley to build a dating service aimed at young people frustrated with traditional dating apps. Rather than asking users to browse profiles and start conversations, Ditto uses an AI chatbot to learn about users and arrange weekly dates.

“As Gen Z ourselves, we were firsthand witnessing the behavioural shift in terms of how people are connecting,” Wang told TechCrunch. “We see that people are getting super tired of all the endless swiping and endless small talk, and they’re really looking for something more genuine in real life.”

AI matchmaking without the swipe

College students sign up for Ditto by texting an iMessage number and entering a code. The chatbot then guides them through an onboarding process that collects basic information such as their name, gender and birth date before asking more detailed questions about personality, interests and dating preferences.

Some users also share photos of celebrity crushes to help Ditto understand their preferred type.

Rather than simply matching people based on shared hobbies, Ditto tries to determine the personality traits behind those interests. For example, Wang said someone interested in rock climbing and skydiving could potentially be compatible with someone who enjoys hip hop, streetwear and skateboarding because both may be adventurous and individualistic.

“We claim that chemistry is actually predictable with the right signals,” Wang said.

Every Wednesday at 7 p.m., Ditto sends users their match along with a time and location for the date. The idea is to remove much of the work involved in traditional dating apps, where users must match, message, arrange a meeting and decide whether to follow through.

After each date, Ditto collects feedback and uses it to improve future recommendations.

150,000 signups

Ditto says it has attracted 150,000 signups. About 20% of matches that connect through the service eventually meet for a date, according to Wang.

The company also uses a collage-style graphic to introduce matches and explain why they might be compatible, an aesthetic that has become popular among Gen Z-focused social and dating startups.

Safety remains a challenge, particularly because Ditto moves users from matching to meeting relatively quickly. For now, the service is available at only a few dozen colleges, giving it a built-in verification system through students’ university .edu email addresses.

Ditto plans to expand to more schools and eventually beyond college campuses, while maintaining safeguards as its user base grows.

Backed by $9.2 million

The startup has raised $9.2 million in seed funding from investors including Gradient, Peak XV and Scribble. Wang said much of the investor interest came through inbound outreach after the founders gained attention on LinkedIn and X.

Ditto has also relied heavily on unconventional marketing, including videos featuring robot stunts designed to attract attention from college students. The company now has 12 full-time employees in San Francisco and is even hiring a “chief yacht officer” to organise promotional parties.

For Ditto, however, the marketing is only intended to get potential users through the door. The company believes the real product is the experience that follows.

“Viral moments get college kids to look; a good first date is what makes them stay,” Wang said.

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Shivangi Yadav Shivangi Yadav reports on startups, technology policy, and other significant technology-focused developments in India for TechAmerica.Ai. She previously worked as a research intern at ORF.