Known: Revolutionizing Dating with Voice AI to Foster Real-Life Connections
In the ever-evolving landscape of digital dating, a new player is making waves by prioritizing genuine, in-person connections over endless virtual interactions. San Francisco-based startup Known, co-founded by Celeste Amadon and Asher Allen, is leveraging voice-powered artificial intelligence (AI) to transform the way individuals meet and engage in the dating world.
The Genesis of Known
Amadon and Allen’s journey began with an AI-driven application designed to assist users in booking restaurants for dates. During the development phase, they introduced a voice-powered AI onboarding system to gather user preferences without the need for cumbersome forms. This innovation revealed a significant insight: users were more inclined to share information through conversation, leading to onboarding sessions averaging 26 minutes. Recognizing the potential of this approach, the duo shifted their focus, giving birth to Known.
Amadon articulated their vision: For the first time, we could know enough about somebody to serve them a date that would make sense. And if we could do that much faster with less rejection rate, we could create a user experience that could get people out on more dates.
Impressive Early Results
During its beta testing phase in San Francisco, Known reported that 80% of its introductions culminated in face-to-face meetings—a stark contrast to the lower conversion rates typical of swipe-based dating applications. This promising outcome attracted substantial investment, with the startup securing $9.7 million from notable investors, including Forerunner and NFX, alongside Pear VC and Coelius Capital. Notably, this marks Forerunner’s inaugural investment in a dating application.
Eurie Kim, a partner at Forerunner, praised Amadon’s approach: Celeste is a really thoughtful founder who understands the mindset of the consumer, which is a young female, to be honest. There are other people who can be focused on the male demographic, but she is focused on the young female who has a lot of unspoken desires and needs that, if you put them in a profile, they would never say, this versus that. And I think in a conversation, you can get a lot of those nuances out, but in the past, the conversation required a $10,000 matchmaker.
Addressing the Loneliness Epidemic
Amadon, who, along with Allen, left Stanford to pursue this venture, has always been deeply interested in creating social impact at scale. She views the current state of dating as a significant challenge for her generation. There’ve been a million pieces written about the loneliness epidemic in the U.S. And I do really think that it’s our generation’s largest problem, she remarked.
How Known Works
Currently in beta testing in San Francisco, Known employs a voice AI-powered onboarding process that engages users in a series of questions, eliminating the need for manual form-filling. This conversational method allows the AI to gather nuanced information about users, leading to more accurate match suggestions. Remarkably, some onboarding sessions have extended up to an hour and 38 minutes, indicating users’ willingness to engage deeply.
Amadon noted that when users type responses, they tend to edit themselves. In contrast, voice interactions are more spontaneous and authentic. The AI is designed to ask dynamic follow-up questions based on the conversation. For example, if a user mentions recently moving to the city, the AI might inquire about their likes and dislikes regarding their new environment.
Upon completing the onboarding, the AI proposes potential matches. Users can interact with AI agents to learn more about these profiles. If interested, they can indicate their preference by tapping interested. When two users express mutual interest, they have 24 hours to accept the introduction and an additional 24 hours to agree on a date. This structured timeline aims to minimize prolonged chats and reduce instances of ghosting, encouraging users to meet in person promptly. After the date, users can provide feedback to the AI, refining future match recommendations.
Integrating Dining and Scheduling
While Known has shifted its primary focus, it hasn’t abandoned its original concept entirely. The app assists users in selecting restaurants based on their preferences. Through AI chat and calendar integrations, users can specify their availability for first dates. During the beta phase, the company charged $30 per successful date but plans to experiment with different pricing models to determine the most effective approach.
Building the Team
Currently, Known comprises three full-time engineers and four team members dedicated to go-to-market strategies, supported by several contractors across various domains. Amadon and Allen plan to expand their team using the recent funding to enhance the app’s capabilities and reach.
The Competitive Landscape
Known is entering a competitive market with several startups aiming to revolutionize the dating experience through AI. For instance, Overtone, led by Hinge CEO Justin McLeod, seeks to understand users better to facilitate meaningful matches. Established platforms like Tinder, Bumble, and Hinge are also integrating AI features to maintain user engagement. Despite the competition, Amadon remains optimistic.
When it comes to other startup dating products, I’ve been so happy to see a lot of people building in the space because I think it shows that it’s time to shift away from a swipe-based model. And I think most of them that I’ve seen have been pretty different from what we’re building at Known, she stated.
Looking Ahead
As Known continues its beta testing in San Francisco, the team is preparing for a broader launch in the near future. By harnessing the power of voice AI, Known aims to address the challenges of modern dating, fostering genuine connections and reducing the prevalence of superficial interactions. With a focus on facilitating real-life meetings, Known aspires to make a significant impact on the dating landscape, offering a refreshing alternative to traditional swipe-based apps.
