Two Business Insider journalists embarked on a weeks-long experiment to test whether AI-powered matchmaking apps could revolutionize their dating lives. They tested four platforms: Facebook Dating (with 21 million users), and smaller startups Sitch, Amata, and Three Day Rule—all promising to use artificial intelligence to find better matches and reduce dating app fatigue.
The experiment revealed mixed results. Amata emerged as the standout performer, successfully facilitating actual dates for both testers. The app’s AI chatbot not only matches users but also plans entire dates, making reservations and scheduling meetups. Users pay $25 to commit to each date, and can only message their match within two hours of the scheduled time—a feature designed to eliminate the exhausting messaging phase that plagues traditional apps.
Sitch offered a premium experience with excellent UX and a friendly chatbot interface, but at $90 for three “set-ups,” the high cost proved prohibitive. The app slows down the swiping process by having users vote on AI-selected profiles and explain their rejections—forcing more thoughtful consideration than mindless swiping.
Facebook Dating’s AI assistant, launched just weeks before the test, delivered underwhelming results with poor match quality and geographic mismatches. Three Day Rule failed to produce any matches for one tester entirely.
A key differentiator: these apps use LLMs (Large Language Models) to conduct extensive interviews with users, then write dating profiles on their behalf—eliminating the dreaded bio-writing process. Users interact with AI chatbots that have human avatars, creating a conversational matchmaking experience rather than endless swiping.
The apps employ various accountability mechanisms. Amata’s AI threatened to pause matches for seven days if users repeatedly failed to show up for dates, protecting other users from disappointment. The chatbots also conduct post-date follow-ups, asking detailed questions about personality compatibility and future plans.
Despite some successful dates—including drinks at a brewery and a Lower East Side bar—the journalists’ verdict was clear: AI matchmaking apps are still just dating apps. While features like automated date planning and slowed-down matching processes offer improvements, they don’t fundamentally solve the dating app burnout affecting millions of users on platforms like Hinge and Tinder.
Key Quotes
We don’t want people who are not emotionally available, who are on dating apps just for their ego boost
Amata founder Ludovic Huraux explained the app’s philosophy to Business Insider, emphasizing how AI matchmaking aims to filter for users seeking serious relationships rather than validation—a key differentiator from traditional dating apps.
My main takeaway: AI can’t fix me. Dating is WORK. I’m still feeling dating app burnout, and messaging a bot instead of swiping didn’t really change all that much for me
Journalist Sydney Bradley’s candid assessment captures the core limitation of AI matchmaking technology: while it can optimize processes, it cannot eliminate the fundamental time, energy, and emotional investment required for dating.
Going forward, if you fail to set up a date again when you have an intro, I’ll need to pause presenting people to you for seven days unfortunately. Because we want to avoid disappointing them if they can’t get a real date with you
This message from Amata’s AI matchmaker demonstrates how these platforms use accountability mechanisms to protect users from flaky behavior—showing AI can enforce social norms that traditional apps struggle to maintain.
I hate all my Hinge prompt answers. Always have, always will. Letting AI play Cupid
Journalist Henry Chandonnet highlighted one of AI matchmaking’s most appreciated features: using LLMs to write dating profiles eliminates the anxiety-inducing task of crafting the perfect bio, a pain point for millions of dating app users.
Our Take
This experiment reveals a critical insight about AI applications: technology excels at optimizing processes but struggles to change human behavior. The AI matchmakers successfully automated logistics, improved profile quality, and enforced accountability—all valuable improvements. However, they couldn’t solve the core problem: people are exhausted by dating itself, not just the apps. The $25-90 price points also expose a potential market limitation—premium AI features may only appeal to a narrow demographic willing to pay significantly more than free alternatives. What’s particularly interesting is how these apps anthropomorphize AI with avatars and personalities, suggesting users still crave human-like interaction even when they know they’re talking to algorithms. The post-date follow-ups and rejection explanations show AI can add a layer of emotional intelligence and accountability missing from swipe-based apps. As AI continues penetrating consumer applications, this case study demonstrates that success requires not just technical sophistication, but understanding which human problems technology can actually solve.
Why This Matters
This real-world test of AI matchmaking technology reveals both the promise and limitations of applying artificial intelligence to human relationships. As dating app fatigue reaches epidemic levels—with users cycling through deleting and redownloading apps—companies are racing to deploy AI as a solution. Startups like Sitch and Amata have raised millions betting that LLM-powered chatbots can succeed where traditional swiping has failed.
The results suggest AI can improve specific pain points: automating profile creation, planning logistics, and forcing more intentional decision-making. However, the technology cannot solve the fundamental challenge of making time for dating or eliminate the emotional labor involved. This matters for the broader AI industry because it demonstrates that even sophisticated language models have limits when addressing complex human behaviors and emotions. The high costs ($25-90 per match) also raise questions about the business model sustainability of AI-enhanced dating platforms. As major players like Facebook integrate AI features and venture capital flows into dating tech startups, understanding what AI can and cannot fix in human matchmaking will shape the industry’s evolution and determine whether these innovations represent genuine progress or just repackaged swiping.