Meera sits in a Mumbai café, swiping through profiles on her phone. But she's not scrolling through Tinder. She's answering questions about her relationship values while an artificial intelligence studies her responses, her communication style, her deepest preferences. Within minutes, the algorithm declares a match: 89% compatible with a fellow business graduate. They meet for coffee. He tells a joke. She doesn't laugh.
"She wasn't even able to understand my jokes," he later complains. "How can you say we're 89% compatible?"
This is the reality of modern romance in India. Algorithms are making life-altering decisions about who you should marry, who you should date, who might be “the one.” But can a machine really understand the chaotic, beautiful mess that is human connection?
When Ancient Tradition Goes Digital
India’s approach to dating looks nothing like the West’s swipe-happy culture. Traditional values still reign supreme here. Around 90 percent of Indian marriages remain arranged, according to UNICEF data. Technology isn’t killing this tradition. It’s evolving it.
Platforms like Betterhalf.ai, Jeevansathi.com, and Shaadi.com are betting big on artificial intelligence. They’re using machine learning to predict partner preferences, automate safety checks, and match personality traits with scary accuracy. 
The numbers back up the hype. India saw a 25% increase in dating app downloads between 2024 and 2025, with over 70 million people actively swiping, chatting, and searching for matches every month. Compare that to traditional dating apps in the West, which struggle with retention rates of just 3.3%. Why the difference? Simple. These platforms aren’t selling weekend dates. They’re selling marriages.
The Science of Digital Chemistry
Modern AI matchmaking looks nothing like your grandmother’s newspaper matrimonial ad. We’re not talking about simple filters for height, salary, and city anymore.
Take Knot.dating, which launched in early 2025. Their chat-based AI assistant has actual conversations with you. It asks about your fears, your goals, what makes you laugh at 2 AM. The system analyzes hundreds of psychological markers, then hands off complex cases to real human matchmakers for the final call.
Or consider Sitch, which launched in December 2024 with a unique approach. Co-founder Nandini Mullaji trained their AI on her grandmother’s matchmaking expertise. Yes, you read that right. Her grandmother was a matchmaker, and that knowledge now lives inside an algorithm. Users answer nearly 50 questions through text or voice, and the AI learns from every interaction. By July 2025, Sitch had raised $6.7 million and was serving tens of thousands of users.
These systems use Natural Language Processing to analyze how you write, what words you choose, how you express emotion. Some platforms even track which photos make you pause, building a profile of your visual preferences without you consciously realizing it.
Coffee Meets Bagel runs their matching on a deep neural network where nine separate models evaluate each potential match and vote on compatibility. Hinge uses the Gale-Shapley algorithm, the same mathematical framework that matches medical students to residency programs. This isn’t guesswork. It’s behavioral science at scale.
The Math vs. The Magic
Here’s where things get interesting and a little contradictory.
AI use in dating has surged, jumping 333% in just one year as singles turn to technology to improve their chances of finding love. Nearly half of Gen Z singles have already used AI in their dating lives, whether to build stronger profiles, craft better openers, or screen for compatibility. Looking ahead, 44% of all singles say they would like AI to help filter matches, and 40% want help crafting the perfect dating profile, according to the 2025 Singles in America study by Match and the Kinsey Institute.
Yet there is a twist. While AI is becoming a major tool, it is not replacing intimacy. It is giving singles an edge. We are leveraging it for clarity and efficiency, but the human element, the laughter, the quirks, the small gestures, remains beyond any algorithm’s reach. That story about Meera and her 89% compatible match? The AI correctly predicted aligned goals and intellectual compatibility, but it could not foresee whether his jokes would land, whether his laugh would make her smile, or whether the way he stirred his coffee would charm or annoy her years down the line.
In many ways, this mirrors traditional arranged marriages in India, which have long emphasized long-term compatibility over instant chemistry. Sometimes, missing the joke does not matter at all.
The Problems Nobody Talks About
AI matchmaking isn’t perfect. Not even close.
Cybersecurity firm Signicat reported that AI-driven fraud attempts in the financial sector accounted for 42.5% of all detected fraud attempts in a 2024 report. This marks a massive increase from three years prior when deepfakes were not even among the top three types of digital identity fraud.[. Bad actors are using the same technology to create fake personas, steal money, and manipulate vulnerable users. Safety remains a huge concern, especially for women in smaller cities.
Then there’s the black box problem. When an AI declares you 85% compatible with someone, what does that actually mean? Most users have no idea. The algorithm won’t explain its reasoning. You’re just supposed to trust it.
Worse, there’s bias baked into the code. Facial recognition systems show error rates exceeding 30% for dark-skinned women, a direct result of training data that skews white and male. If your algorithm learns from biased data, it perpetuates those biases at scale.
Platforms are fighting back. Flutrr uses face recognition algorithms and vernacular profanity filters covering several Indian languages. They’ve implemented no-screenshot policies to prevent harassment. But it’s an arms race.
Even Nandini Mullaji, who’s building one of these AI matchmakers, admits the limits. “The data in those apps is insufficient to tell you if two people will have long-term compatibility,” she told TechCrunch. She’s trying to collect deeper information, but even she knows there’s only so much code can do.
The Indian Challenge
India’s matchmaking platforms face challenges that would make Silicon Valley founders weep.
The dating apps market in India was valued at $788 million in 2024 and is projected to hit $1.42 billion by 2030. But more than 1,500 matrimony portals are fighting for that revenue, each trying to crack a market of 500 million non-English speaking users in smaller cities and towns.
These platforms must navigate caste preferences, regional languages, astrological compatibility, family expectations, and community traditions. It’s not just about matching two people. It’s about matching two families, two cultures, sometimes two completely different worlds.
Some platforms are making bold moves. Knot.dating set a minimum income requirement of ₹50 lakh per year for men in July 2025, while setting no income bar for women. They defend it as maintaining “user intent” and elevating the experience. Critics call it elitist and discriminatory.
Meanwhile, offline services can charge $2,000 per year for curated matchmaking, targeting wealthy families who reject the “checkbox methodology” of apps. The irony? They’re using AI too, just hiding it behind white-glove service.
Can You Code Cupid?
Let’s be honest. Nobody really knows if this works yet.
33% of Gen Z have tried romantic relationships with AI companions, not humans. The technology is evolving faster than our ability to measure its impact on real relationships. The global dating app market is racing toward $20 billion by 2030, and that kind of money fuels rapid innovation, whether we’re ready for it or not.
What we do know is this: AI can’t replicate human empathy, intuition, or cultural sensitivity. It struggles with the unquantifiable things that make relationships work. The inside jokes. The comfortable silences. The moment you realize you want to see this person every day for the rest of your life.
But maybe that’s exactly the point. Maybe AI’s real job isn’t to replace human judgment. Maybe it’s to handle the impossible scale of modern dating, filtering millions of profiles down to a handful where real human chemistry gets its chance.
Think about it this way: Your grandmother’s matchmaker knew 50 families in her community. Today’s AI matchmaker analyzes 50 million profiles across continents. It can’t tell you if someone’s laugh will make your heart race. But it can tell you that out of those 50 million people, these three share your values, your goals, and your vision for life.
That 89% compatible match who didn’t laugh at the joke? The algorithm did its job. It found two people with the intellectual foundation for a lasting partnership. What happened next, whether they chose to build something despite the awkward first date or walked away, that was gloriously, messily human.
And maybe some decisions should stay that way.
The real question isn’t whether AI can pick your perfect partner.
It’s whether “perfect” can be calculated at all. Because love, in all its chaotic beauty, might just be the one thing that refuses to be solved.
