At the 3F VC Mixer, we heard the story of Styl AI from its co-founder, Dhruv Bindra. After the session, a founder next to me summed it up perfectly:
“This unlocked a new domain of interest, data collection, annotation, and selling rich datasets as a business. I’m intrigued by Dhruv’s ability to articulate complex ideas in the simplest, yet most effective way possible.”
He was right. Styl AI isn’t just the story of a clever shopping app. It’s a playbook for building a data-first company, where the product is simply the vehicle and the dataset is the real asset.
Here’s a breakdown of the mental models and founder lessons from Dhruv’s journey:
Mental Model 1: Engineer for Data Collection, Not Just Engagement
The genesis of Styl was a UX observation: scrolling through e-commerce grids was inefficient. The solution, a “Tinder for Shopping” swipe interface, looked like an engagement gimmick.
The Founder Insight: A swipe is not a scroll. A scroll is passive, low-signal. A swipe is explicit, binary, and structured. Every session wasn’t just browsing, it was training data on individual fashion preferences. Styl wasn’t built to entertain users. It was engineered, from day one, to be a data-collection machine.
Mental Model 2: Weaponize GTM for Targeted Data Acquisition
Styl struggled for eight months with user acquisition. The breakthrough? A growth hack: “Guess My Sorority.”
The Founder Insight: It wasn’t just a viral loop, it was a precision funnel for targeted data acquisition.
- Pre-Qualified Leads: By scraping public sorority rosters, Styl reached socially influential users.
- Zero-Party Data Collection: The “game” of swiping before the sorority reveal quietly generated the first layer of preference data.
- Low-Friction Onboarding: The reveal drove downloads, moving users into the app where the real data collection began.
This ensured Styl’s dataset was high-quality from the start, focused on a specific, valuable demographic.
Mental Model 3: Data is Expensive, Pay the Price
Founders often underestimate what it costs to acquire high-quality data. Dhruv didn’t. He went wherever he had to, even to Telegram services that charged steep Bitcoin-only fees for scraping tools. These were the only tools that worked, and Styl invested in them.
The Founder Insight: If data is your asset, treat it like gold. Sometimes the right dataset is so valuable, you pay a premium upfront to build the foundation for your business. Styl’s dataset wasn’t an accident, it was a deliberate, expensive, and defensible investment.
Mental Model 4: First-Principles Research Beats Assumptions
When planning Instagram growth, Dhruv assumed women should be the face of the brand. Instead of trusting the assumption, he sat with female friends, observed how they scrolled, and discovered what content actually worked.
The result? Dhruv himself became the face of Styl, not out of ego, but because it was the data-driven conclusion.
The Founder Insight: Don’t outsource your understanding of your customer or your distribution channel. Roll up your sleeves, observe, and get your own insights.
The Endgame: The App is the Vehicle, The Data is the Asset
Styl AI wasn’t acquired for its UI, MAUs, or brand. It was acquired for its proprietary dataset.
The Founder Insight: Know what business you’re really in. Dhruv was never building a shopping app. He was building a data company disguised as a consumer product. That clarity shaped every decision, from UX to GTM to acquisition.
The Dhruv Bindra Checklist for Founders
- Target Niche Leaders: Win over influencers first.
- Master Your Platform: Don’t just post, study the mechanics.
- Validate with a Service Model: In India, start as an agency, then productize.
- Invest in Defensible Tech: Datasets and deeptech create moats.
- Stay Objective: Know when to exit and move to the next play.
The Styl AI story is a reminder: the most powerful companies aren’t just built on clever apps. They’re built on relentless creativity, disciplined execution, and an obsessive focus on building assets others can’t easily replicate.