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Palo Alto, California. Summer 2015.
Ray Zhou and Shubham Goel have just finished their sophomore year at Stanford. They're supposed to be studying computer science. Instead, they're spending twelve weeks interviewing fifty professionals—venture capitalists, investment bankers, consultants, dealmakers.
Every interview follows the same pattern. Zhou asks about their work. Goel takes notes. And without fail, the conversation turns to the same frustration.
"I have thousands of relationships," one VC tells them. "I can't remember who introduced me to whom. I can't track which deals came from which connections. I'm supposed to be in the relationship business, and I'm drowning in my own network."
A private equity partner says something similar: "My inbox is a graveyard of missed follow-ups. There are people I should have called back three months ago. I don't even know who I know anymore."
An investment banker confesses: "I manually log every meeting into our CRM. Then nobody looks at it. It's administrative theater."
Fifty interviews. Same problem.
Zhou looks at Goel. "Software exists for transactional relationships—sales pipelines, customer support tickets. But what about relationship journeys? The long-term connections that dealmakers live on?"
There's software for everything else. Why not this?
They walk out of that summer with a conviction: someone needs to build a CRM that automatically understands your relationships. That captures the "data exhaust" from emails and calendars. That knows who you know before you have to remember.
The two Stanford roommates are about to drop out and build it themselves.
The Bay Area Kid and the Delhi Kid
Ray Zhou grew up in the Bay Area—surrounded by technology, steeped in Silicon Valley culture. Shubham Goel grew up in New Delhi, a world away.
"We became close friends well before founding the company," Zhou later reflected. "It was such an improbable encounter—me having spent my whole life in the Bay Area while Shubham grew up in New Delhi."
They met at Stanford. Different backgrounds, same obsessions: technology, society, how systems shape human behavior. They built side projects together. They debated ideas late into the night.
By the time they decided to start a company, they'd already proven they could work together.
The Stanford Ecosystem
Stanford wasn't just where they met—it was where they got their first support.
They became fellows at The Garage, a program run by Pear Ventures for entrepreneurial Stanford students. The program gave them space to explore, mentorship to sharpen their thinking, and the permission to take their summer of interviews seriously.
The Garage was designed to turn Stanford students into founders. Zhou and Goel were exactly what they were looking for.
The Insight: Everyone Manages Relationships for a Living
Zhou and Goel's insight was deceptively simple: the most valuable professionals—VCs, dealmakers, consultants—manage relationships for a living. Their network is their competitive advantage.
But their tools were terrible.
Salesforce was built for sales teams closing transactional deals. It assumed you'd manually enter every interaction, every note, every follow-up. It was a "system of record" that required constant feeding.
For relationship-driven professionals, this was backwards. You couldn't manually track thousands of relationships. You needed a system that understood your relationships automatically.
The Technical Challenge
What Affinity set out to build was ambitious:
- Integrate with email and calendar
- Automatically capture every interaction
- Analyze patterns to understand relationship strength
- Surface insights about who you know and how
This wasn't a simple database. This was relationship intelligence—using data to understand human connections.
The engineering was hard. Email parsing is messy. Calendar data is inconsistent. Privacy concerns are real. Building something that felt helpful rather than creepy required careful design.
First Customers: Venture Capital
The first market made sense: venture capital.
VCs live on relationships. They meet hundreds of founders. They track deals for years before investing. They rely on networks for introductions, references, and deal flow.
And VCs are willing to pay for tools that give them an edge.
Affinity's early customers were VC firms who immediately understood the value proposition: stop manually logging meetings, start understanding your network automatically.
The Recognition
Zhou and Goel made Forbes 30 Under 30—validation that their bet on relationship intelligence was resonating.
More importantly, the company grew. What started with VC firms expanded to private equity, investment banking, commercial real estate, professional services. Any industry where relationships drove deals.
The Funding
The funding rounds scaled with the ambition:
- $10 million Series A (2019)
- $80 million Series C (2021)
By the Series C, Affinity had built a "late eight figures" revenue business—extraordinary growth in the crowded CRM category.
The Positioning
Affinity carved out a distinct position: relationship intelligence for deal makers.
Not Salesforce (too transactional, too manual).
Not HubSpot (too focused on inbound marketing).
Not traditional CRM at all.
Instead: a system that understood your relationships before you asked it to.
The Platform Expansion
Affinity expanded beyond basic relationship tracking:
- Integration with dozens of data sources
- Team collaboration features
- Deal pipeline management
- Automated data enrichment
The core insight—automatically capture relationship data—remained central. But the platform grew to handle the full workflow of deal-driven teams.
Ray Zhou and Shubham Goel Today
Zhou serves as CEO, Goel as President. The Stanford roommates who spent a summer interviewing professionals are now running a company that serves thousands of them.
The Lesson
Affinity's origin story is a reminder that the best companies often come from listening, not inventing.
Zhou and Goel didn't dream up relationship intelligence in a vacuum. They spent twelve weeks interviewing people who managed relationships for a living. They heard the same pain over and over. They built what everyone was asking for.
The insight wasn't technical. It was human: everyone believes their relationship should work for them, not the other way around.
Two Stanford roommates—one from the Bay Area, one from Delhi—figured out how to make that happen.
