Vectorial AI Beat OpenAI by 30% at Predicting Human Behavior | Vectorial AI Founders | AI Unfiltered Ep3

Every founder has that one product moment that keeps them up at night.

The launch you thought would take off—crickets.The feature you were sure people would love—ignored.The funnel that fell apart the second real users touched it.

Product development has always had this ugly truth baked into it: You build in the dark, and you pray you guessed right.

But what if you didn't have to?

What if you could see how thousands of real people would react to your product before you waste months building it?

That's not a fantasy. That's Vectorial AI.

And the story of how it came to exist will change how you think about building products forever.

The 10-Year Wait Nobody Talks About

This story doesn't start in a Stanford lab. Not in a VC meeting. Not in a slick product roadmap.

It starts with paperwork.

Visa deadlines. Uncertainty stretched over years. Building a career and a dream in a country that asks you to constantly prove you deserve to be there.

Taranveer Singh spent 10 years waiting to start his company. Not because he lacked vision—he was modeling population behavior for India's Defense Department and building AI agents at Chegg before they became a buzzword.

He waited because as an immigrant founder, the cost of failure meant survival. One visa mistake, and it's back to square one.

Jasmine Kaur's path was equally unconventional: aerospace research → reaching 75 million people in healthcare → Stanford Business School → deep tech entrepreneurship.

Most people see an immigrant founder's highlight reel. They never see the years in limbo. The lives paused. The opportunities missed because timing wasn't yours to control.

That's where their patience got forged—in the waiting, the grinding, the "not yet."

And that patience? It became their superpower.

They Were Building the Answer Before They Knew the Question

Before Vectorial, they were building models that predicted how populations behave—in education, in defense, in enterprise environments where being wrong wasn't an "oops"… it was a problem.

That kind of work trains you differently.

You stop guessing. You stop assuming. You start hunting for signal, and you don't move until you find it.

While most of Silicon Valley was playing with prototypes, these two were quietly learning how to map human behavior at scale.

They were building the foundation long before the company had a name.

And then they saw it: Every product team was making the same fatal mistake.

The $38 Billion Problem Hiding in Plain Sight

MIT found that 95% of enterprises see zero ROI on AI investments.

Why?

Because companies build 10x faster with AI but still validate painfully slow with users.

• Months of user research

• Hit-or-trial experiments

• Stroke-of-luck product-market fit

• Features that die on contact with reality

"We'll find out once it's live."

That sentence has killed more good products than bad ideas ever did.

Teams don't struggle with building. They struggle with seeing.

Seeing reactions. Seeing friction. Seeing how real people move through an idea—not how we want them to move.

Vectorial was built to solve the root problem: certainty.

What If You Could Test Your Product With 5 Billion People Before Launch?

Here's what makes Vectorial different from every other "AI product tool" you've heard of:

They built synthetic users that replicate real human behavior with 84% accuracy—30% better than leading LLMs like OpenAI.

Not personas. Not stereotypes. Not shallow user profiles.

Actual behavior patterns grounded in large-scale public and enterprise data.

Their AI system, SAPIENS, models how people think, feel, and act. It's the difference between understanding what people know versus understanding what they'll actually do.

What This Means for Product Teams:

✅ Test in days, not months — No more waiting for user research cycles

✅ Catch weak concepts early — Before they consume your roadmap

✅ Explore thousands of personas — Including long-tail segments you'd never reach

✅ Validate across the entire lifecycle — Features, onboarding, messaging, pricing, PLG workflows

Imagine seeing user reactions before the code exists.Imagine watching ten different versions of a flow play out before design even opens Figma.Imagine removing the guessing game entirely.

That's what they built.

This Isn't AGI. It's Something More Important: BGI

Everyone's obsessed with AGI (Artificial General Intelligence)—teaching AI to understand the world's knowledge.

But Taranveer and Jasmine are building something fundamentally different: Behavioral General Intelligence (BGI).

BGI is the third branch of AI:

• AGI = World's knowledge

• World Models = Physics simulation

• BGI = Human behavior modeling

"Simulation is the holy grail," Taranveer says. "Aeronautical and chip industries have had it for decades. Digital products haven't—until now."

This isn't just about product development. BGI has implications for:

• Social science research

• Public policy

• Training foundation models

• Any industry where understanding human behavior is critical

The biggest AI breakthroughs haven't happened yet. And they won't come from the companies everyone's betting on.

The Contrarian Truth Nobody Wants to Hear

OpenAI won't solve behavioral simulation. It requires fundamentally different thinking.

While everyone bets on five or six companies, new opportunities are emerging for the next decade.

Vectorial isn't trying to compete with OpenAI. They're building something OpenAI can't build—because their philosophy is different from the ground up.

They're not chasing hype. They're chasing certainty.

And in a world where 95% of AI investments fail, certainty is the most valuable commodity in tech.

Co-Founding With Your Life Partner

Here's the part that makes this story even more remarkable:

Taranveer and Jasmine are married.

They co-founded Vectorial together. They work together every day. They disagree weekly—sometimes in front of family who've learned to adjust to seeing them "huddle head-first, then 30 seconds later being totally normal."

"Our love language is empowering each other," Jasmine says.

What makes it work?

Complementary skills: Taranveer is a tinkerer who experiments. Jasmine is a strategic thinker who sees long-term vision.

Micro-habits: They leave phones at home for an hour daily—no work talk, just sports or walks together.

Creating space: In investor meetings, if Jasmine isn't being included, Taranveer and their co-founder Rahul pause: "Jasmine, what do you think? We want your pushback."

Most co-founder relationships crack under pressure. These two turned pressure into partnership.

The Immigrant Founder Reality: "It Comes Down to Survival"

"The cost of failure as immigrant founders comes down to survival," Jasmine shares. "If you mess up your visa situation, it means going back to where you started."

Their advice for immigrant founders:

Build support systems. Find other founders who've navigated the journey. Silicon Valley is diverse—lead with your personal story.

Get logistics right first. Taranveer waited a decade to sort immigration, build financial resilience, and find co-founders he could trust.

Be patient and creative. There are unconventional paths. Talk to people. Make yourself vulnerable. The community pays it forward.

"I was patient for 10 years to start," Taranveer says. "My grandparents came with nothing during partition. I don't take this opportunity for granted."

That's the kind of conviction you can't fake. And it's the foundation Vectorial is built on.