As automation, dashboards, and predictive models become more common, leaders are starting to ask a key question: What happens to human relationships when everything is reduced to data?
For Dr. Masoud Nafey, who has founded three A.I. companies and advises a global wealth fund, this question is practical. It led him to create Ment, a platform that helps leaders manage complexity while keeping the personal connections that build trust and long-term value.
“I don’t believe in a self-made this or a self-made that. I believe that the network around you and the relationships you have get you to where you are and shape you as a human,” Nafey told the California Business Journal in an exclusive interview.
His belief comes from his early life. Nafey moved to the United States at age five with nothing. That experience still shapes how he thinks about access, opportunity, and what drives success. “A lot of the ability to be where I am today is because of the people I’ve met, the people I’ve surrounded myself with, and the trust I’ve built with them,” he said.
From charisma to context
Ment was not designed as a typical social platform or just another productivity tool. It started with a moment that changed how Nafey thought about leadership and memory.
He recounts a story involving one of Ment’s board members meeting President Barack Obama for the first time while President Obama was in office. “It was probably the 50th person the President met with that day. And he knew something so personal. He said, ‘Whenever you get healthy again, and your knee feels better, maybe we’ll see each other on the basketball court sometime,’” Nafey said.
Nafey says that moment showed him something important. “We can’t make people more charismatic, but we can make charismatic people better and give them the right information, at the right time, with the right context.” He built Ment to put that idea into practice.
A live contact book for modern leaders
Ment works as what Nafey calls “a live contact book.” It gathers public information in real time from professional, social, and media sources, then filters it to show what matters for each relationship.
“You already have your contacts. Now, you can’t keep in touch with all your contacts. The problems are real: too many relationships, not enough time, too much data, not all data is relevant.”
Ment does not overwhelm users with data. It shows only the most important insights of what it collects. “We only display like five percent of it. Because there’s so much extra, too much irrelevant information.”
This approach is on purpose. Each relationship needs a different view. “Maybe you want a business relationship with someone, so you want a business persona aggregated. But with somebody else, you want a personal relationship. You want to become a better friend, who remembers important milestones in their lives. So you can prompt Ment to give you that kind of data.”
Built on public data — and strict privacy
Ment relies primarily on open-source intelligence. It aggregates publicly available information that already exists online. Nafey is explicit about what the platform does not do. “We don’t buy data anywhere at Ment. Everything we do, we collect in real time from public sources.”
Equally important is what Ment does not touch. “We don’t ask for access to your Instagram, your LinkedIn, your text messages, your emails. Ment doesn’t need any information like that. It’s privacy by design.”
That philosophy extends to what Nafey calls sacred information: Private notes and insights users add to themselves after meeting someone. “Our own team can’t even look at that data. Nobody else gets that information, and we don’t reuse it for anyone else.”
Teaching A.I. what actually matters
Before writing a single line of code, Nafey and his team focused on human behavior rather than software architecture. “We did psychological studies with PhDs. We wanted to understand how people interact when they meet. What makes someone bring their guard down? What builds trust quickly?”
Only after answering those questions did Ment’s technical framework take shape. “That’s the magic. Now we know what to collect, and we’re constantly teaching our A.I. agents what is most important for our users.”
The system is built for relevance, not volume. “At first glance, with just a first name, last name, and one additional data point, we have about 95 percent accuracy,” Nafey said.
A.I. without the hype
As artificial intelligence attracts record investment and heightened expectations—despite many applications still struggling to translate spending into returns—Nafey takes a pragmatic view of its risks. “The risk is what people invest in and how much they invest. But the fundamental technology—machine learning, complex algorithms—that stuff works. It’s worked for years.”
He points to experience. “My first A.I. company was in 2014. It cost me five million dollars to build. I can build it for under fifty thousand today,” Nafey said. His trajectory reflects the logic of Moore’s Law—the long-observed pattern that the number of transistors on an integrated circuit roughly doubles every 18 to 24 months, driving exponential gains in computing power while sharply reducing the cost per unit. While not a formal axiom, Moore’s Law continues to describe the underlying tempo of technological development with striking consistency.
Ment, Nafey adds, is model-agnostic. “We can work with public models, private models, or build a private A.I. model for a client. There’s no bubble around the technology. The bubble is around expectations.”
Institutionalizing relationships
Ment operates strictly as a B2B platform, a choice driven by how relationships scale inside organizations. Nafey poses a common scenario: “Are my top salespeople so good because of relationships? If they leave, what’s at risk? All those relationships.”
The solution, he says, is continuity. “What if you could institutionalize relationships even though the person is no longer there?”
That logic extends to investors, executives, and public-sector leaders. “When you get beyond simply looking up an individual, it becomes: here’s my network, what introductions should be made, and where the missed opportunities are,” Nafey said.
People data as the missing layer
For Nafey, the broader implication goes beyond Ment itself. “Organizations always forget people’s data. They say, here’s our revenue, our transactions, our numbers. They forget there’s a person who signed on the dotted line and a person who sold.”
That oversight, he argues, limits strategy. “Did we even match the right people in our organization with the right people in theirs? People data is the hidden gem.”
Ment’s stated goal is straightforward. “Our goal is to empower you with up-to-date, relevant, accurate, contextual insights with the people you meet and the people you want to create bonds with,” Nafey says. “Because ultimately, if they like you, they’re more likely to do business with you.”
As automation accelerates, Ment’s wager is explicit: That in a world optimized for machines, the leaders who win will be the ones who use A.I. to remember, strengthen, and institutionalize human relationships—not replace them.
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