HomeNyne, founded by a father-son duo, fills AI agents' human context gap
AI agents are on track to soon begin making autonomous purchasing and scheduling decisions for humans.
Michael Fanous, a UC Berkeley computer science graduate and former machine learning engineer at CareRev, argues that these agents still lack a crucial component: the full context needed to genuinely understand the people they are designed to assist.
Fanous points out that today's machines struggle to determine whether a person's LinkedIn profile, Instagram activity, and public government records all refer to the same individual.
To address this, he partnered with his father, Emad Fanous, an experienced CTO, to create Nyne—a startup that aims to serve as the intelligence layer enabling agents to understand humans across their complete digital footprint.
On Friday, Nyne announced it had raised $5.3 million in seed funding, led by Wischoff Ventures and South Park Commons, with participation from several angel investors, including Gil Elbaz—co-founder of Applied Semantics and a pioneer of Google AdSense.
While it might appear that Nyne is solving a problem already addressed by classic machine learning—given how effectively Google’s ad targeting identifies its users—CEO Michael Fanous disagrees. He explains that Google’s “secret sauce” lies in its exclusive access to users' search histories and cross-platform activity, a data advantage the tech giant will never share with external agents.
For everyone else, “this is an oddly hard problem to solve,” explained Nichole Wischoff, founder of the solo VC fund Wischoff Ventures, which backed the deal.
Fanous told TechCrunch that Nyne addresses the problem by deploying millions of agents across the internet to analyze public digital footprints, then applying machine learning techniques to that data.
Nyne can triangulate information about a person by examining not only major social networks like Instagram, Facebook, and X, but also their activity on apps such as SoundCloud and Strava.
Later, as more consumer-facing companies deploy AI agents, they can use Nyne to give those agents a deeper, real-world understanding of both existing and potential customers.
“I can provide any piece of information about a person that could be useful for making the right next move,” Fanous said. “Once you make all these connections, you can understand a person fairly deeply—their interests, hobbies, and how they think about very specific topics,” he added.
According to Wischoff, the market for this data is huge and valuable to any company using AI agents to engage with customers.
“How do I know you’re pregnant and sell you A, B, or C as early as possible?” she said.
While previous generations of ad tech companies could gather some of this data, Nyne aims to do so for the world of agents with far greater precision.
As for how the father-son duo works together, the CEO says he has an ideal partnership with his CTO—and his dad.
“I think with co-founders, it becomes easy to walk away when things don’t work out,” Fanous said. “If I have to ping him at three in the morning to finish a launch, I know he’ll still love me the next day.”
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AI agents are on track to soon begin making autonomous purchasing and scheduling decisions for humans.
Michael Fanous, a UC Berkeley computer science graduate and former machine learning engineer at CareRev, argues that these agents still lack a crucial component: the full context needed to genuinely understand the people they are designed to assist.
Fanous points out that today's machines struggle to determine whether a person's LinkedIn profile, Instagram activity, and public government records all refer to the same individual.
To address this, he partnered with his father, Emad Fanous, an experienced CTO, to create Nyne—a startup that aims to serve as the intelligence layer enabling agents to understand humans across their complete digital footprint.
On Friday, Nyne announced it had raised $5.3 million in seed funding, led by Wischoff Ventures and South Park Commons, with participation from several angel investors, including Gil Elbaz—co-founder of Applied Semantics and a pioneer of Google AdSense.
While it might appear that Nyne is solving a problem already addressed by classic machine learning—given how effectively Google’s ad targeting identifies its users—CEO Michael Fanous disagrees. He explains that Google’s “secret sauce” lies in its exclusive access to users' search histories and cross-platform activity, a data advantage the tech giant will never share with external agents.
For everyone else, “this is an oddly hard problem to solve,” explained Nichole Wischoff, founder of the solo VC fund Wischoff Ventures, which backed the deal.
Fanous told TechCrunch that Nyne addresses the problem by deploying millions of agents across the internet to analyze public digital footprints, then applying machine learning techniques to that data.
Nyne can triangulate information about a person by examining not only major social networks like Instagram, Facebook, and X, but also their activity on apps such as SoundCloud and Strava.
Later, as more consumer-facing companies deploy AI agents, they can use Nyne to give those agents a deeper, real-world understanding of both existing and potential customers.
“I can provide any piece of information about a person that could be useful for making the right next move,” Fanous said. “Once you make all these connections, you can understand a person fairly deeply—their interests, hobbies, and how they think about very specific topics,” he added.
According to Wischoff, the market for this data is huge and valuable to any company using AI agents to engage with customers.
“How do I know you’re pregnant and sell you A, B, or C as early as possible?” she said.
While previous generations of ad tech companies could gather some of this data, Nyne aims to do so for the world of agents with far greater precision.
As for how the father-son duo works together, the CEO says he has an ideal partnership with his CTO—and his dad.
“I think with co-founders, it becomes easy to walk away when things don’t work out,” Fanous said. “If I have to ping him at three in the morning to finish a launch, I know he’ll still love me the next day.”
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