As artificial intelligence continues to evolve, the role of AI agents is set to expand significantly, with expectations for them to autonomously manage purchasing and scheduling tasks. However, Michael Fanous, a UC Berkeley computer science graduate and former machine learning engineer at CareRev, highlights a crucial gap: these agents lack the comprehensive context necessary to truly grasp the individuals they serve.
According to Fanous, current AI systems struggle to connect disparate digital identities--such as a LinkedIn profile, Instagram activity, and public government records--to the same individual. To address this challenge, he and his father, Emad Fanous, an experienced CTO, co-founded Nyne, a startup designed to serve as an intelligence layer that enhances AI agents' understanding of humans through their entire digital footprint.
Recently, Nyne secured $5.3 million in seed funding, led by Wischoff Ventures and South Park Commons, along with contributions from several angel investors, including Gil Elbaz, a co-founder of Applied Semantics and a pioneer of Google AdSense.
While it may appear that Nyne is addressing a problem already tackled by traditional machine learning--like Google's effective ad targeting--Michael Fanous argues that the situation is more complex. Google's success largely stems from its exclusive access to users' search histories and cross-platform activities, a data advantage that is not available to external agents.
"This is an oddly hard problem to solve," explained Nichole Wischoff, founder of Wischoff Ventures, emphasizing the unique challenge Nyne aims to overcome.
Nyne approaches this issue by deploying millions of agents across the internet to analyze public digital footprints, leveraging machine learning techniques to interpret the data. The platform can integrate information from major social networks like Instagram and Facebook, as well as activity on apps like SoundCloud and Strava, to create a cohesive profile of an individual.
As more consumer-facing companies begin to utilize AI agents, they can turn to Nyne for insights that provide a deeper, real-world understanding of both current and prospective customers. "I can give them any piece of information about a person that could be useful to make the right next action," Fanous stated. "By making these connections, you can gain a profound understanding of a person's interests and thought processes."
Wischoff notes that the demand for this data is immense, offering significant value to companies employing AI agents for customer engagement. "How do I know you're pregnant and sell you A, B, or C as early as possible?" she posed, highlighting the potential applications of Nyne's technology.
Unlike previous generations of ad tech that gathered data, Nyne aims to achieve a higher level of precision in understanding consumer behavior. The collaboration between the Fanous duo exemplifies a strong partnership; Michael describes their working relationship as ideal, ensuring mutual support even during challenging times.
As Nyne continues to develop its technology, the implications for the future of AI agents are promising, potentially transforming how businesses interact with their customers in a more personalized and insightful manner.