Nyne, launched by a father-son team, aims to add human context to AI agents

AI agents are widely expected to begin making autonomous decisions on behalf of people, including purchases and scheduling tasks. However, Michael Fanous — a computer science graduate from UC Berkeley and former machine learning engineer at CareRev — believes these systems still lack a crucial element: the depth of context needed to understand the individuals they are designed to serve genuinely.

Fanous points out that current AI systems often struggle to determine whether different digital profiles — such as a professional account on LinkedIn, social activity on Instagram, and publicly available government records — all correspond to the same individual.

To address this challenge, he partnered with his father, Emad Fanous, an experienced CTO, to create Nyne. The startup aims to function as an intelligence layer that enables AI agents to better interpret human identity by connecting information across a person’s entire digital footprint.

On Friday, Nyne revealed that it has secured $5.3 million in seed funding. The round was led by Wischoff Ventures and South Park Commons, with additional backing from angel investors including Gil Elbaz, co-founder of Applied Semantics and a key figure behind Google AdSense.

At first glance, Nyne’s approach might seem similar to what traditional machine learning systems already accomplish — particularly considering how effectively companies like Google tailor ads to users. However, CEO Michael Fanous argues that this comparison misses an important point. Google’s advantage lies in its access to proprietary user data, including search histories and cross-platform behaviour, which it does not share with external AI systems.

For other companies, replicating that level of insight remains a significant challenge. Nichole Wischoff, founder of the venture firm Wischoff Ventures, described the problem as surprisingly difficult to solve, despite advances in machine learning.

According to Fanous, Nyne approaches the issue by deploying millions of AI agents across the web to examine publicly available digital footprints. These agents then use machine learning models to process and connect the data.

The platform can piece together information about individuals by analysing activity not only on major social platforms like Instagram, Facebook, and X but also across niche applications such as SoundCloud and Strava.

As more businesses begin integrating AI agents into customer-facing roles, Nyne aims to provide those systems with a more comprehensive and realistic understanding of both existing users and potential customers.

Fanous explained that the system can supply agents with any relevant data point that might help determine the most appropriate next action. By connecting multiple data sources, Nyne enables a deeper understanding of a person’s interests, habits, and decision-making patterns.

From an investor perspective, Wischoff believes the potential market for this type of data is substantial, particularly for companies looking to use AI agents to engage with customers in more targeted ways.

She illustrated the potential by pointing out how valuable it would be for businesses to identify life events or needs early — allowing them to tailor offerings with greater precision.

Earlier generations of advertising technology collected fragments of this data. Nyne aims to refine and expand that capability for AI-driven systems, delivering higher accuracy and insight.

On the personal side of the business, Fanous described his relationship with his father as a strong, reliable partnership. He noted that, unlike typical co-founder relationships where disagreements can lead to separation, their bond adds an extra layer of commitment.

He added that even in demanding situations — like needing help in the middle of the night to complete a product launch — he knows his father will be there and that their relationship will remain intact beyond the pressures of building a company.