A next-gen personal security platform from a founding team that spent a decade turning "uninsurable" human behavior into a quantifiable, insurable category — now pointed at protecting people.
Protecting a human today means a patchwork of apps, alarms, guards and gut instinct. None of it is modeled, priced, or predictive. The market is waiting for a team that can turn personal risk into a quantifiable, defendable score.
Stalking, doxxing, swatting, executive & family targeting, AI-enabled impersonation. The risk lives in behavior and exposure — not just locks and cameras.
Personal protection is sold on fear, not data. There is no trusted "risk score" for a human, no underwriting layer, no predictive early-warning.
Guards, monitoring apps, identity-theft tools, and insurance all sit in silos. Nobody owns the unified, data-driven layer.
Deepfakes and automated harassment scale attacks. Defense has to be predictive and data-native — exactly the kind of system this team builds.
This is not a first-time team learning the category on someone else's dime. They built the data engine that scores how individual humans behave — and the underwriting layer that turns those scores into insured, bankable products.
An engineer- and analyst-heavy org culture. Models and defensibility come first; features second.
Comfortable with MGAs, reinsurers and Lloyd's capacity — the relationships a protection-plus-insurance product needs.
Sold a brand-new category into conservative buyers before. They can sell trust, not just software.
Predictive analytics scoring trust, likability and risk of public figures for brands like Nike, Neiman Marcus and H&M. The team's first human-behavior risk engine.
Turned behavioral scores into underwriting: model the likelihood a person disgraces themselves, then insure the brand against it — capacity from Lloyd's.
Built a "Civil Authority Shutdown Likelihood" score with almost no historical data. The line ran profitably at the height of COVID — proof the team models emerging risk fast.
Continued work at the intersection of analytics and insurance — exactly the muscle a personal-security platform needs.
Co-founder and CEO of Spotted / SpottedRisk — the company that built the data engine for predicting how individual humans behave and turned it into an insurance category.
B.A., University of Pennsylvania. Varsity women's tennis — a competitor's temperament.
Forbes 30 Under 30; "20 Women in Technology," Accomplice Ventures (2015).
Still building in risk — insurance + analytics, next chapter.
A sales-leader-turned-founder who broke into insurance "with no prior experience." Personal security is a trust sale — she has closed exactly that kind of sale before.
Comfortable with Lloyd's, MGAs, and reinsurers. A security platform can bundle protection + insurance; she already owns those relationships.
D1-level athlete, Forbes 30U30. The grit to build a hard, regulated, trust-heavy category from zero.
"We spot underserved opportunities and underwrite them analytically." That is the exact instinct human-security needs.
"We wanted to create a new type of company that uses analytics to develop products for risks the market deems uninsurable — and underwrite them in a rigorous, analytical way."
SpottedRisk is a personal-security platform pointed at brands. Re-point the same engine and the same team at the individual, and the fit is almost one-to-one.
A platform that scores, predicts, and protects an individual the way SpottedRisk scored a public figure — continuously, quantitatively, and with a financial backstop.
A live, per-person index from exposure, behavior, digital footprint and threat signals. The credit score of physical & digital safety.
Model emerging threats — doxxing, stalking escalation, impersonation — before they hit, using proxy + real-time data.
Connected services: monitoring, takedowns, guards-on-demand, identity defense — orchestrated by the score.
Underwrite personal-harm and reputation risk on top of the score. The revenue moat incumbents can't copy.
From consumer to UHNW / executive protection — natural up-market expansion, just like brand → enterprise.
Every protected human sharpens the models. Defensibility compounds — the team's favorite kind of moat.
Scoring humans invites scrutiny. Mitigant: the team has already navigated reputational/behavioral data responsibly at scale, with legal & PR sensitivity baked in.
Confirm the financial outcome and current status of Spotted/SpottedRisk and the team's current commitments before a formal ask.
Personal security can skew niche/UHNW. Validate the consumer wedge vs. starting top-down with execs & families.
The real question for Jeff: is this team catalyzable into this, and in what roles — founders, operators, or advisors?
None of these are disqualifying. They're the agenda for the first real conversation.
This team spent a decade learning to score, predict and insure human risk. A next-gen personal security platform is that same engine — finally pointed at the person instead of the brand. That's not a pivot for them. It's a homecoming.
Warm intro / reconnect — frame it as "Human Security 2.0," their thesis applied to people.
Share this deck + a one-page vision; gauge appetite and ideal roles.
Scope a 4-week team-fit sprint: market wedge, model spec, capital plan.