Personam | Origin Story

Personam began with a stark realization:

Even the world’s best-funded cybersecurity teams were losing ground, despite using the most advanced tools available.

The founding team spent decades designing and operating highly secure government and intelligence-community networks. After a major breach, they built a world-class defensive system. It worked, but only at a scale and cost that a handful of agencies could sustain. Meanwhile, organizations everywhere continued to suffer breaches using conventional security tools.

At the same time, a breakthrough emerged in behavioral AI. The new approach abandoned signatures, rules and pre-trained attack models in favor of learning how real networks actually behave. Best of all, this approach could instantly detect anything that didn’t belong.

When the founding team compared this behavioral approach to the rule-based tools dominating the NDR market, the gap was undeniable. Traditional platforms were noisy. They were labor-intensive, slow to adapt, and consistently missed novel attackers, insiders, and credential-based threats. Average attacker dwell time remained measured in weeks or months.

The team knew the industry needed a fundamentally different model: one built on autonomous learning, not human-authored assumptions.

Personam was built to deliver that change.

Today, Personam’s patented AI autonomously learns how every entity operates across the network, cataloging more than 200 behavioral attributes per asset. It identifies real threats in real time: insiders, lateral movement, reconnaissance, beaconing, bots, malware and adaptive adversarial tradecraft.

No rules.

No tuning.

No thresholds.

No false positives.

Mission:

To eliminate cyber threats and make the internet safe by delivering autonomous, real-time threat detection once reserved only for the world’s most sophisticated government agencies.

Personam is the always-on autonomous threat-hunting partner that finally gives defenders back the advantage.