About Personam

Seeing What Others Miss

Personam.ai was founded on a single, urgent belief: the threats that matter most are the ones your current tools don't even know to look for. We built our behavioral network detection engine to surface these hidden risks in real time.

Traditional security solutions such as SIEMs, EDRs, and signature-based NDR tools are strongest when they have an identity, an endpoint agent, a known indicator, or a rule to evaluate. But today's attackers don't follow patterns. They adapt. They hide beneath the logs. And they exploit the very systems meant to detect them.

Our Mission

To protect organizations from the threats operating inside their networks, including the ones signature-based products miss.

We do this by delivering a lightweight, self-learning Network Detection and Response engine that operates below the log files, continuously learning the behavior of every entity on your network, users, devices, and applications, to identify when something is acting out of character.

Our Vision

We envision a cybersecurity landscape where every organization, regardless of size, has behavioral-level visibility across its entire network. Attackers are already using automation to move faster than human review. Detection has to learn at the same speed.

Because in the next era of cybersecurity, knowing your own network better than your adversary will be the ultimate advantage.

"Our mission isn't just detection. It's detection in time to act, left of boom."

Our Team

Personam was built by veterans of the commercial and defense cybersecurity sectors, combining decades of experience in behavioral analytics, threat intelligence, and AI-driven detection.

Our engineers and analysts have operated in mission-critical environments where failure is not an option, from national defense to critical infrastructure and Fortune 500 networks. That expertise now powers a commercial-grade product that gives CISOs, SOCs, and MDR/MSSPs security shaped by the standards of those environments.

Who We Serve

What Makes Us Different

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Operates Below the Logs

Personam sees activity that log-based solutions can't, at the network metadata layer, before anything is written to a file.

Self-Tuning

No signatures, thresholds, or rules to author. The model adapts to your environment as it changes.

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Behavioral Intelligence

Learns your unique network patterns, not someone else's dataset. Profiled against your own baseline.

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Agentless Coverage

From servers to cloud to IoT to BYOD, including the devices that cannot run endpoint software.

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Precision Detection

High-signal, prioritized alerts that pinpoint the who, what, when, and where behind each detection.

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Rapid Deployment

Up and running in hours. Deploy sensors where you need visibility and point NetFlow at Personam. DNS and Syslog add context where available.

Why It Matters

Today's adversaries use AI, automation, and stealth to operate below traditional detection layers. They exploit the gaps between your security tools. Personam closes those gaps.

We give defenders visibility into behavior their existing tools were not built to surface. No signatures. No noise. Just a real-time view of what's happening in your network, and what shouldn't be.

Origin Story

Where Personam came from, and why it had to exist.

A defensive system built for environments where a missed detection is unacceptable, and the decision to rebuild it for everyone else.

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.

"The problem wasn't the talent. It wasn't the funding. It was the architecture. Traditional tools were built on the assumption that you already know what to look for."

A Breakthrough in Behavioral AI

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. This approach could surface behavior that did not fit the network it had learned.

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.

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

What Personam Was Built to Do

Today, Personam's patented AI continuously 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.

Talk to a threat detection expert.

See what Personam finds in an environment like yours, in under 30 minutes.

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