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Company's Profile

Established: 2023
Line of Business: Cyber
Address: 488 Madison Ave
New York , NY 10022
Email: [email protected]
Website: http://www.nagomisecurity.com
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Company Executives

  • Emanuel  Salmona, Nagomi Security

    Emanuel Salmona

    Co-Founder & CEO

    Nagomi Security

  • Shai  Mendel, Nagomi Security

    Shai Mendel

    Co-Founder & CPO

    Nagomi Security

  • Jonathan  Maler, Nagomi Security

    Jonathan Maler

    Co-Founder & CTO

    Nagomi Security

Leading Executives

    Nir Fuchs, VP R&D
    Stav Raz Arad, VP HR
    John Schmitz, SVP Sales
    Alexei Rubinstein, VP Customer Experience
Icon About

About Nagomi Security

Nagomi is a cybersecurity company that has built a new operating model for defense in the age of AI. Traditional defense tools were built to manage lists of exposures - scan, score, report, and patch - a model designed to demonstrate regulatory compliance, not to stop attackers. Now that offense has lost its speed limit, and the path from disclosure to working exploit has collapsed from weeks to hours, the list is no longer the right unit of work.
Nagomi replaces the list with a loop: autonomous AI agents that detect, validate, neutralize, and verify the closure of real exposures - continuously, and from within the security tools an organization already owns. Instead of managing risk, Nagomi operates it away to neutralization. The company’s promise: do less, and be ahead of your time.

Vision and Strategy

Nagomi operates from the conviction that the core cybersecurity problem is not a shortage of tools, nor a patch list that runs too slowly - it is that the existing exposure-management model was never built to stop a breach. You can be 100% compliant and breached the same afternoon; nearly every major breach of recent years struck an organization that had a mature exposure-management program in place.
The company aims to lead the shift from “managing exposure” to “operating exposure” (Agentic Exposure Operations): from a reactive, list-based model to an autonomous, continuous one in which every security decision is measured against a single question - was the attack path actually broken? At the heart of this approach is one assumption: in an era where offense is driven by AI, defense must be driven by AI as well. AI is not a feature added to the model - it is the model itself.

Product and Technology

The Nagomi platform is built on more than 100 read-only integrations with the organization’s existing security tools, unifying data from disparate sources - assets, controls, vulnerabilities, and threats - into a single context layer and a single decision. On top of this layer, a team of autonomous AI agents (“AI Exposure Eliminators”) runs in a continuous loop:
Detect - continuous, real-time monitoring of every change in the environment.
Investigate and validate - an agentic verdict on every signal: criticality, threat intelligence, the controls in place, and real-world exploitability, with under 4% false positives.
Neutralize - blocking the attack path using compensating controls the organization already owns, before a patch even exists.
Validate - confirming the exposure is actually closed, and re-checking when the context shifts.
Autonomy is earned, not granted by default: the agents build the case, the organization approves the fix in a single click, and the system proves it held. This frees the team from the 95% of work it never needed to touch - five people with the coverage of fifty.

Key Areas of Activity

• Exposure Detection & Response - a continuous, agentic operating model
• Full-context exploitability validation - not “does an exposure exist” but “can it be exploited on this asset, right now, given the controls actually in place”
• Exposure neutralization via compensating controls - blocking the path before the patch
• Agentic autonomy with human approval and one-click remediation
• Unifying assets, controls, threats, and vulnerabilities into a single context and decision layer
• Verified validation and closure - proof that the attack path was actually broken

 

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