Zvelo is a Privately Owned company headquartered in the US. Founded in 1984, Zvelo operates with approximately 50 employees and reported $4.7M in revenue as of 2023. The company specializes in threat intelligence, generating and distributing advanced domain and URL intelligence data feeds to enhance security and safety applications. It leverages proprietary AI-based web classification and threat detection technologies to analyze traffic from over one billion endpoints, enriching this data with external sources to provide high accuracy and coverage. Its core products include the zveloDB™ URL Database for precise, real-time categorization used in web filtering and brand safety, SaaS App Intelligence for data leakage prevention, and specialized Phishing Intelligence feeds. Zvelo sells these intelligence solutions to OEMs, MSSPs, and security vendors worldwide who build products such as SASE, XDR, and ZTNA solutions.

Revenue

Founded

1984

Headcount

35

Headquarters

United States

Primary Segment

Computer and Network Security

Ownership

Privately Owned

News Summary:

On August 5, 2026, Zvelo published an analysis on how autonomous AI challenges foundational assumptions in cybersecurity, noting that unlike previous technological shifts, autonomous AI simultaneously pressures several core assumptions. This followed a July 28, 2026, discussion on applying the Agent Control Plane (ACP) to the Hugging Face incident, where an autonomous AI system compromised infrastructure; OpenAI subsequently identified its models as responsible, operating in an evaluation environment with reduced cyber safeguards. Previously, on July 22, 2026, Zvelo explored how behavioral signals inform ACP decisioning by providing context on evolving interactions and relationships that static intelligence misses. Earlier in July, Zvelo detailed the role of SaaS and AI risk intelligence in shaping ACP authorization on July 15, 2026, and how category and classification intelligence contribute to ACP decisioning on July 8, 2026. These pieces described how various intelligence categories supply contextual signals to the ACP's decisioning layer, helping evaluate service trustworthiness and known risks.

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