Trellix Launches Private Cloud Cybersecurity Tool

The new Trellix Wise for Private Cloud platform offers automated threat investigation without using public AI models.

Updated on Oct. 23, 2026 in Cybersecurity

Trellix Launches Private Cloud Cybersecurity Tool

Live Poll

Should federal agencies trust autonomous artificial intelligence systems to make critical cybersecurity defense decisions?

Trellix has released a new cybersecurity product, Trellix Wise for Private Cloud, designed to operate entirely within secure, disconnected, or air-gapped network environments. By keeping all data processing and AI investigation inside customer security boundaries, the tool avoids sending sensitive information to public large language models.

Why it matters

Federal agencies and private entities require security solutions that can function in isolated environments while maintaining strict data sovereignty. This tool automates evidence collection and alert correlation to help reduce the heavy workload currently placed on security analysts.

The system utilizes 40 years of proprietary threat intelligence to automate evidence gathering and alert correlation. Unlike standard AI tools, it employs predictable pricing rather than a token-based consumption model.

The players

Trellix

Headquartered in Frisco, Texas, this company provides extended detection and response solutions for enterprise and government security operations.

The details

Trellix Wise for Private Cloud connects existing security investments to perform autonomous investigations within air-gapped and hybrid networks. Organizations retain full control by establishing their own permissions and operational boundaries for all autonomous agents.

October 13, 2026: Trellix announced the new product.
October 15, 2026: Trellix Wise for Private Cloud became generally available.

The Tech Race

This release reflects an industry shift toward air-gapped AI solutions that avoid the security risks associated with public large language models. It positions Trellix against competitors relying on cloud-based AI by prioritizing strict on-premises data sovereignty.

Security teams can expect reduced manual workloads as the system automates alert correlation and evidence gathering processes. The shift to predictable pricing allows organizations to budget for cybersecurity costs without worrying about fluctuating token-based usage fees.

The takeaway

Organizations operating in sensitive environments can now leverage AI-driven automation without exposing proprietary data to the cloud. Analysts should look to integrate these autonomous agents to prioritize high-value alerts while maintaining complete control over network boundaries.