LLM.co Launches Private LLM Infrastructure Purpose-Built for Cybersecurity Teams

New offering enables CISOs, security teams, and MSSPs to deploy AI for threat analysis, incident response, and compliance—without exposing sensitive data to public models

Seattle, Washington, United States, January 29, 2026 — LLM.co, a provider of private large language model (LLM) infrastructure for regulated and data-sensitive industries, today announced the launch of its private LLM solutions designed specifically for cybersecurity teams. The new offering allows organizations to apply AI across security operations while keeping sensitive data fully contained within their own environment.

As cybersecurity teams increasingly experiment with AI to improve detection, response, and operational efficiency, many face a fundamental barrier: public AI models are incompatible with security, compliance, and data-governance requirements. Logs, alerts, incident data, and investigative materials cannot be safely shared with third-party AI platforms without introducing unacceptable risk.

LLM.co’s private LLM infrastructure addresses this challenge by enabling fully isolated AI deployments—on-premises, in private cloud environments, or in hybrid configurations—without data ever leaving the organization’s control.

“Security teams want the productivity gains AI offers, but they cannot compromise on data protection,” said Samuel Edwards, Chief Marketing Officer at LLM.co. “Private LLMs eliminate that tradeoff. This is about giving cybersecurity teams modern AI capabilities without creating new attack surfaces or compliance liabilities.”

Built for High-Risk Cybersecurity Workflows

LLM.co’s private LLMs are designed to support real-world security operations, including:

• Threat analysis and alert triage across SIEM, SOAR, and EDR systems
• Incident response support, including playbooks and root-cause analysis
• Security documentation, reporting, and executive summaries
• Policy analysis, compliance mapping, and audit preparation
• Vulnerability and exposure assessment
• Internal security knowledge bases trained on proprietary data

Unlike public AI tools, LLM.co’s models are not trained on customer data, do not log prompts externally, and operate entirely within controlled environments.

“From a revenue and go-to-market perspective, we’re seeing strong demand from organizations that already understand the risks of public AI,” said Timothy Carter, Chief Revenue Officer at LLM.co. “CISOs aren’t asking whether AI will be used in security—they’re asking how to deploy it safely. Private LLMs are quickly becoming the default answer.”

Designed for Enterprise Control and Compliance

LLM.co’s cybersecurity-focused LLM deployments support strict governance requirements, including internal security policies and industry compliance frameworks such as SOC 2, ISO 27001, HIPAA, CJIS, and other regulatory standards. Organizations retain full control over data access, retention, model behavior, and user permissions.

“Sales conversations in cybersecurity are fundamentally about trust and control,” said Eric Lamanna, Vice President of Sales at LLM.co. “Private LLMs allow security leaders to move forward with AI initiatives without pushing risk uphill to legal, compliance, or the board. That alignment is critical for adoption.”

Serving Enterprises, MSSPs, and Regulated Industries

The private LLM offering is designed for:

• Enterprise security teams
• Managed Security Service Providers (MSSPs) and MDR firms
• Financial services, healthcare, government, and critical infrastructure organizations
• Any organization with strict data-handling and confidentiality requirements

LLM.co integrates with existing security stacks and workflows, allowing teams to deploy AI without disrupting established controls or processes.

A Broader Shift Toward Private, Domain-Specific AI

The launch reflects a broader industry shift away from general-purpose public AI toward private, domain-specific LLMs tailored to high-risk use cases. As AI adoption accelerates, organizations are increasingly prioritizing architectures that balance capability with control.

“Cybersecurity is one of the clearest examples of where private AI is not optional—it’s essential,” Edwards added. “This launch formalizes what many security leaders already know: if AI touches sensitive security data, it must be private by design.”

About LLM.co

Created by DEV.co, LLM.co provides private, secure large language model infrastructure for organizations operating in regulated and data-sensitive environments. The company specializes in deploying AI systems that prioritize compliance, control, and enterprise-grade security—enabling teams to benefit from AI without exposing proprietary or sensitive information.

Contact Info:
Name: Samuel Edwards
Email: Send Email
Organization: Digital.Marketing
Website: https://digital.marketing

Release ID: 89182243

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