Galaxy One Security Team has successfully integrated Agentic AI into the SOCOne system — where AI actively participates in analysis, orchestration, and decision support within cybersecurity operations, while still ensuring enterprise-grade control and governance.
According to the 2025 report by the CUBE Research in collaboration with Kong Inc., 63% of enterprises now prioritize paid enterprise-grade LLM solutions, with 31% identifying security as the top criterion when selecting AI platforms. This reflects a broader market shift, where organizations demand not only accuracy, but also reliability, transparency, and seamless integration capabilities.
By 2026, more than 70% of enterprises are expected to seek sovereign, highly secure, and infrastructure-independent AI solutions. This trend further reinforces the growing importance of security and compliance across all enterprise AI applications.
Recognizing the challenges in a landscape where data has become a core enterprise asset, the Galaxy One Security Team has pursued a different approach: transforming the SOC model from “AI-assisted” to “AI-powered decision” through a multi-agent AI system called SOCOne AI Agentic.
Built on Galaxy One’s proprietary SOC platform, the team did not simply add AI into the existing SOC workflow. Instead, they redesigned the entire operational workflow around tasks that AI Agents can execute effectively, including log analysis, context aggregation, risk assessment, and incident response recommendation support.
The key differentiator lies in solving one of the biggest challenges of AI adoption in enterprise environments: controllability. SOCOne AI Agentic was developed using a “data-centric decision” architecture, ensuring that every conclusion and remediation action is grounded in real operational data rather than AI inference alone. At the same time, a Human-in-the-loop model is maintained, enabling security operators to supervise, orchestrate, and intervene at any stage of the process.
The system is also capable of operating on open-source LLM models, allowing enterprises to proactively manage infrastructure, reduce dependence on LLM SaaS platforms, and optimize deployment costs. The goal of AI in SOC is not to replace humans, but to accelerate operational capabilities, standardize incident handling processes, and improve detection and response speed in real-world cybersecurity environments.
This achievement not only demonstrates Galaxy One’s AI research and deployment capabilities, but also marks another milestone in its journey toward building next-generation cybersecurity capabilities for enterprises.
