Sentinel Launches Security Platform Designed for AI-Driven Organizations

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Sentinel Launches Security Platform Designed for AI-Driven Organizations

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Reimagining Safety for the Digital Age

As the digital landscape evolves, so does the way organizations operate and protect themselves. The rise of so-called "Frontier Firms" sees human and artificial intelligence (AI) collaboration in real-time to resolve issues, foster innovation, and create robust organizations.

For security teams, this shift brings about both fresh possibilities as well as challenges. The complexity and pace of current cyber threats require solutions that surpass traditional tools. To meet these demands, a new wave of agentic security capabilities is being introduced, fully equipping defenders to thrive safely in this new AI era.

A New Security Platform for the AI Age

Defenders require a platform that marries data, context, automation, and intelligent agents, allowing them to safeguard and adjust at AI speed. This new platform, known as Sentinel, meets these needs.

Initially, Sentinel began as a cloud-native security information and event management (SIEM) system. It then expanded to incorporate a unified security data lake. Now, it is evolving into an agentic platform with the full availability of Sentinel data lake, and the preview of Sentinel graph and Sentinel Model Context Protocol (MCP) server. These developments equip defenders with a single platform to ingest signals, correlate across domains, and empower AI agents built in Security Copilot, VS Code using GitHub Copilot, or other developer platforms.

Understanding the Digital Estate

Sentinel takes in signals, either structured or semi-structured, and constructs a rich, contextual understanding of your digital estate. This is achieved through vectorized security data and graph-based relationships. By integrating these insights with Defender and Purview, Sentinel delivers graph-powered context to the tools already used by security teams. This helps defenders trace attack paths, comprehend impact, and prioritize response, all within familiar workflows.

Moreover, Sentinel organizes and enriches your security data, preparing it for AI agents to detect issues faster, investigate with more clarity, and respond automatically when needed. Sentinel’s graph-based approach enables Security Copilot agents to reason over your environment with precision and speed, thanks to the built-in MCP server, which uses open standards for easy agent access and action. This shifts security from reactive to predictive, helping teams anticipate threats and automate response at scale.

Building Customized Agents with Security Copilot

Security Copilot was designed to help security teams address the toughest challenges, such as endless alerts, siloed tools, and the constant pressure to do more with less. Now, you can build your own Security Copilot agents with a no-code agent builder, which allows you to articulate what you need in natural language and create, optimize, and publish agents tailored to your workflows in minutes.

Security Copilot agents can be integrated into daily tools and workflows, whether they are embedded in the security products you already use or are custom-built for your environment. These agents can reason more effectively across your environment by correlating alerts, enriching context with relationships, prioritizing by impact, and automating common actions. This reduces false positives, accelerates triage, and lowers the mean time to resolution. Work shifts from manual triage to agent-led workflows, enabling analysts to focus their time on strategic decisions and proactive threat hunts.

Securing and Governing AI Effectively

As organizations adopt AI, investments are being made in tools that assist security teams in securing and governing their AI platforms, apps, and agents across the enterprise. These tools help discover and manage your agent estate, prevent data oversharing in custom-built AI apps and agents, offer risk discovery tools for AI model providers and MCP servers, and provide advanced detection for prompt injection attacks.

Security is no longer a one-man show, but a team sport. A team that includes everyone, innovating together, learning together, and defending together. Together, we’re not just imagining the future. We’re securing it.

 
The shift to predictive, agent-driven security is honestly huge—curious if Sentinel’s context protocols can play nice with legacy systems, or is full modernization basically required?
 
To meet these demands, a new wave of agentic security capabilities is being introduced, fully equipping defenders to thrive safely in this new AI era. A New Security Platform for the AI Age

Defenders require a platform that marries data, context, automation, and intelligent agents, allowing them to safeguard and adjust at AI speed.

Merging data, context, and automation sounds impressive, but I wonder if real-time adaptation at “AI speed” is practical on the ground or just marketing talk—how do their intelligent agents actually handle unpredictable scenarios?