Cloud security teams aren’t short on data - they’re short on time. Between chasing false positives, deciphering vague alerts, and negotiating ownership across silos, the gap between knowing and fixing continues to widen. Sysdig’s
new agentic AI cloud security platform aims to close that gap by combining real-time context with autonomous reasoning.
The centerpiece of the launch is
Sysdig Sage, an AI-powered analyst embedded within
Sysdig’s CNAPP. Sage doesn’t just generate answers - it acts like a teammate. It observes, interprets, recommends, and, when permitted, automates the response. This is agentic AI applied directly to the workflow of cloud security.
Moving Beyond LLMs Bolted onto Dashboards
While many security tools today claim AI integration, most rely on generic LLM chatbots that sit on top of a dashboard.
Emanuela Zaccone, AI for Cybersecurity Product Manager at Sysdig, that’s where Sysdig’s approach fundamentally differs.
“Sysdig Sage implements multiple specialized AI agents that work cooperatively on subsets of cloud security workflows, taking action and delivering a human-like approach to cybersecurity problems,” Zaccone explained. “Most solutions are unaware of specific cloud and user context. That’s not the case for Sysdig Sage.”
Instead of surface-level assistance, Sage uses semantic analysis to understand environment and asset types, business functions, and customer data flows—then correlates that with runtime behavior to identify what’s truly at risk.
“It automates semantic analysis of cloud environments to uncover critical business context,” Zaccone said. “This delivers insights about what’s most important, helping teams focus on what’s truly at risk and generating step-by-step guidance that teams need to fix issues fast.”
Closing the Loop Between Security and Dev
Security and development teams often operate in parallel, but not always in sync. That disconnect leads to friction, delays, and missed opportunities to act on risk before it escalates. Sysdig Sage was built to change that.
“One of Sysdig’s guiding principles is to bridge the divide between security and development teams,” Zaccone said. “Sage links critical business risks to what’s actually running in production, ties those risks to deployment pipelines, and translates findings into developer-ready context.”
With one-click ticketing, shared views, and precise ownership mapping, both teams operate from the same set of facts. It’s not just about faster handoffs - it’s about shared responsibility made actionable.
Autonomous, But Not Uncontrolled
Agentic AI implies autonomy, but in a regulated environment like cloud security, oversight matters. Sysdig Sage was designed with this balance in mind.
"Control and trust are core to Sysdig Sage’s design,” Zaccone noted. “Our agentic solution works on a user's behalf, though the insights and recommendations are always reviewable. Nothing happens in a black box.”
Users can tune or override decisions, and all actions are governed by transparent privacy and data management policies. Sage acts as an extension of the team, not a replacement.
Built to Scale for MSSPs
Managing security across multiple clients with different risk profiles adds another layer of complexity. Sage is built for this too.
"Sysdig’s SaaS platform is designed to isolate tenants, including all security data and AI interactions,” Zaccone explained. “MSSPs can tailor the solution to individual clients, enabling AI access for distinct user roles and customizing policies per risk profile.”
Tested in production at scale - across tens of thousands of nodes and billions of signals - Sysdig Sage can run multiple AI agents in parallel across diverse environments without sacrificing clarity or speed.
Sysdig’s agentic cloud security platform doesn’t just add another layer of automation. It reframes how teams approach risk, priority, and action. With business context built in, and AI agents that understand, reason, and support remediation, Sysdig Sage offers a clear path to faster decisions and smarter defenses, without more noise.
