Stellar Cyber has released results from an independent study of 124 days of customer trials of its Agentic Auto Triage capability. The study evaluated 138,475 real security alerts and found that Auto Triage reached the same verdict as human analysts 99.7% of the time, addressing the central question facing every security team weighing autonomous SOC technology: Can AI actually be trusted to make decisions?
Auto Triage agreed with human analysts 99.7% of the time across 138,475 real security alerts.
Returns 19 minutes of every analyst hour, translating to one day per week per analyst reclaimed.
Equivalent of 1.5 full-time analysts' annual workload handled by Auto Triage.
64% of false positives closed automatically; 15% of true positives escalated for human review.
Powered by machine learning models trained on real-world phishing patterns with human-in-the-loop oversight.
Available now as part of Stellar Cyber AI-native SecOps platform.
AI-driven tools have made it easier than ever for adversaries to design highly convincing phishing and ransomware attacks. The World Economic Forum reports potential security threats have surged dramatically, with ransomware attacks jumping by up to 48% year-over-year and phishing attempts exploding by 1200% since late 2022. This escalation is largely driven by GenAI-enhanced tactics. Automatic Triage, powered by Agentic AI, levels the playing field for human security analysts by automatically ingesting, correlating, analyzing, and prioritizing suspicious events from the user's environment.
Across the trials, Auto Triage returned roughly 19 minutes of every analyst hour to higher-value work, including working more cases per shift and dedicating more time to exposure management. This time translates to about one day per week per analyst, or the equivalent of 1.5 full-time analysts reclaimed annually. By closing out confident false positives and surfacing real threats before a human ever opens them, Auto Triage reduces noise, helps teams move from an alert-centric mode to a case-management mode, and transforms the job of the human security analyst. This shift helps improve MTTD and MTTR while giving analysts time to think like attackers and close visible gaps before they are exploited.
Using machine learning models trained on real-world phishing patterns, the platform delivers reliable, actionable verdicts in seconds. Auto Triage assigns each alert a decision through an AI-driven Verdict Signal Check, with human-in-the-loop oversight and a closed-loop learning process that improves accuracy over time. During the trials, the system analyzed 138,475 alerts, disposing of 64% as confident false-positive closures. Auto Triage escalated 15% of the alerts as true positives for human analyst review and routed the remainder as informational, clearing noise before it reached a person.
"Security operations have reached a tipping point. The volume and complexity of alerts are simply beyond what human analysts can manage alone," said Aimei Wei, Chief Technology Officer at Stellar Cyber. "This real-world study proves that our approach of combining machine-speed analysis with human judgment is the right way forward. These results show what that looks like in practice: the AI does the alert work at scale, the analyst stays in control, and they almost always agree—freeing analysts to manage more cases and get ahead of emerging exposure."
"The Agentic AI built into Auto Triage is designed to address one of the most pressing challenges security analysts deal with on a daily basis: tuning out the noise and focusing on legitimate threats to the business," said Christopher M. Steffen, CISSP, CISA, CCZT, VP of Research, Information Security, Risk, and Compliance Management at EMA. "This study proves that Stellar Cyber's approach of automatic ingestion and analysis, AI-driven prioritization, and highly accurate decision-making has the power to transform the way analysts work in the enterprise SOC—from processing alerts to managing cases, moving from MTTD and MTTR towards MTTN - mean time to neutralize, and spending more time proactively reducing exposure."
About Stellar Cyber
Stellar Cyber is a full-cycle AI-native SecOps platform purpose-built for MSSPs and lean enterprise security teams. Since 2015, Stellar Cyber has helped organizations illuminate the darkest corners of cybersecurity to see every threat, know what matters most, and act with speed and confidence — always with the human in the loop. By applying the right tool to the right problem, Stellar Cyber combines machine learning to uncover hidden anomalies, agentic AI to guide responses in real time, and human-augmented decision-making where expertise is essential. The result is real-world impact: analyst productivity improved by more than 80%, false positives reduced by over 90%, and security teams free to focus on what matters.
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