- Rapid7's (RPD, Financial) agentic AI system achieves 99.93% accuracy in alert triage.
- The integration saves over 200 SOC hours weekly through automation.
- Enhanced threat detection capabilities provide transparency and improved alert fidelity.
Rapid7, Inc. (RPD), a leader in threat detection and exposure management, has announced the integration of agentic AI workflows into its next-generation SIEM and XDR platform. This innovation is poised to transform threat investigation within Managed Detection & Response (MDR) environments by leveraging Rapid7’s AI Engine. The AI system autonomously performs investigative tasks with analyst-level expertise at AI speeds, boasting an impressive 99.93% accuracy in alert triage and saving over 200 Security Operations Center (SOC) hours each week.
The agentic AI workflows are trained using playbooks crafted by Rapid7's SOC experts and are designed to combat increasingly sophisticated AI-powered cyber threats. These workflows provide scalable, transparent, and human-centric security operations, allowing organizations to enhance their security posture with greater confidence. With the increased visibility into AI-driven decisions, this system maximizes returns on detection and response investments by reallocating analyst hours to more complex and strategic tasks.
As the threat landscape accelerates with AI-enabled attacks, Rapid7’s innovation ensures that organizations can keep pace. The new workflows not only automate repetitive tasks but also deliver relevant findings and contextual information, supporting SOC analysts in making more informed and timely decisions. This positions Rapid7's solution as an essential tool in modern cybersecurity operations, maintaining human oversight and transparency in AI applications.
For those interested in learning more about Rapid7’s Managed Detection and Response services with agentic AI workflows, further information is available on their website.
