Todays environments are multi-cloud, SaaS-heavy, containerized, API-driven, and identity-centric, which creates far more data and complexity. Teams that move to modern data pipelines and data lakes get better scale, flexibility, and cost control. But they
Security has become a data challenge. Identifying threats in the AI era depends on complex data engineering processes, but legacy tools and infrastructure force a painful tradeoff: either collect and store everything and sacrifice your
The CardinalOps Agentic Fleet equips your team to succeed in the AI era. Purpose-built agents continuously improve signal quality and expand coverage, transforming detection engineering into a scalable, adaptive system. Built on decades of practitioner
TAG Infosphere, a professional research and advisory firm serving the cybersecurity community, provides a return on investment (ROI) analysis for the CardinalOps AI-Powered Detection Posture Management platform. Their in-depth analysis shows how the platform delivers
Detection engineers are at a breaking point, managing countless detections, endlessly tuning rules, monitoring telemetry for drift, and researching new adversary behaviors. It’s time for a new model to take flight, with agentic AI pointing
For years, security teams have rallied around a clear idea: shift detection engineering left. Treat detections as code, map them to adversary behaviors, and continuously refine them into high-fidelity signals. On paper, it’s a powerful
For years, security operations leaders have been pushing a simple but powerful idea: shift detection engineering left. Treat detections as code, manage them through lifecycle processes, map to adversary behaviors, then continuously tune, validate, and
Recent news of a cyberattack targeting global medical technology manufacturer Stryker is another reminder that even highly sophisticated organizations remain vulnerable to modern cyber threats. The attack reportedly disrupted corporate systems and forced employees offline
CardinalOps closes gaps identified by your BAS platforms and proactively reduces risk with AI-powered detection engineering. By incorporating evidence from attack simulations into automated rule development and tuning workflows, CardinalOps helps accelerate red and purple
Traditional SIEM architectures are under increasing strain as modern environments generate massive volumes of security telemetry from cloud, SaaS, containerized workloads, and identity systems. As data volumes grow, organizations face rising SIEM costs and operational
CardinalOps integrates with security data lakes and pipelines to operationalize security contextual data, continuously expand detection coverage, and drastically reduce costs from outdated SIEM licensing models. Modular, scalable data infrastructure provides the right context, at
AI SOC represents a fundamental rethinking of how detection, response, and investigation are delivered. At the heart of this shift is an important technical and strategic theme: the critically important role of detection engineering. For