AiStrike Launches Continuous Detection Engineering at RSA 2026

Why It Matters

By turning detection management into a continuous, data‑driven process, organizations can cut operational expenses, improve threat coverage, and extract more value from existing security investments. This addresses a core industry pain point—alert fatigue caused by low‑quality detections—enhancing overall security posture.

Key Takeaways

• 80% alerts dead ends; detection quality is core issue
• Continuous Detection Engineering cuts alert noise up to 90%
• Auto-generates MITRE ATT&CK aligned detections to close gaps
• Optimizes SIEM data use, lowering ingestion and storage costs
• Provides detection-as-code workflow without replacing existing tools

Pulse Analysis

Alert fatigue remains a top challenge for security operations centers, with most enterprises drowning in low‑value notifications rather than genuine threats. Traditional SIEM deployments often leave more than half of collected telemetry unused, creating blind spots that attackers can exploit. Continuous Detection Engineering tackles this inefficiency by treating detections like software code—subject to version control, automated testing, and iterative improvement—thereby transforming static rule sets into living defenses that adapt to evolving adversary tactics.

AiStrike’s platform leverages a closed‑loop model that ingests real‑world incident outcomes, maps detection coverage to the MITRE ATT&CK framework, and automatically generates or refines rules to fill identified gaps. By focusing on high‑impact telemetry, it reduces data ingestion and storage costs while maintaining comprehensive visibility. The detection‑as‑code approach also aligns with modern DevSecOps practices, allowing security teams to use familiar Git and CI/CD pipelines for rule development, validation, and deployment without overhauling existing security stacks.

The market implications are significant: organizations can achieve up to a 90% drop in false positives, accelerate time‑to‑detect and time‑to‑contain, and realize better ROI on SIEM and XDR investments. As more vendors adopt continuous, intelligence‑driven detection models, the competitive landscape will shift toward solutions that embed automation and analytics into the core of security operations. Early adopters like SUBSCRIBE report tangible cost savings and heightened confidence in their threat coverage, signaling a broader industry move toward proactive, data‑centric security engineering.