Alert fatigue is a persistent problem in security operations, but AiStrike is framing it as a symptom of a deeper issue: poor detection quality. At RSAC 2026, the company announced Continuous Detection Engineering, a capability designed to shift SOC teams from reactive alert triage toward ongoing, intelligence-driven detection optimization.

The company’s own analysis across enterprise environments paints a stark picture: more than 80% of alerts lead to dead ends, fewer than 20% of detection rules ever trigger, and under 5% of rules generate most of the noise. On the coverage side, over 70% of detection gaps can be addressed with data already in the SIEM, while more than 50% of SIEM data is never used for detection at all.

“Security teams don’t have an alert problem, they have a detection engineering problem,” said Nitin Agale, Founder and CEO of AiStrike. “Most organizations are operating with noisy, misaligned, or incomplete detections. We built AiStrike to continuously improve detection quality, reduce noise, and align security operations to real threats, without requiring teams to rip and replace their existing stack.”

Continuous Detection Engineering works as a closed-loop system, pulling in feedback from real investigations and incident outcomes to keep detection logic current with each organization’s environment. The capability maps coverage against MITRE ATT&CK and threat intelligence feeds to identify gaps, auto-generates detections to close them, and continuously optimizes high-volume, low-value rules to cut false positives without sacrificing visibility.

Other components include detection validation and readiness checks that eliminate inactive or misconfigured rules before incidents occur, plus data and SIEM efficiency optimization to surface high-impact telemetry while reducing ingestion and storage costs.

The approach draws from software engineering practices, bringing detections-as-code, automated validation, and feedback-driven optimization to security teams that don’t have the bandwidth to build those workflows themselves.

Early results are notable. Robert Vaile, CISO at SUBSCRIBE, reported significant noise reduction: “AiStrike reduced our alert noise by over 90%, but more importantly, it gave us clear visibility into which detections are actually effective. Instead of chasing alerts, we’re now continuously improving our coverage against real threats.”

AiStrike integrates with existing SIEM, XDR, and cloud security platforms. The company says outcomes include up to 90% reduction in alert noise, improved detection coverage aligned to real threats, lower SOC and SIEM costs, and faster investigation cycles. Continuous Detection Engineering is available immediately as part of the AiStrike platform.