Teceze implemented AI-driven threat detection and automated incident response for NetSecure's security operations centre, reducing security incident response time by 85% through machine-speed threat identification and containment across the enterprise environment.
NetSecure is a regional managed security services provider (MSSP) protecting 300+ mid-market and enterprise customers across infrastructure, applications, and endpoints. They manage 40,000+ security events daily and serve industries including retail, manufacturing, and insurance. The organization operates a Security Operations Center (SOC) where analyst burnout from alert fatigue was undermining threat detection effectiveness.
NetSecure’s SOC generated 400+ daily alerts across 300 customers. Analysts spent 80% of their time chasing false positives and low-severity events, leaving little bandwidth to focus on genuine threats. With a 73% false positive rate, the signal-to-noise ratio had degraded to the point where real incidents were routinely buried in the queue.
Mean Time to Respond (MTTR) averaged 4.2 hours. By the time serious threats were investigated, attackers had already established lateral movement and persistence—a gap that contributed to three significant breaches in 2024, resulting in $1.8M in customer claims and eroding confidence in the SOC’s ability to protect the environments it monitored.
Security Operations Centers managing 300+ customers face a critical challenge: alert fatigue from 400+ daily alerts prevents effective threat detection while analyst burnout drives team attrition. Teceze’s approach to NetSecure’s SOC modernization prioritized AI-powered threat detection, automated triage and response, behavioral analytics, and 24/7 threat hunting—delivering a model where AI automation enables security excellence without operator burnout. Teceze implemented a comprehensive SOC transformation strategy prioritizing intelligence and human well-being: deployed machine learning models trained on 50+ million historical alerts detecting anomalies with 98% accuracy, built automated triage and response playbooks investigating and remediating alerts without human involvement, integrated behavioral analytics enabling per-customer baselines and insider threat detection, and deployed 24/7 threat hunting automation continuously scanning for indicators of compromise and attack patterns.
From challenge to transformation, the solution included:
Machine learning models trained on 50+ million historical alerts learn per-customer baselines for behavior and traffic, identifying deviations automatically and reducing 400+ daily alerts to actionable, high-confidence threats.
Automated playbooks investigate and enrich alerts without analyst involvement—low-confidence alerts are suppressed, medium-confidence alerts auto-remediated, and high-confidence alerts escalate with complete investigation data.
Identity and access logs detect behavioral anomalies—unusual login times, impossible travel, privilege escalation, data exfiltration—with real-time risk scores enabling early detection of insider threats and compromised accounts.
An automated threat hunter continuously scans for indicators of compromise and known attack signatures across all 300 customers, proactively surfacing threats that reactive response alone would miss.
For a SOC serving 300 customers with varying security requirements, governance must balance rapid incident response with thorough investigation and customer communication:
| Cadence | Forum | Focus |
|---|---|---|
| Real-Time | Incident response | High-priority alerts, active incidents, automated remediation actions, analyst escalations |
| Daily | SOC stand-up | Critical incidents, threat landscape changes, overnight activity, analyst capacity planning |
| Weekly | Threat intelligence | Emerging threats, detection accuracy, false positive trends, model performance review |
| Monthly | Leadership review | MTTR improvements, incident trends, customer satisfaction, analyst burnout metrics, capability roadmap |
“We went from fighting fires to being strategic defenders. Our team now hunts threats instead of chasing false alarms. One customer said, ‘Your security posture is why we renewed our contract’—that’s never happened before. This platform is our competitive edge.”
— Chief Security Officer, NetSecure
Teceze embedded security engineers and data scientists within NetSecure’s SOC for 6 months. Conducted daily model performance reviews, trained the team on AI-driven detection, and progressively transferred ownership of platform management. By month 9, NetSecure’s internal team was fully autonomous in managing and optimizing the platform while Teceze provided ongoing model refinement and threat intelligence integration.
The expertise in AI-driven threat detection, behavioral analytics, and SOC transformation continues to drive value beyond initial platform deployment. The strategic partnership ensures sustained threat detection excellence, seamless evolution of AI models with emerging threats, and continuous security innovation aligned with threat landscape changes.