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The Shift Toward Autonomous Security
94%
Of enterprises face alert fatigue due to growing volume and complexity of security threats
<5 mins
average response time with autonomous playbooks vs. manual intervention
4x
faster threat containment using AI/ML-powered detection and response pipelines
88%
reduction in false positives using behavioral analytics and continuous model refinement
Platform Highlights
Leverages AI and automation to transform traditional security operations into intelligent, self-healing systems
01
Leverage AI models trained on real-time threat signals, anomaly patterns, and adversarial behavior to surface high-fidelity alerts
02
Automate triage, containment, and remediation steps using customizable response workflows triggered by confidence scores
03
Ingest global threat feeds and contextual threat indicators to enhance detection precision and adversary profiling
04
Assign dynamic trust and risk scores to users, devices, and workloads using behavior analytics, geolocation, and historical patterns
Principles of an Autonomous SOC
AI at the Core
Machine learning, anomaly detection, and predictive models drive every detection, decision, and response
Automation as a Default
Orchestrate workflows, update rules, and respond to threats in real-time—without waiting for manual action
Human-in-the-Loop Governance
Allow analysts to validate, tune, or override AI-driven decisions with explainable outcomes
Continuous Threat Learning
Incorporate feedback loops, honeypot data, and new attack vectors to evolve SOC defenses autonomously
Cloud-Native and Platform Integrations
AWS Security Stack
Integrate GuardDuty, CloudTrail, and AWS Security Hub for unified telemetry and incident response automation
Microsoft Defender & Sentinel Integration
Extend threat visibility across endpoints and cloud with native integration into Azure Sentinel and Microsoft Defender XDR
Google Chronicle & BeyondCorp
Fuse Chronicle logs with AI-driven threat modeling to detect insider threats and lateral movement across Google Cloud workloads
Use Cases for Autonomous SOC
Insider Threat Detection
Proactive Defense Against Privileged Misuse
Detect risky behavior by internal users through behavioral baselines, access deviation analysis, and intent prediction
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Cloud Threat Hunting
AI-Powered Hunting Across Multi-Cloud Workloads
Correlate cloud logs, workload metadata, and network signals to uncover hidden threats across AWS, Azure, and GCP
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SOC Modernization
ServiceNow AI Agents for Autonomous Security Operations
Integrate ServiceNow with AI-driven agents to automate incident management, accelerate response workflows, and unify SOC operations with intelligent ticketing and real-time resolution
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OT and IoT Security
Secure Industrial Assets with Autonomous Defense
Monitor industrial and connected devices with protocol-aware agents and real-time anomaly detection models
Our Approach to SOC Autonomy
Composable Security Pipelines
Build flexible detection and response workflows that adapt to evolving threats and compliance demands
Behavioral Analytics at Scale
Continuously learn and profile normal vs. suspicious behavior across users, systems, and applications
Explainable AI in Action
Generate transparent explanations for AI-driven alerts, increasing analyst trust and response accuracy
Security as Code
Manage detection rules, thresholds, and workflows with Git-based policies and CI/CD for security operations
Resilience Through Simulation
Run automated red-team simulations and adversarial testing to continuously validate SOC readiness and tooling
Competencies
Benefits of an Autonomous SOC
Offers transformative benefits by combining AI, automation, and advanced analytics to streamline threat detection and response
Speed Redefined
Respond to incidents in seconds—not hours
Visibility Redefined
Gain unified insight across endpoints, cloud, identity, and network
Precision Redefined
Eliminate alert fatigue with intelligent prioritization and contextual correlation
Scalability Redefined
Scale security operations without scaling your team—through automation and AI assistance
Cloud-native Autonomous SOC
Discover how cloud-native architectures enhance SOC agility and scalability—enabling AI-powered threat detection, automated response, and seamless integration across hybrid environments
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Edge Computing in Autonomous Security Operations Center
Explore how edge computing brings real-time security intelligence to the network’s edge—powering faster threat detection and response in distributed and low-latency environments
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