Conditional Automation and Actionable Remediation

Automating remediation by linking root causes to tailored playbooks for faster resolution

“NetAI links root causes to tailored playbooks, enabling conditional automation. For example, it diagnosed bandwidth congestion and automatically triggered a reroute, requiring no manual intervention.” 

How the AI NOC Does It

The AI NOC’s Conditional Automation and Actionable Remediation leverages advanced Graph Neural Networks (GNNs) and intelligent playbook integration to automate the remediation process while maintaining precise control. By linking root causes to tailored playbooks, the AI NOC ensures remediation actions are executed only under specific, pre-configured conditions, enabling rapid and safe resolution without the risk of unintended consequences.

Here’s how the AI NOC achieves this:

• Dual-Stage Root Cause Analysis:
  The AI NOC first performs Initial Root Cause Analysis, rapidly identifying the anomaly and suggesting a potential fix for quick triage. In the Comprehensive Root Cause Analysis stage, it delves deeper to ensure diagnostic accuracy before proceeding with remediation.

• Linking Root Causes to Tailored Playbooks:
  Each root cause is mapped to a specific, pre-defined playbook containing step-by-step remediation actions. These playbooks are tailored to the organization’s unique network policies, configurations, and operational requirements.

• Conditional Automation:
  The AI NOC executes remediation actions only when specific, pre-set conditions are met, ensuring that automation remains safe and reliable. For example, in the case of bandwidth congestion, the AI NOC triggers a reroute only after verifying that alternate paths meet required thresholds for latency and capacity.

• Automated Execution of Actions:
  Once conditions are satisfied, the AI NOC automates the remediation process such as rerouting traffic, adjusting QoS policies, or reconfiguring devices. These actions are performed without manual intervention, significantly reducing response times.

• Real-Time Monitoring and Feedback:
  Throughout the remediation process, the AI NOC continuously monitors the network to ensure actions taken are effective and do not introduce new issues. If further adjustments are needed, the AI NOC updates the playbook dynamically for future incidents.

• Seamless ITSM Integration:
  The AI NOC integrates with ITSM tools like JIRA or ServiceNow to log incidents, root causes, and remediation actions. This ensures complete transparency and documentation for post-incident analysis.

Why the AI NOC Stands Out

Traditional tools often lack the intelligence or flexibility to link root causes to tailored remediation actions, relying instead on generic or manual processes. The AI NOC’s approach is unique because it:

• Enables Conditional Automation:
  Ensures actions are executed only when predefined conditions are met, reducing the risk of unintended consequences.

• Links Root Causes to Tailored Playbooks:
  Provides precise, context-aware remediation for faster resolution.

• Reduces Mean Time to Repair (MTTR):
  Automates remediation actions, cutting response times by up to 90%.

• Ensures Transparency:
  Logs all actions and decisions for accountability and continuous improvement.

• Supports Scalable Automation:
  Adapts to complex, multi-vendor environments without requiring extensive manual configuration.