AI Change Manager for Xurrent (4me)

Overview

The AI Change Manager is a powerful integration between NopeSight and Xurrent (4me) that provides automated, AI-powered risk assessment for IT change requests. When a change is initiated in Xurrent, NopeSight's AI analyzes the impact, dependencies, and risks associated with the change, providing comprehensive insights to help decision-makers evaluate and approve changes with confidence.

Key Features

🤖 Automated Risk Assessment

• Real-time Analysis: Instantly analyzes change requests when they are created or updated in Xurrent
• Multi-dimensional Risk Scoring: Evaluates technical, business, dependency, and historical risks
• Confidence Levels: Provides AI confidence scores for each assessment

📊 Comprehensive Impact Analysis

• Dependency Mapping: Identifies all systems and services affected by the change
• Critical System Detection: Highlights impacts on critical infrastructure
• Downtime Estimation: Provides realistic downtime estimates based on complexity
• User Impact Assessment: Quantifies the number of users affected

🎯 Intelligent Recommendations

• Pre-change Actions: Specific steps to take before implementing the change
• During-change Guidance: Real-time recommendations during implementation
• Post-change Validation: Verification steps to ensure successful completion
• CAB Talking Points: Key discussion items for Change Advisory Board meetings

Prerequisites

Before setting up the AI Change Manager, ensure you have:

1. NopeSight Requirements:

   • Active NopeSight deployment with CMDB populated
   • Discovery agents running and collecting infrastructure data
   • CI relationships mapped (network connections, software dependencies)
   • AI-enhanced relationships (CIAiRelationships) for better insights

2. Xurrent (4me) Requirements:

   • Active Xurrent account with administrative access
   • API access enabled for your Xurrent instance
   • Ability to create automation rules and webhooks

3. Xurrent API Token:

   • You must create a Personal Access Token in Xurrent with the following required scopes:
     • Automation Rule — Create, Delete, Read, Update
     • Configuration Item — Create, Read, Update
     • Note — Create, Read
     • Organization — Create, Read, Update
     • Person — Create, Read, Update
     • Product — Read, Update, Create
     • Product Category — Read, Create, Update
     • Task — Create, Read, Update
     • Task Template — Create, Read, Update
     • Team — Create, Read, Update
     • UI Extension — Create, Read, Update
     • Webhook — Create, Delete, Read, Update

Configuration

Step 1: Access Xurrent Integration Settings

1. Navigate to Integrations in the main menu
2. Select Xurrent Integration
3. Click on Create New Configuration or edit an existing configuration

Step 2: Configure Basic Settings

1. Configuration Name: Enter a descriptive name (e.g., "Production Xurrent Integration")
2. Service URL: Enter your Xurrent GraphQL endpoint
   • Format: https://graphql.your-domain.4me.com or
   • Demo: https://graphql.4me-demo.com
3. Account ID: Your Xurrent account identifier
4. API Token: Paste your Personal Access Token with the required scopes

Step 3: Enable AI Change Manager

1. Navigate to the AI Change Manager tab in the configuration
2. Toggle Enable AI Change Manager to ON
3. Click Setup AI Change Manager button

The system will automatically create:

• ✅ Webhook: Receives change notifications from Xurrent
• ✅ UI Extension: Adds AI assessment fields to Xurrent tasks
• ✅ Task Template: Template for change tasks with AI fields
• ✅ Automation Rule: Triggers AI analysis when changes are created

Step 4: Configure Product Mappings (Optional)

The Product Mappings section allows you to map your internal CI Types to Xurrent products:

1. Select CI Type: Choose from your configured CI types (Server, Workstation, etc.)
2. Search for Product: Use the dynamic search to find Xurrent products
3. Add Mapping: Click "Add Mapping" to create the association

Product mappings help Xurrent understand which products are affected by changes to specific CI types.

Step 5: Verify Setup

After setup completion, you'll see:

• Webhook Status: ✅ Created and Verified
• UI Extension Status: ✅ Created
• Task Template Status: ✅ Created
• Automation Rule Status: ✅ Created

The webhook will be automatically verified, and you'll see the verification timestamp.

How It Works

1. Change Initiation

When a change request is created in Xurrent that includes Configuration Items:

• The automation rule detects the new change
• A webhook is triggered to NopeSight with change details
• The webhook payload includes CI IDs, change description, and metadata

2. AI Analysis Process

NopeSight's AI engine performs comprehensive analysis:

• CI Identification: Locates the affected CIs in the CMDB
• Dependency Discovery: Maps all related systems and services
• Risk Calculation: Evaluates multiple risk dimensions
• Impact Assessment: Determines business and technical impacts
• Recommendation Generation: Creates actionable recommendations

3. Results Delivery

The AI analysis results are automatically sent back to Xurrent:

• Custom Fields Update: 21 specialized fields populated with assessment data (including 2 comprehensive JSON fields)
• Task Note: Summary added to the task for quick review
• Real-time Updates: Results appear within 10-30 seconds

Understanding the AI Analysis

Risk Assessment Fields

The AI populates the following risk assessment fields in Xurrent:

Field	Description	Example Values
AI Risk Level	Overall risk classification	Low, Medium, High, Critical
AI Risk Score	Numerical risk score	0-100
AI Technical Risk	Technical complexity score	0-100
AI Business Risk	Business impact score	0-100
AI Dependency Risk	Dependency complexity score	0-100
AI Historical Risk	Based on past changes	0-100
AI Risk Details	Comprehensive JSON with risk assessment, dependencies, historical context, CAB talking points, and testing strategy	JSON format

Impact Analysis Fields

Field	Description	Example Values
AI Affected Systems	Total number of impacted systems	5, 10, 25
AI Critical Impacts	Number of critical systems affected	0, 1, 3
AI Affected Users	Estimated user impact	"100-500 users"
AI Affected Services	List of impacted services	"Email, Authentication, Database"
AI Business Impact	Business impact assessment	"Moderate - affects key services"
AI Impact Details	Comprehensive JSON with impact summary, downtime analysis, recommendations, insights, success criteria, and monitoring points	JSON format

Downtime Estimation Fields

Field	Description	Example Values
AI Planned Duration	Expected change duration	"2 hours"
AI Risk Adjusted Time	Duration with risk buffer	"2.5-3 hours"
AI Service Downtime	Actual service unavailability	"30 minutes"
AI Recommended Window	Optimal implementation time	"Weekend 2-5 AM"

Recommendation Fields

Field	Description
AI Pre Change Rec	Actions to take before the change
AI During Change Rec	Guidance during implementation
AI Post Change Rec	Validation and verification steps

Analysis Metadata

Field	Description
AI Summary	Executive summary of the analysis
AI Insights	Key insights and observations
AI Confidence	AI confidence in the assessment (0-100%)
AI Analysis Version	Version of the analysis engine used

Best Practices

1. CMDB Data Quality

• Maintain Accurate CIs: Ensure your CMDB is up-to-date with latest discovery data
• Map Relationships: Network connections and dependencies should be discovered
• Regular Scans: Run discovery scans regularly to maintain data freshness

2. Change Description

• Be Specific: Provide detailed change descriptions for better AI analysis
• Include Context: Mention the business reason and technical approach
• List All CIs: Include all systems that will be modified

3. Review and Validation

• Verify AI Insights: Review the AI's assessment before CAB meetings
• Update Risk Scores: Adjust if you have additional context
• Document Deviations: Note when actual results differ from predictions

4. Continuous Improvement

• Monitor Accuracy: Track how well predictions match actual outcomes
• Provide Feedback: Report inaccurate assessments for improvement
• Update Mappings: Keep product mappings current

Troubleshooting

Common Issues

1. Webhook Not Triggering

Symptoms: Changes in Xurrent don't trigger AI analysis Solutions:

• Verify webhook is active in Xurrent
• Check automation rule is enabled
• Confirm CI IDs are included in the change
• Validate webhook URL is accessible

2. No AI Results Appearing

Symptoms: Analysis runs but fields remain empty Solutions:

• Check UI Extension is properly installed
• Verify task template includes custom fields
• Confirm API token has required permissions
• Check NopeSight logs for errors

3. Incorrect Risk Assessment

Symptoms: Risk scores seem inaccurate Solutions:

• Verify CI relationships are discovered
• Check if affected CIs exist in CMDB
• Ensure recent discovery scan data
• Review dependency mappings

4. Timeout Errors

Symptoms: Analysis times out or returns errors Solutions:

• Check network connectivity
• Verify API endpoints are accessible
• Review system load and performance
• Check for large numbers of dependencies

Log Locations

For detailed troubleshooting, check these logs:

NopeSight Logs:

• Backend logs: /backend/logs/combined.log
• AI service logs: /backend/logs/ai.log
• Look for entries containing "Xurrent webhook" or "change analysis"

Xurrent Logs:

• Automation rule execution logs
• Webhook delivery status
• API call history

Security Considerations

Data Protection

• Encryption: All data transmitted via HTTPS
• Authentication: API tokens stored securely
• Audit Trail: All changes logged for compliance

Access Control

• Token Scopes: Use minimum required permissions
• User Permissions: Limit who can configure integration
• Webhook Security: Validate webhook signatures

Compliance

• Data Residency: Analysis performed in your region
• GDPR Compliance: No PII stored unnecessarily
• Audit Logs: Complete trail of all operations

Support

For assistance with the AI Change Manager:

1. Documentation: Review this guide and related documentation
2. Support Portal: Submit tickets through your support channel
3. Community Forum: Share experiences and best practices
4. Professional Services: Contact for implementation assistance

Appendix

Webhook Payload Format

{
  "webhook_id": 18,
  "account_id": "your-account",
  "name": "NopeSight AI Change Manager",
  "event": "automation_rule",
  "payload": {
    "ci_id": ["ci-id-1", "ci-id-2"],
    "ci_name": ["Server-1", "Database-1"],
    "change_note": ["Upgrade database version"],
    "task_node_id": "task-node-id",
    "change_fields": {
      "priority": "high",
      "category": "software"
    }
  }
}

API Response Format

The AI analysis returns structured data that is automatically mapped to Xurrent fields:

{
  "riskAssessment": {
    "riskLevel": "Medium",
    "overallRisk": 45,
    "scores": {
      "technical": 60,
      "business": 40,
      "dependency": 50,
      "historical": 30
    }
  },
  "impactAnalysis": {
    "affectedSystems": 8,
    "criticalSystemsAffected": 2,
    "estimatedDowntime": "2-3 hours",
    "userImpact": "500-1000 users"
  },
  "recommendations": {
    "preChange": ["Backup database", "Notify users"],
    "duringChange": ["Monitor performance", "Check logs"],
    "postChange": ["Verify functionality", "Run tests"]
  }
}