Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Technology • 150 Clients

Case Study 19: IT Managed Services

Marketing-optimized case study for Canadian SMBs.

$145,000
Annual Savings
400%
ROI
3.4 months
Payback
Technology • 150 Clients
Industry Focus

Executive Summary

Ticket Triage: AI analyzes support tickets, categorizes by severity, identifies known issues, and routes to appropriate technician with relevant documentation. Auto-resolves 40% of tier-1 tickets.

Challenge

Solution

  • Ticket Triage: AI analyzes support tickets, categorizes by severity, identifies known issues, and routes to appropriate technician with relevant documentation. Auto-resolves 40% of tier-1 tickets.
  • Knowledge Base Search: RAG system trained on 8 years of tickets and documentation. Technicians and clients can search in natural language for solutions.
  • Proactive Monitoring: ML analyzes system logs, performance metrics, and error patterns to predict failures 3-5 days before they occur. Generates preventive maintenance tickets automatically.

Technical Stack

Key Metrics

42%
First-call resolution improved from 42% to 68%
3.2
Average ticket resolution time reduced from 3.2 hours to 1.1 hours
1
Tier-1 support staff reduced from 6 FTE to 3 FTE ($128k savings)
280
Prevented outages saving estimated 280 hours of client downtime
4.3
Client satisfaction improved from 4.3 to 4.8 stars

Implementation Timeline

11 weeks including knowledge base training and monitoring agent deployment

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