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How Qinfinite’s AI-powered ITSM Capabilities Reduced MTTR and Increased Cost Efficiency for a Leading UK Bank

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About the Client:

A leading UK-based bank offering a wide range of retail and commercial financial services. The client operates in a highly regulated environment and manages complex IT operations through a centralized service desk team. 

Business Need

The client’s IT service desk team supported operations 16×5 and was responsible for resolving over 1,000 tickets per month (growing to 2,000+ as the business expanded). Unlike traditional ITSM models with multiple segmented support groups, this bank had a single support team encompassing multiple roles—AWS engineers, Salesforce specialists, and L1 to L3 support—all working from the same Jira-based system (instead of ServiceNow). 

The key challenges: 

  • Manual ticket triage by L1 support 
  • Role ambiguity: Determining who in the team should handle a specific ticket 
  • Frequent duplicate tickets and ping-ponging between support roles 
  • Disjointed collaboration via Slack channels not synchronized with Jira 
  • High median resolution time (MTTR) of ~16 hours 
  • Compliance risks due to missing ticket documentation 

The Qinfinite Solution

Without disrupting existing tools or processes (Jira, Slack, Confluence), Qinfinite was implemented as an overlay AI-powered agent to drive intelligent automation across the service desk. 

Before Qinfinite:

  • L1 support manually read, routed, and tagged all tickets 
  • Slack rooms were manually created for incident resolution 
  • Conversations often remained in Slack, not documented in Jira 
  • Duplicate ticket identification and classification was error-prone and inconsistent 
  • Ticket routing lacked contextual understanding of roles, shifts, and availability 

After Qinfinite:

  • AI Agent takes over L1 effort: It reads ticket descriptions, identifies duplicate tickets using predefined rules (log checks, DB queries), and filters noise 
  • Intelligent classification: Tickets are auto-classified as incident or service request, tailored to the bank’s custom definitions 
  • Dynamic Slack room creation: Qinfinite reads the Confluence playbook to auto-create rooms and add relevant engineers based on role and issue type 
  • Smart routing: Agent identifies the right engineer (L2/L3) based on role and shift availability 
  • Preliminary remediation: Qinfinite fetches logs, screenshots, or related diagnostics and attaches them to the ticket before escalation 
  • End-to-end documentation: Slack conversations are auto-summarized and added to the Jira ticket, ensuring compliance 

The Business Benefits We Delivered (First 4-5 Months Snapshot)

  • Ticket Volume Managed: Increased from 1,000 to 2,000+ monthly without additional headcount 
  • MTTR Reduction: Significant drop in median resolution time 
  • Effort Savings: L1 manual effort reduced drastically due to automation 
  • Cost Efficiency: Optimized support resources and minimized redundant escalations 
  • Improved Compliance: All incident records and conversations captured in Jira 
  • Higher Satisfaction: Both internal teams and end-users benefited from faster, cleaner resolutions 

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