Clearing a 6-Week L2 Backlog in Just 4 Days with Support Genie
Balancing Product Innovation with Support Demands
The client is a rapidly growing technology company with a 200-person engineering team responsible for managing a complex ecosystem of applications, integrations, and customer-facing platforms. As the business scaled, the volume of support tickets increased significantly, especially in L2 and L3 tiers, creating mounting pressure on engineering resources. Despite having a skilled engineering team, the organization found itself spending a substantial portion of sprint cycles on support activities rather than on product innovation. Leadership recognized that the growing support burden was impacting delivery timelines, team productivity, and overall business agility.
When Support Backlogs Start Impacting Product Delivery
As ticket volumes continued to rise, the company struggled to keep pace with L2 and L3 support demands. What began as occasional support interruptions gradually evolved into a persistent operational bottleneck that affected engineering productivity and product delivery timelines.
The most common ticket types driving the backlog were:
Authentication failures and JWT token expiry issues causing widespread user session disruptions
Payment API timeouts and rate-limit misconfigurations affecting transaction completion rates
Webhook delivery mismatches breaking order sync and downstream data pipelines
Database sync lag in reporting modules causing data inconsistency across dashboards
Deploying Support Automation Powered by AI
To address the growing support burden, ThoughtMinds implemented Support Genie, an AI-powered support operations platform that seamlessly integrated with existing support and engineering workflows to automate ticket analysis, triage, resolution, and knowledge retrieval.
Leveraging historical ticket data, internal documentation, and past resolution patterns, the platform rapidly connected with GitHub, Datadog, PagerDuty, Jira, and internal runbooks, enabling it to analyze logs, trace dependencies, recommend root-cause fixes, and progressively automate recurring L2 and L3 support issues. By continuously learning from support interactions, Support Genie significantly reduced manual effort and accelerated issue resolution, allowing engineering teams to focus on higher-value initiatives.
A Structured Approach to Support Transformation
Integrated Support Genie with existing ticketing systems, monitoring tools, and knowledge repositories.
Trained AI models using historical support tickets and documented resolution workflows.
Automated ticket classification, prioritization, root-cause analysis, and resolution recommendations.
Continuously monitored performance and optimized automation coverage across support queues.
Creating Value Beyond Ticket Resolution
By reducing support overhead, the organization improved employee productivity, enhanced customer experiences, and enabled engineering teams to return their focus to innovation.
Engineers regained valuable time to focus on product development and strategic initiatives.
Support teams experienced lower workloads and fewer repetitive manual tasks.
Customers received faster responses and more consistent issue resolution.
Leadership gained greater visibility into support performance and resource allocation.
The Business Impact at a Glance
94%
Auto-resolution rate of L2 and L3 support tickets within the first week.
4
Days to clear a 6-week backlog without requiring developer overtime.
40%
Sprint capacity recovered and redirected toward product innovation and delivery.