How a Fortune 100 Tech Company Eliminated Incident Overload With AI-Enabled Operations
A leading Fortune 500 technology company partnered with Galent to transform its enterprise operations landscape with a focus on improving reliability, scalability, and SLA adherence across a complex, multi-stack software ecosystem.
With a vast portfolio of applications and services operating at global scale, the organization faced recurring operational challenges, including incident overload, delayed resolutions, and limited automation in monitoring and reporting. These issues directly impacted service reliability and operational efficiency.
The engagement focused on embedding AI into SRE practices leveraging the Galent AI Platform to enable intelligent automation, proactive incident management, and continuous operations.
The result: a resilient, AI-enabled operations model delivering near-perfect SLA adherence, significantly reduced support effort, and always-on system reliability.
Client Challenges:
Operating at scale introduced several operational and architectural challenges:
Complex Multi-Stack Ecosystem:A highly distributed architecture with multiple technology stacks led to recurring incidents and increased operational complexity.
Delayed Incident Resolution: Manual triaging and fragmented workflows resulted in slower resolution times, impacting SLA compliance and system reliability.
Limited Automation in Operations: Alert management, ticket handling, and reporting processes were largely manual, leading to inefficiencies and inconsistencies.
Scalability Constraints in SRE Model: The existing SRE framework lacked the flexibility and intelligence required to scale with growing system demands.
Reactive Operations Model: Dependence on reactive incident management limited the ability to predict, prevent, and proactively resolve issues.
Galent’s Approach
Galent implemented a comprehensive AI-driven SRE transformation strategy, embedding intelligence, automation, and observability into core operations.
AI-Powered SRE Platform
Deployed a self-service, AI-enabled SRE platform to streamline and automate operations:
- Automated ticket management and intelligent routing
- Alert rationalization to reduce noise and improve signal accuracy
- Real-time performance monitoring and reporting dashboards
SRE Lab for Continuous Optimization
Established a dedicated SRE Lab to drive ongoing improvements:
- Observability design and enhancement
- Architecture tuning and system optimization
- Continuous testing and refinement of SRE practices
Automation-First Operating Model
Redesigned operational workflows with automation at the core:
- Standardized processes aligned to SLA goals
- Automated incident detection and resolution workflows
- Reduced manual intervention across support layers /li>
Predictive Monitoring & Proactive Remediation
Enabled 24×7 intelligent monitoring powered by AI:
- Predictive analytics to identify potential failures
- Proactive remediation before incidents impact users
- Continuous system health tracking
Centralized Command Center
Established a unified command center for all SRE-related activities:
- Centralized visibility into incidents, alerts, and tickets
- Real-time coordination and response management
- Improved governance and operational control
Solution Delivered
- AI-powered SRE platform for automated operations
- Centralized command center for unified incident management
- Dedicated SRE Lab for continuous optimization
- Automation-first workflows aligned to SLA compliance
- Predictive monitoring with AI-driven insights
- 24×7 global operations coverage
Business Impact
The transformation delivered significant improvements in reliability, efficiency, and operational scalability.
Key outcomes:
- Near-Perfect SLA Adherence: Achieved 99.999% SLA adherence through AI-led incident detection, prioritization, and resolution.
- Reduced Operational Effort: Delivered a 60% reduction in support effort through automation of workflows, ticketing, and alert management.
- Always-On Operations: Enabled 100% continuous operations coverage with 24×7 AI-powered monitoring and proactive remediation.
- Improved Incident Response & Resolution: Significantly reduced mean time to detect (MTTD) and mean time to resolve (MTTR) through intelligent automation.
- Scalable, Future-Ready SRE Model: Established a resilient operations framework capable of supporting growing system complexity and scale.
This engagement demonstrates how AI can redefine enterprise operations by embedding intelligence into the core of reliability engineering. Through a combination of automation, predictive analytics, and centralized governance, Galent enabled a shift from reactive incident management to proactive, autonomous operations.
The result is a high-performance, resilient SRE model designed to deliver consistent reliability, optimize effort, and support continuous innovation at scale.
Executive Insight: A Client Perspective
“Galent’s AI-driven SRE model has fundamentally transformed our operations. We’ve moved from a reactive support environment to a highly intelligent, automated system that ensures reliability at scale. The impact on SLA adherence, efficiency, and overall operational visibility has been exceptional”
– Director, Site Reliability Engineering