40% Faster Mean Time to Resolution with ResolvAI
Transforming an Energy Leader’s Incident Management with AI-Driven Efficiency and Excellence
About the Client
The client is a leading global player in the energy sector, specializing in upstream oil and gas operations. With a strong focus on exploration, production, transportation, and marketing of crude oil, natural gas, and related products, the organization operates across multiple geographies to meet the world’s growing energy needs. Recognized as one of the largest independent companies in its domain by production and proved reserves, the client is committed to delivering sustainable energy solutions while driving innovation and operational excellence.
Need for Change
Modern enterprises face growing complexity in managing incidents across diverse technology landscapes. Traditional approaches to enterprise incident management, often reliant on manual monitoring, fragmented knowledge, and reactive fixes, struggle to keep pace with high-volume pipelines and stringent SLAs. As technology environments grow and expectations for rapid response rise, organizations encounter new obstacles that demand smarter, more agile solutions. To overcome the challenges of traditional approaches, organizations need intelligent, automated enterprise incident management solutions that deliver real-time responsiveness, contextual insights, and seamless integration across systems.
Challenges
The client’s incident management was hindered by several challenges that led to repetitive troubleshooting and inefficiencies and this impacted their manufacturing units’ efficiency. Some of the key challenges included:
Fragmented Knowledge Ecosystem
Resolution intelligence was siloed, causing repetitive troubleshooting and missed learning opportunities.
Low Operational Efficiency
Manual tracking of email alerts and incident responses was slow, inconsistent, and resource-intensive, leading to prolonged downtime and inflated support costs.
No Systemic Learning Loop
Lack of instant feedback mechanisms prevented the organization from evolving based on past incidents, limiting agility and resilience.
Integration Complexity
Diverse technology stacks required seamless integration to maintain operational continuity and prevent SLA breaches across high-volume pipelines.
SLA Breaches in High-Volume Pipelines
Frequent breaches impacted service reliability and customer trust, highlighting inefficiencies in current processes.
Integration Across Diverse Technology Stacks
Complex environments demanded seamless integration of disparate data sources to ensure operational continuity and reduce risk.
LTM’s Solution
To address these challenges, LTM implemented ResolvAI, an AI-driven automation framework that integrated with Microsoft 365, seamlessly plugging into the client’s incident management ecosystem. It was customized for the client to streamline and automate incident resolution, eliminate manual monitoring, and enable proactive management across high-volume data pipelines. Acting as a virtual expert, ResolvAI automated triage, ticketing, and scheduling, and boosted efficiency. Its enterprise-grade, domain-agnostic design bridged skill gaps and delivered expert responses at machine speed.
Key aspects of the solution included:
Ingested pipeline alerts via email or activity monitoring APIs. Applied past resolution intelligence for accurate, context-rich fixes.
Utilized GPT-4o to analyze incidents, detect failures in real-time, pinpoint root causes, apply contextual fixes, and generate actionable recommendations.
Enabled feedback, rating, regeneration, and prompt-based improvements directly in Microsoft Teams, and continuously learns from user interactions.
- Approvals and Collaboration: Triggered approval workflows for critical issues and auto-schedules Teams meetings.
- Ticketing and Tasking: Automated ticket creation and updates in Microsoft Planner optionally (JIRA and ServiceNow) reducing manual overhead.
Seamlessly integrated with Microsoft 365 and Power Automate using domain- and technology-agnostic architecture that supports plug-and-play deployment across environments.
Benefits
Leveraging LTM’s ResolvAI automation framework delivered a range of measurable benefits and business value to the client. These benefits included:
Conclusion
This case study demonstrates how intelligent automation can fundamentally transform enterprise incident management at scale. By seamlessly integrating AI, in this case LTM’s ResolvAI framework, into existing data and application pipelines, the client was empowered to shift from reactive, manual operations to a proactive, learning-driven model that delivers faster resolution, higher accuracy, and sustained operational excellence. The measurable gains in efficiency, cost savings, and user satisfaction underscore ResolvAI’s ability to bridge skill gaps, institutionalize knowledge, and future-proof incident management for complex, high-volume enterprise environments—setting a new benchmark for resilient, AI-powered operations. ResolvAI sets a new standard for intelligent automation in enterprise IT as it is ready to deploy and scale for any enterprise. Thus, it empowers modern enterprises to transform incident management through advanced AI, seamless integration, and modular, domain-agnostic architecture.
Internal Quote
“With ResolvAI, our clients in energy operations are achieving 40% faster resolution, 30–40% lower support costs, and 95%+ precision across recommendations. ResolvAI embodies LTIMindtree’s philosophy of intelligent automation that learns and adapts. Its domain-agnostic, plug-and-play architecture and conversational refinement in Teams empower frontline responders while protecting service reliability.”