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  • 40% Faster Mean Time to Resolution with ResolvAI

    Transforming an Energy Leader’s Incident Management with AI-Driven Efficiency and Excellence

    40% Faster Mean Time to Resolution with ResolvAI

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.

Market Trends

The global liquefied natural gas (LNG) market is undergoing a rapid transformation, driven by rising demand for cleaner energy sources, increased investments in infrastructure, and a strong push for operational efficiency. As countries seek to reduce carbon emissions and transition away from coal and oil, LNG has emerged as a strategic fuel for both domestic consumption and international export. In Africa, large-scale LNG projects are reshaping regional energy landscapes, attracting billions in investment and fostering economic growth. Companies are prioritizing digitalization, data-driven decision-making, and compliance with international standards to remain competitive and future-ready in a dynamic market environment.

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

Fragmented Knowledge Ecosystem

Resolution intelligence was siloed, causing repetitive troubleshooting and missed learning opportunities.

Low Operational Efficiency

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

No Systemic Learning Loop

Lack of instant feedback mechanisms prevented the organization from evolving based on past incidents, limiting agility and resilience.

Integration Complexity

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

SLA Breaches in High-Volume Pipelines

Frequent breaches impacted service reliability and customer trust, highlighting inefficiencies in current processes.

Integration Across Diverse Technology Stacks

Integration Across Diverse Technology Stacks

Complex environments demanded seamless integration of disparate data sources to ensure operational continuity and reduce risk.

LTIMindtree’s Solution

To address these challenges, LTIMindtree 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:

Contextual Ingestion

Ingested pipeline alerts via email or activity monitoring APIs. Applied past resolution intelligence for accurate, context-rich fixes.

AI-Powered Analysis

Utilized GPT-4o to analyze incidents, detect failures in real-time, pinpoint root causes, apply contextual fixes, and generate actionable recommendations.

Conversational Refinement

 Enabled feedback, rating, regeneration, and prompt-based improvements directly in Microsoft Teams, and continuously learns from user interactions.

Workflow Automation: Orchestrated end-to-end incident resolution with:

  • 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.

Enterprise Integration and Scale

Seamlessly integrated with Microsoft 365 and Power Automate using domain- and technology-agnostic architecture that supports plug-and-play deployment across environments.

Tech Stack

AI/GenAIGPT-4o
AutomationMicrosoft Power Automate
CollaborationMicrosoft Teams, SharePoint
Monitoring and ReportingPower BI
ITSM IntegrationJIRA, ServiceNow (Optional)

Benefits

Leveraging LTIMindtree’s ResolvAI automation framework delivered a range of measurable benefits and business value to the client. These benefits included:

 
Efficiency Gains

Efficiency Gains

40% reduction in mean time to resolution (MTTR), accelerating resolution cycles.

Cost Effectiveness

Cost Effectiveness

Estimated 30–40% savings by reducing manual effort and support overhead.

User Satisfaction

User Satisfaction

2× boost in user experience through conversational AI and faster outcomes (CSAT: 5.8 / 6).

Volume

Volume

150+ AI-generated recommendations delivered in production.

Accuracy

Accuracy

95%+ precision in AI-generated fixes, validated via user feedback.

Knowledge Reuse

Knowledge Reuse

Growing knowledge base for faster resolution and systemic learning.

Conversational Usability Led to Higher Efficiency

Conversational Usability Led to Higher Efficiency

There was high user engagement through the conversational refinement feature made available directly in MS Teams to review, rate, refine and regenerate AI powered contextual recommendations. This boosted the efficiency of incident resolution.

Conclusion

This case study demonstrates how intelligent automation can fundamentally transform enterprise incident management at scale. By seamlessly integrating AI, in this case LTIMindtree’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

 

— Principal Director, Data & Analytics at LTIMindtree.

“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.”

Plug AI into your enterprise ecosystem seamlessly for enhanced incident management.

Connect with us at eugene.comms@ltimindtree.com to learn more.

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