Client Overview
The client is a multinational energy corporation operating across exploration, production, refining, and marketing of petroleum. With a footprint in over 180 countries, the client ranks among the largest non-state-owned oil and gas companies globally, producing over one million barrels of crude oil daily. Beyond petroleum, the client has substantial interests in petrochemicals, coal, mineral mining, and geothermal energy. The client is deeply committed to delivering affordable, reliable, and cleaner energy to support human progress.
The Need for Change
The client’s legacy application landscape was becoming increasingly difficult to maintain, scale, and secure. With rising infrastructure and licensing costs, limited agility, and growing technical debt, the organization needed a strategic shift toward a modern, cloud-native architecture. The lack of standardization and manual development processes slowed down innovation and impacting time-to-market. These challenges underscore the urgent need for a comprehensive modernization initiative powered by Gen AI to drive efficiency, reduce costs, and future-proof the technology ecosystem.
Gen AI Application Modernization was required to address the limitations of the client’s legacy systems. It focused on accelerating digital transformation across legacy systems, enhancing operational efficiency and decision-making through intelligent automation. Additionally, it aimed to improve data accessibility and insight generation across complex energy workflows, while supporting the client’s sustainability goals by enabling smarter energy management and predictive maintenance. GitHub Copilot for development also played a pivotal role in this transformation by enabling AI-assisted coding, reducing manual effort, and accelerating delivery timelines.
Business Challenge
The client faced significant challenges in modernizing a vast portfolio of legacy applications. Key hurdles included:
High dependency on legacy SMEs for business logic extraction
Complex architecture analysis and redesign
Manual and repetitive development tasks
Inconsistent code quality and performance
Lengthy testing cycles and high defect density
Manual deployments
LTIMindtree Solution
LTIMindtree deployed a 75+ member team across 5 agile pods to drive modernization using GitHub Copilot, a Gen AI-powered development accelerator. The engagement spanned over 2 years, operating under a fixed-price agile model. Gen AI Application Modernization was central to this initiative, enabling accelerated development, improved code quality, and enhanced productivity across modernization efforts.
Key offerings:
* Click on Solution Names to read more
Program and scrum management
End-to-end governance of the modernization initiative through agile delivery frameworks. LTIMindtree ensured seamless coordination across teams, including sprint planning, backlog grooming, and stakeholder alignment among multiple stakeholder groups with conflicting priorities, to maintain velocity and quality.
Low-level design and PaaS migration
Legacy applications were reimagined and redesigned for Azure PaaS by a team of client architects. The modernization team was responsible for the low-level design, enabling scalability, resilience, and cost efficiency. This included in-depth architecture analysis, decoupling monoliths, and leveraging cloud-native services to achieve optimized performance.
Application refactoring and re-platforming
Legacy codebases were refactored to align with modern frameworks (C#, .NET Core, Angular), ensuring SAST scan compatibility and improving maintainability and performance. Applications were re-platformed to a custom application in Azure, reducing infrastructure overhead, licensing cost for off-the-shelf SaaS products, and enhancing integration capabilities.
Gen AI Adoption and Benefits Realized Across SDLC
Requirement analysis and design
- Business logic extraction: Automated and accelerated requirement analysis and design using Gen AI-powered tools, reducing dependency on manual documentation and SME input.
- Architecture analysis: Enhanced architecture analysis, enabling faster understanding of legacy systems and supporting “first-time-right” design decisions.
- CI/CD pipeline design: Streamlined CI/CD pipeline design through intelligent automation and standardized templates.
Development
- Code generation (.NET & Angular): Accelerated code generation and refactoring for modern frameworks (e.g., .NET, Angular) using AI-assisted development tools.
- Performance optimization: Improved code review and standardization processes, resulting in more maintainable and consistent codebases.
- Unit test automation: Enabled automated unit test creation and improved test coverage through Gen AI-driven approaches.
Quality assurance and DevOps
- Code quality improvement: Fostered greater collaboration and innovation by embedding Gen AI into daily workflows across agile teams.
Benefits
15% improvement in productivity during assessment and design
Gen AI-assisted analysis and documentation accelerated the understanding of legacy systems, enabling faster and more accurate gathering of requirements and design of solutions. GitHub Copilot for development further enhanced this process by enabling AI-powered code generation, reducing manual effort, and streamlining development workflows.
35% reduction in lead time for business logic extraction
GitHub Copilot helped automate the reverse engineering and extraction of embedded business logic from legacy code, reducing reliance on SMEs and speeding up modernization.
45% faster CI/CD pipeline design cycles
Automated generation of Ansible roles and pipeline templates streamlined DevOps setup, significantly cutting down design time.
30% increase in code generation throughput (.NET & Angular)
AI-assisted code generation enabled developers to rapidly convert legacy code into modern frameworks, boosting delivery speed and reducing manual effort.
40% reduction in unit testing effort
Automated generation of unit test cases improved test coverage and reduced the time and effort required for manual test creation.
25% reduction in UAT defect density
Quality-optimized and standardized code, along with a shift left strategy and early defect detection, resulted in fewer issues during user acceptance testing.
20% reduction in bugs post-modernization
Enhanced code quality, adherence to standards, and AI-driven reviews contributed to a more stable, robust, scalable, and reliable application landscape.
Conclusion
By integrating GitHub Copilot across the software development lifecycle, LTIMindtree enabled a seamless modernization journey for a global energy giant. The initiative not only accelerated delivery and reduced costs but also significantly improved code quality, performance, and team productivity. GitHub Copilot for development was instrumental in driving AI-assisted development, streamlining workflows, and enhancing engineering efficiency. The success of this engagement highlights the transformative potential of Gen AI in large-scale enterprise modernization.
Transform. Accelerate. Modernize.
See how Gen AI-powered modernization delivers real business results. Write to us at eugene.comms@ltimindtree.com to begin your journey.
