Background
 
A global SaaS provider faced significant challenges with large volumes of legacy code written in COBOL, Delphi, and older .NET frameworks. These monolithic applications increased technical debt, slowed product innovation, and raised operating costs. The company deployed Generative AI and agentic agents to automate and accelerate code modernization, transforming 9 million lines of COBOL to Java, Delphi to .NET, and ASP.NET to .NET Core. What once required years of manual effort was reduced to months, delivering rapid ROI and enabling faster customer innovation.
 
Customer Outcome
 
End-users now benefit from faster feature releases, more reliable performance, and modernized SaaS applications that integrate seamlessly across devices and industries. Simplified navigation and improved responsiveness enhance customer satisfaction and loyalty.
 
Business Outcome
 
The SaaS provider cut migration timelines by over 70%, reduced maintenance costs by 40%, and accelerated time-to-market for new offerings. By leveraging Gen-AI automation, reusable code frameworks, and secure cloud-native practices, the company achieved significant productivity gains while future-proofing its platform portfolio across diverse verticals.
 
Technology Platform Options
 

1. Gen-AI Code Transformation Platforms

   • Examples: Accionlabs CodeMesh, Microsoft Copilot for Developers, IBM watsonx Code Assistant for Z, AWS CodeWhisperer, OpenRewrite.

   • Why: Automate large-scale code conversion, detect dependencies, and generate optimized, test-ready modern code.

2. Agentic Automation Frameworks

   • Examples: LangChain Agents, AutoGen (Microsoft), CrewAI.

   • Why: Deploy intelligent agents to orchestrate migration tasks, manage dependencies, and validate business logic continuity.

3. Application Modernization Toolkits

   • Examples: Google Dual Run, CAST Highlight & Imaging, Micro Focus Enterprise Analyzer.

   • Why: Assess legacy applications, prioritize modernization roadmaps, and reduce risks during migration.

4. Cloud-Native Runtime & Frameworks

   • Examples: Java Spring Boot, .NET Core, Kubernetes, Docker, GraalVM.

   • Why: Provide scalable, secure, and cost-efficient environments for re-platformed applications.

5. Testing & Quality Automation

   • Examples: Tricentis Tosca, Selenium, GitHub Actions, Jenkins.

   • Why: Ensure migrated applications are validated, regression-tested, and production-ready with minimal downtime.
     
     Connect below with an aiT specialist today to find out how to deploy 'AI Legacy code migration' across your organisation.