Overview

A leading European telecommunications provider relied on a mainframe-based payment management platform that was costly to maintain, difficult to scale, and dependent on scarce specialist skills.

Tech Mahindra validated an AI-led approach to modernize the platform with accelerated timelines and establish scalable platform for future digital services running on AWS.

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Industry Challenge

The client is a leading European telecommunications provider managing critical payment and collections operations. Their system sits on a mature, business-critical platform built on legacy mainframe technology. While it has reliably powered the business for years, its legacy foundations have become a barrier to what comes next —constraining scalability, increasing maintenance costs, and creating a compelling opportunity to modernize for the future.

Our Approach and Solution

We adopted a phased, AI-enabled approach to modernize the client’s mainframe environment while preserving core business logic.

  • Baseline Extraction: Key JCL and CA Gen components were converted to Java 1.8, establishing a controlled baseline for modernization.
  • AI-Driven Java Upcycling: Amazon Q Developer accelerated migration from Java 1.8 to Java 21 through code refactoring, validation, debugging, and test-data generation, while Claude Opus supported complex optimization.
  • Cloud-Native Integration: The solution integrated AWS services and technologies, including Amazon S3, PostgreSQL, HikariCP, EventBridge, GitHub Actions, CloudFormation, and Flyway.
  • AI-Infused Quality Engineering: GitHub Copilot accelerated test generation, automation, edge-case analysis, root-cause analysis, and documentation. Shadow-run validation was planned to compare the modernized application with the existing system before transition.

Business and Community Impact

Migration proved faster modernization, lower costs, stronger security, greater scalability, and improved productivity.

  • Faster Value: AI-led modernization reduced transformation timeline from about 24 months to seven months.
  • Lower Costs: Moving workloads reduced infrastructure costs by up to 50%.
  • Better Security: Modern, cloud-native technologies reduce legacy risks.
  • Simpler Technology: Java 21, PostgreSQL, AWS, and GitHub replace reliance on CA Gen and specialized mainframe tools.
  • Greater Scalability: The cloud-native platform supports easier scaling and future integrations.
  • Higher Productivity: Automation and AI reduced manual work and speed up development, testing, and validation.