A leading American mass media and telecommunications company was carrying the weight of legacy PERL systems that had powered its operations for years, but time was catching up with them. Those systems came with real performance limitations, rising technical debt, and scalability issues that made it harder to manage the large-scale, data-driven workflows the business depended on every day. To keep pace with modern technology and standards, the company needed to transition to a solution that was genuinely scalable and maintainable, but that transition came with real constraints. The primary challenge was achieving a seamless move to Java while preserving complex workflows and integrations that had been built up over time, all within stringent security requirements that couldn’t be compromised along the way
Ascendion’s approach began with an in-depth, AI-assisted analysis of the PERL codebase to document core functionalities, engineering AI agent-based workflows to map out an efficient transformation plan and drive a smooth, intelligent conversion from the start.
Ascendion deployed the AAVA Core GenAI Platform to drive a streamlined modernization process end to end. Agent workflows managed technical analysis, user story generation, code transformation, unit testing, and documentation, while GenAI models with customized prompts confirmed that function definitions met project standards. User stories and Gherkin-format test scenarios accelerated early project phases, and the PERL code was efficiently converted to Java Spring Boot, backed by extensive JUnit test cases for enhanced validation. With the AAVA GenAI Core platform powering the effort, Ascendion redefined legacy system modernization, performing a true end-to-end transformation from user stories all the way to final documentation.
Tech Stack:
Delivered a 60% reduction in manual conversion time.
Achieved a 40% improvement in testing efficiency.
Enabled 30% faster deployment, enhancing time-to-market capabilities.
Delivered detailed AI-generated artifacts and developed a scalable conversion framework for future modernization efforts.
