This ambitious project tackled a critical challenge for a prominent European bank: reducing costs and dependency on outdated legacy systems hosted on mainframes. With a significant portion of the institution’s IT workforce nearing retirement, the need for modernization became urgent. The bank partnered with AdvanceWorks to develop a cutting-edge software migration tool powered by generative AI, beginning with the transformation of an application hosted on the mainframe.

The migration tool features a user-friendly frontend for manual edits and validations while supporting advanced Large Language Models (LLMs) like ChatGPT and Gemini. These LLMs were pivotal in ensuring the system’s adaptability and accuracy in translating legacy code into modern formats. By embracing this transformative approach, the bank not only streamlined its migration process but also set the stage for a future-proof IT framework that enables seamless code conversion across programming languages.

Team Collaboration:
The project involved close collaboration between the bank’s internal IT team and AdvanceWorks’ AI specialists. A shared focus on innovation and adaptability ensured the successful integration of generative AI technologies into the bank’s processes. The streamlined and transparent communication fostered an agile working environment, enabling quick adjustments to challenges and aligning with the project’s objectives.

Goals achieved:

• Reduced dependency on retiring talent: By automating the conversion process, the bank minimized its reliance on COBOL expertise.
• Lowered mainframe costs: Transitioning legacy applications off the mainframe led to significant cost savings.
• R&D advancements: Developed an innovative framework with the potential to semi-automate code conversion between any programming languages, paving the way for long-term efficiency.

Results:
The successful deployment of the AI-driven migration tool has significantly enhanced the bank’s operational resilience. Costs associated with mainframe maintenance have been reduced, and the reliance on legacy skill sets has been mitigated. Furthermore, the initiative has positioned the bank as a leader in embracing AI to solve complex IT challenges, with a scalable framework that offers opportunities for future innovation.

Next steps:
AdvanceWorks will focus on refining and scaling the migration tool to cover additional legacy applications, ensuring broader adoption across the bank’s IT infrastructure. Emphasis will also be placed on evolving the framework to enable fully automated code conversion capabilities and integrating additional AI models to expand functionality. Regular training sessions will equip the bank’s IT staff with the skills needed to maintain and optimize the new system, ensuring sustained technological leadership.