Artificial Intelligence for legacy modernisation

Generative AI is driving legacy modernisation towards an era of automation and enhanced value extraction, reshaping the trajectory of modernisation efforts.

Modernisation solutions

From Code to Doc, to new Code

Automated reverse-engineering from code to documentation, then to new code is key in modernisation. Utilising Large Language Models, the process thoroughly documents and refines legacy code, aiding translation into an Object-Oriented codebase. Incorporating guidelines and target architecture ensures a smooth transition, facilitated by reinforcement learning from human feedback for iterative conversion. Thorough validation is ensured through comprehensive test case sets and rigorous comparative testing for iso-functional coverage verification.

This method significantly reduces time and effort for modernisation, while enhancing code quality and aligning with contemporary architectural patterns. Furthermore, it bridges knowledge gaps, streamlining the entire process.

From Code to new Code

This approach involves automating the transformation of existing code into modernised versions for improved efficiency and compatibility. Reply is currently developing and testing an AI-powered Translation Framework to streamline code translation between programming languages, simplifying transitions to different platforms. By leveraging copilot tools, developers refine source code and adhere to standard conventions, while machine learning streamlines it into industry-specific processes. The integration of OpenAI API and Large Language Models facilitates effortless translation from source to target, with a final human review ensuring both quality and security.

This process reduces time and effort, ensures quality, and enhances compatibility with contemporary patterns, streamlining development and improving performance.

An opportunity for a 'Legacy Renaissance'?

AI is not merely assisting in upgrading outdated systems; it transforms this challenge into an opportunity for strategic improvement rather than just an IT update. As the modernisation unfolds, Generative AI could unlock new scenarios for businesses to innovate more swiftly and efficiently, minimising the impact on existing systems through more effective processes of collecting and formalising business requirements. This innovative approach expedites time-to-market by capitalising on previous investments in core systems, without significantly restricting business opportunities.

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