About the client:
Our client is a leading transport technology company, specializing in innovative solutions for the logistics and transportation sectors. They develop critical systems that support complex operations and streamline processes.
Benefits Overview
Challenge
The client faced significant challenges due to their EJB 3-based system (mission-critical but outdated), which was vital for operations but increasingly difficult to maintain. The complexity and lack of documentation hindered modernization efforts, making traditional approaches slow and costly, leading to concerns over operational disruptions.
Solution Architecture:
Legacyleap led the modernization of the client’s EJB 3 system, leveraging Gen AI models to tackle the lack of documentation and the system’s complexity. The project began with automating code comprehension and business logic extraction, dramatically reducing the time and effort required to document and understand the legacy codebase.
AWS services complemented this effort by enhancing functionality and scalability. Amazon Bedrock’s Gen AI capabilities powered the analysis and documentation process, while Amazon Neptune was utilized as a vector database to map code relationships, ensuring smooth transitions during modernization.
Additionally, Amazon SageMaker enabled AI-driven risk assessment, safeguarding critical business functionality and mitigating operational risks.
By integrating Gen AI automation with a well-structured modernization framework, Legacyleap delivered a high-performing, maintainable system architecture that addressed the client’s immediate challenges and positioned them for future scalability.
High-level Architecture Diagram:
Results:
50% Faster Code Comprehension:
Reduced the time required to understand and document legacy code.
50% Faster Business Logic Extraction:
Streamlined extraction of critical business logic for modernization.
Enhanced Risk Mitigation:
Improved risk management throughout the modernization process.