Case Study 3
Charting a New Flight Path with AI-powered Migration at a Leading American Airline
Accelerating development efficiency through a seamless shift from TIBCO to Java
A leading American airline faced operational bottlenecks as it sought to modernize its IT infrastructure by migrating from TIBCO to an open-source Java platform. This transition was hindered by complex legacy systems and a lack of automation.
Legacy Dependency
Reliance on TIBCO BusinessEvents and BusinessWorks interfaces made system scaling and innovation challenging.
Manual Inefficiencies
Existing migration processes required significant manual effort, slowing project timelines.
Technological Limitations
Extracting business rules and maintaining coding standards during migration proved time-intensive and prone to errors.
Infosys partnered with the airline to deploy an innovative AI-powered migration framework, ensuring a seamless and efficient transition to Java.
Automated Code Migration
Implemented Infosys Code Migrator to replace TIBCO with Java, reducing manual effort and errors.
Gen AI-based Optimization
Used generative AI to extract business rules from TIBCO code to streamline and optimize migration.
Custom Processing Mechanisms
Configured LLM parameters to improve outputs for XML/JSON mappings and coding standards validation.
Human-in-the-loop Framework
Delivered an outcome package enabling iterative improvements post-migration.
The migration significantly enhanced operational performance, delivering efficiency across multiple domains and setting the foundation for future scalability.
Development Turnaround Accelerated through Automation
Achieved a 40% faster development cycle through AI-powered automation for code conversion and optimization.
Coding Standards Improved through Generative AI
Automating tasks like code cleansing and keyword replacements ensured better quality and compliance.
Integration Capabilities Enhanced through Updated Framework
Successful handling of SOAP/REST service calls and trigger configurations with seamless Java integration.
Combining generative AI with a human-in-the-loop approach ensures both high efficiency and reliability when modernizing legacy systems.
