AI Driven Legacy Transformation Assembler to Java Modernization

Federal agencies continue to rely on decades‑old assembler applications that are increasingly difficult to maintain—constrained by aging infrastructure, shrinking legacy expertise, and limited documentation. IBM provides an AI‑driven, automated modernization approach that transforms these legacy systems into modular, event‑driven Java architectures optimized for cloud deployment. By combining AI techniques with AWS services such as Amazon Bedrock and Code Llama, this solution accelerates critical phases of legacy analysis, dependency mapping, and code translation. The solution can reduce analysis time by up to 40% and improve overall modernization efficiency by up to 70%, helping agencies rapidly uncover hidden business logic, eliminate obsolete components, and transition to secure, scalable modern platforms. IBM’s solution supports the stringent compliance needs of federal environments, including alignment with FedRAMP, FISMA, and OMB modernization guidance. Agencies such as the IRS and others can move from batch‑oriented Assembler systems to real‑time, event‑driven architectures without disrupting mission operations. The solution also enables improved standards alignment, supporting requirements such as FHIR, ISO 20022, and HL7 where applicable. With reusable modernization patterns, a patented parser framework, and customizable business glossaries, the Analyst and Renovation Catalyst ensures modernization outcomes are consistent, efficient, and aligned with both technical and business requirements. AI enhances rule extraction, insights, and code transformation, while AWS provides the scalable infrastructure needed for analysis, testing, and deployment. Together, they enable federal agencies to confidently modernize legacy workloads with reduced risk, greater speed, and long‑term architectural flexibility.