Modernizing legacy mainframe applications is critical for enterprises seeking agility, security, and competitiveness. While these systems remain robust, they are becoming increasingly difficult to maintain due to skill shortages and integration complexity. We present WCA4Z, an AI-powered framework for understanding and transforming legacy code. WCA4Z combines static analysis, multi-agent systems, and large language models to automate key stages of the modernization lifecycle, including semantic code comprehension, modular refactoring, COBOL-to-Java transformation, and equivalence validation. The framework also offers strong support for LLM lifecycle management through configurable, reproducible workflows and an integrated dashboard.