This multi-phase framework presents a holistic, data-driven solution to contaminant tracking in the environment, exposure assessment, and pollution prevention. By integrating AI-driven material selection, hydrologic modeling, analysis of different water matrices, WBE, near real-time health diagnostics, and policy interventions, it creates a proactive approach to reducing hazardous chemical exposure at both individual and systemic levels. The framework aligns with global sustainability initiatives and regulatory standards and offers a scalable, adaptable model for industries, policymakers, and researchers working toward environmental and public health protection while also protecting the chemical industry and fostering innovation. By bridging the gap between scientific knowledge and regulatory action, this framework will reduce environmental contamination while promoting sustainable product development.