Groundwater is a lifeline for rural and urban communities, yet its quality is often compromised by contaminants from agricultural and industrial sources. This study dives into the groundwater quality of Samoda, Chhattisgarh, analyzing data from 45 sites to uncover patterns and assess safety for consumption. Through advanced visualization tools and machine learning model, the proposed work transforms complex water quality metrics such as Water Quality Index (WQI), nitrate, fluoride, and pH into actionable insights. Its findings reveal that while much of the region’s water is suitable for drinking, certain areas suffer from elevated nitrate and fluoride levels that may impact health. This research not only highlights the need for targeted interventions but also provides a model for proactive water quality monitoring. By empowering local authorities with data-driven insights, this study aims to help secure safer groundwater for communities and support sustainable resource management across similar regions.