Rainwater chemistry helps to understand atmospheric deposition, acid precipitation and long-range transport of the pollutants. Therefore, systematic analysis of rainwater chemistry is essential to understand the sources, transformation and environmental impacts of the pollutants through deposition. Despite its importance, there is a gap that there is no analytical platform to study large and multi-site rainwater chemistry data. The presence of this type of platform will increase the efficiency and reproducibility of precipitation chemistry studies. We present WetChemX, a R web application that addresses this gap. The framework is designed to process multi-site and multiparameter rain chemistry data (excel or CSV format). Along with unit conversion, it incorporates a quality assurance and quality control (QA/QC) procedure based on internationally established guidelines. There are 11 modules in the WetChemX which include descriptive statistical analysis with calculation of volume-weighted mean concentrations and wet deposition fluxes; validation of ionic balance together with consistency checks for pH and electrical conductivity; assessment of neutralization factors, fractional acidity, ammonium acidity index, and differentiation of sea-salt and non-sea-salt contributions; estimation of nitrogen deposition (different species); and sulphur-nitrogen balance. Additionally, acid-neutralization ratios and a newly developed "Patel plot" designed to visualise neutralization ratios in rain chemistry datasets. Multivariate analysis is supported through principal component analysis (PCA) with varimax or promax rotation, while spatial patterns can be explored using Inverse Distance Weighting (IDW) interpolation with optional shapefile boundary integration. By integrating these features into a single platform, WetChemX reduces the technical barriers associated with precipitation chemistry analysis and offers a transparent and reproducible computational framework that can support large-scale monitoring networks.