cross-platform analyses. Secondly, RamanSPy addresses challenges in data preprocessing by facilitating the compilation of reproducible pipelines to streamline and automatise preprocessing protocols. Thirdly, RamanSPy helps bridge the gap between RS data and state-of-the-art AI technologies within the extensive machine learning (ML) ecosystem in Python. Complemented by direct access to Raman datasets, preprocessing protocols and performance metrics, this provides the foundation for AI model development and benchmarking.