RamanSPy facilitates AI integration and validation of nextgeneration Raman data analytics. To help accelerate the adoption of AI technologies for RS analysis, RamanSPy is endowed with a permeable architecture, which streamlines the interface between Raman spectroscopic data and the burgeoning ML ecosystem in Python. This is complemented by tools for benchmarking, such as datasets and performance metrics, which support the evaluation of new models and algorithms. We show below two examples of RamanSPy's capabilities for ML integration and benchmarking.