The complexity of Raman spectra often conceals patterns invisible to the human eye. Raman Base integrates machine learning tools that enable automated data clustering, similarity detection, and spectral classification. By leveraging AI, you can uncover relationships between spectra, materials, and experimental conditions.

The AI modules can perform dimensionality reduction (PCA, t-SNE), anomaly detection, and similarity mapping. This allows you to compare spectra within a dataset or across multiple projects, identifying trends, outliers, or material groupings.

For researchers, this means faster interpretation and new insights - without the need for manual preprocessing or scripting. The AI features are continuously updated to adapt to new Raman techniques and computational models, making your data analysis more powerful with every iteration.

Transform raw data into knowledge with the intelligence of Raman Base.