CATO is an AI data analysis and literature review tool for biomedical researchers, built by NYRUS AI. SPSS is IBM's long-standing statistical package, used across the social and health sciences for decades. Both run real statistics; they differ in how you work and what you pay.
How the workflows differ
In SPSS you navigate menus or write SPSS syntax: choose a test, configure its dialog, and read the output viewer. In CATO you upload a dataset and ask in plain language, for example 'compare treatment groups on the primary outcome and check the assumptions.' CATO profiles the data, selects and runs the appropriate tests in a sandboxed Python and R environment, and returns figures, tables, and the exact code and assumptions behind every result.
Transparency
SPSS output shows results but not reusable code unless you work in syntax. Every CATO result exposes the Python or R that produced it, which is what a reviewer or a collaborating statistician will eventually ask for.
File compatibility
CATO reads SPSS .sav files directly, alongside SAS, Stata, Excel, CSV, and 50+ research formats including genomics, single-cell, imaging, and proteomics data. Moving from SPSS does not require converting your archives.
Price
SPSS is licensed per seat at a significant annual cost. CATO's Standard plan is $20 per month, Pro is $100 per month, and Pay-as-you-go is metered with no monthly fee.
Where SPSS still fits
Teams with decades of SPSS syntax, institutional licenses, and validated SOPs may keep SPSS for legacy pipelines. For new analyses, researchers who want speed, transparency, and no coding overhead tend to prefer an AI-native workspace.
You can try CATO at cato.nyrus.ai, or learn more at nyrus.ai/cato.