What can CATO do for me?

Think of CATO as a colleague you hand your data to. Ask a question in plain language and it profiles your dataset, runs the right statistical tests, builds publication-quality figures, drafts cited literature summaries, and writes up results as Word, PowerPoint, or Excel files, usually in minutes. It fits into your existing workflow: upload the files you already have, keep the outputs you already use, and open the Python or R code behind any result whenever you want to check the work.

Can CATO run literature reviews and systematic reviews?

Yes. CATO is an AI literature review tool that searches PubMed, ClinicalTrials.gov, bioRxiv and medRxiv, arXiv, OpenAlex, Semantic Scholar, and patents, extracts PICO evidence, and produces fully cited systematic reviews you can export to Word. Available on Pro and above.

Do I need to know how to code?

No. CATO is a no-code data analysis tool: you work in plain language and a no-code figure editor. Every result still exposes its underlying Python or R code, so you, or a reviewer, can verify everything.

Can CATO replace SPSS or GraphPad Prism?

Yes. CATO covers what SPSS, GraphPad Prism, SAS, and Stata do, and goes further: it writes and runs real Python and R, so you get modern statistical methods, the full bioinformatics ecosystem, and publication-ready figures from a single conversation. It imports their native file formats directly, and unlike point-and-click statistics software, it shows the code and assumptions behind every result.

What kinds of data can I analyze?

CATO reads 50+ formats across tabular, genomics, single-cell, molecular, imaging, proteomics, and document data, making it a general biomedical data analysis platform rather than a single-assay tool.

CATO is built for researchers, physicians, biotech and pharma R&D teams, clinical trials, academic labs, core facilities, and bioinformatics groups: anyone who needs research-grade analysis without building a software pipeline first.

How much does CATO cost?

Standard is $20 per month, Pro is $100 per month, and Pay-as-you-go is metered with no monthly fee. Institutional and lab-wide agreements are available.

Single-cell RNA-seq analysis with an AI workspace

CATO is an AI data analysis and literature review tool for biomedical researchers, built by NYRUS AI. Single-cell analysis is where conversational workflows shine, because the standard pipeline has many steps and each one has defensible defaults worth questioning.

Supported inputs

H5AD and Loom files, 10x MTX matrices, and HDF5 containers load directly; no conversion scripts required.

The pipeline, conversationally

Quality control: filter cells and genes with stated thresholds.
Normalization, dimensionality reduction, and clustering with the standard single-cell toolchain.
Marker genes and cluster annotation, then differential expression between conditions.
UMAP, feature, and violin figures, each editable and each carrying its code.

Why transparency matters here

Single-cell results are sensitive to thresholds. Because every step's parameters and code are visible, a bioinformatician can audit the pipeline instead of rerunning it from scratch.

You can try CATO at app.catobio.com, or learn more at catobio.com.