From question to figure
in one conversation.

Upload your data, ask in plain English, get statistical tables, publication-quality figures, and cited prose. All executed in real time.

No credit card required

0
biomedical tools
Gene lookup, pathway analysis, drug interactions, clinical trial search, and more
0
pre-loaded datasets
DepMap, GWAS Catalog, GTEx, DisGeNET, MSigDB, BindingDB
0+
Python packages
pandas, scipy, statsmodels, scikit-learn, lifelines, scanpy, DESeq2
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citation formats
JAMA, APA, Vancouver, AMA, NEJM, NLM, MLA
0+
AI tools per conversation
File reading, code execution, literature search, delegation to specialist agents

Talk to your data

Upload CSV, Excel, Parquet, or SAS files. Ask questions the way you'd ask a colleague. Cato reads your data, writes the code, executes it in a secure sandbox, and returns figures, tables, and interpretation in seconds.

10+ file formats including .fcs and .h5ad
CATO
CATO running code execution and saving results
Table 1. Baseline Characteristics by Treatment Arm
VariableTreatmentControlp
Age, mean (SD)62.4 (8.1)61.8 (7.9).71
Female, n (%)48 (41%)52 (44%).63
Stage III, n (%)67 (57%)71 (60%).68
ECOG 0–1, n (%)98 (83%)95 (80%).54
JAMA format · Smith et al., 2024
Test: χ² | df: 1 | 95% CI reported | Effect size: Cohen's d

Publication-quality output, every time

Every statistical test reports the test name, sample size, test statistic with degrees of freedom, 95% CI, exact p-value, and effect size. Figures are rendered in journal-ready styling. Reports export to DOCX with your preferred citation format.

7 citation formats (JAMA, APA, Vancouver, AMA, NEJM, NLM, MLA)
216

biomedical tools built in

Gene and protein lookup, pathway analysis, drug interaction checks, CRISPR sgRNA design, molecular docking, clinical trial search. All accessible through conversation.

Genomics
Pharmacology
Proteomics
Molecular Biology
Clinical Trials
Pathway Analysis
Drug Discovery
Biostatistics
Epidemiology
Bioinformatics
Immunology
Oncology

76 pre-loaded datasets including DepMap, GWAS Catalog, GTEx, and DisGeNET

Multi-agent AI architecture

Not one model, but a team. An orchestrator delegates to specialized agents, each picking the right approach for the task.

Orchestrator
Routes to specialist agents
Coder
Complex analysis
Reader
Multi-file exploration
Researcher
Literature search
Analyzer
Deep EDA

Built for researchers who need more

Literature search meets data analysis

Search PubMed and BioRxiv from the same conversation where you’re analyzing data. Cato returns formatted citations with PMIDs, DOIs, and full abstracts, then weaves them into your analysis narrative.

Real-time search across PubMed + BioRxiv/MedRxiv

Secure by design

Code runs in isolated Kubernetes containers with gVisor user-space kernel isolation. Network-isolated, non-root, ephemeral. Your data is encrypted at rest (AES-256) and in transit (TLS 1.3).

Each execution gets a fresh sandbox. Nothing persists.

It learns how you work

Cato remembers your preferences, your data conventions, and your analysis patterns across conversations. Prefer detailed stats? It runs them without asking.

Automatic memory extraction after every conversation

Healthcare data connectors

Built-in access to NPI Registry, ICD-10 (diagnosis + procedure), HCPCS Level II codes, and RxNorm for drug normalization. No separate API keys or setup required.

4 industry-standard healthcare APIs built in

Ask anything. Get results.

Run a Kaplan-Meier survival analysis by treatment arm

Full figure + log-rank test in seconds

Compare gene expression across clusters

Volcano plot + differential expression table

Search PubMed for recent pembrolizumab melanoma trials

Formatted citations with abstracts

Profile all my datasets and flag data quality issues

Variable-by-variable assessment

Export a DOCX report with JAMA citations

Downloadable Word document

Look up drug interactions for my compound list

Pharmacology database results

Plans for every stage of your research

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25 MB file uploads
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