cReate
From question to insight—R code and visuals in seconds
Upload a dataset, ask in plain English, and get clean R code with publication‑ready plots. Collaborate in real-time with your team, share datasets, and track every version.
Everything you need for data analysis
Powerful features designed to make your research faster and more collaborative
AI-Powered Chat
Ask questions in plain English. Get tailored R code that fits your data and intent instantly.
Real-time Collaboration
Work together seamlessly with live edits, team chat, and real-time code collaboration.
Shared Datasets
Share datasets with your team for consistent analysis across projects.
Version History
Never lose your work. Full version history with plots, code snapshots, and easy restoration.
Privacy First
Your data stays yours. Private by default with optional data randomization for extra security.
Clean, Editable Code
Transparent outputs you can tweak, run, and reproduce. No black boxes—just clean, readable R code.
Built for teams
Collaborate seamlessly with powerful team features
Invite Collaborators
Invite team members with edit or view-only access. Manage permissions and roles easily.
Team Chat
Built-in collaboration chat. Share code selections, discuss changes, and communicate in real-time.
Shared Datasets
Share CSV files with your team for consistent analysis.
Live Editing
See who's editing in real-time. Typing indicators and live cursors keep everyone in sync.
How it works
Four simple steps from raw data to publication‑ready visuals
Upload your data
CSV or spreadsheet—cReate previews columns and types automatically.
Ask in plain English
Describe the plot or analysis you need. No R experience required.
Review editable R code
Transparent, clean code you can tweak, run, and reuse.
Get beautiful visuals
Publication‑ready plots with consistent themes and accessibility in mind. Save versions and restore anytime.
"Make a bar chart of average mpg by cylinder count."
library(dplyr) library(ggplot2) mtcars %>% group_by(cyl) %>% summarise(avg_mpg = mean(mpg)) %>% ggplot(aes(x = factor(cyl), y = avg_mpg, fill = factor(cyl))) + geom_col() + theme_minimal() + labs(x = 'Cylinders', y = 'Average MPG')