Verifiable data analysis
Ask your data.
See the code.
Curator turns a plain-English question into real Python, runs it on your actual rows in your browser, and shows every line behind the number. Not a guess — an answer you can open.
No credit card · Runs in your browser · 30 questions free
Verifiable, not just plausible
A number you can change and re-check.
Open the code behind any answer, edit a line — drop a filter, exclude a segment — and hit Run. The chart and the number update from your edit, not a black box. That’s the difference between a guess and an answer.
How it works
Three steps, nothing hidden.
Bring your data
Drop in a CSV, Excel, JSON, or Google Drive file. Every sheet becomes a table; load several and Curator finds the keys to join them.
Ask in plain English
q = df[df.quarter.isin(["Q3", "Q4"])]g = q.groupby(["region", "quarter"]).revenue.sum()g.unstack().pct_change(axis=1)
Your question becomes real Python, run in a sandbox inside your own browser tab. Your full file never leaves the page.
Get the answer + its code
Every result carries its proof one click away — the exact code, the rows it touched, the full trace. Edit a line and re-run anytime.
Built to be shared
A whole notebook, curated into one report.
When the analysis is done, turn the whole notebook into a clean, shareable report. One click for an AI summary of the findings — keep the code in for a technical audience or leave it out for a plain-English read — then export to PDF or share a link.
Do it once, then never again
Save an analysis. Run it on next week’s file.
Turn a finished notebook into a repeatable workflow. Drop in the new export and every step re-runs on the fresh data — same questions, same checks, new numbers. No rebuilding from scratch.
Your data, handled honestly
It runs in your browser — and we’re straight about the rest.
The honest version, not the marketing one: your file stays on your machine. The model sees your question and column names to write the code — never your rows, and your values are masked even when it phrases the answer.
Runs on your machine
Your file is loaded and analyzed in a sandboxed worker inside your own browser tab. The full dataset is never uploaded to, or stored on, a Curator server — there’s no ingest queue because the data never leaves.
- ✓ your question
- ✓ column names & types
- ✗ your rows
- ✗ your data values
Honest about what’s sent
To turn your question into Python, Curator sends the question and your column names and types — never your rows. When it phrases your answer in words, the values are masked before sending and restored on your machine, so your numbers never leave. See what’s sent →
The compounding part
Verified building blocks, not one-off guesses.
A chatbot regenerates the analysis on every question. Curator reuses code that’s already been checked — and run thousands of times.
correlation_pairIt reuses verified code
Ask the same question twice and you get the same trusted answer. Curator reuses building blocks that have already been checked and run — instead of re-writing the analysis, and re-rolling the risk, every time.
revenue_by_regioncertifiedcohort_retentionreviewedpct_change_by_groupreviewedseasonality_indexcommunity
It gets sharper over time
Every analysis can promote a block — community → reviewed → certified. The trusted library grows as it’s used, so reliability climbs over time instead of drifting.
Questions
The things people ask first.
How is this different from asking ChatGPT?
Do I need to know how to code?
What can I upload, and how big can it be?
Is my data private?
What does it cost?
Pricing
Simple, and free to start.
- 30 questions a month
- CSV, Excel, JSON & Google Sheets
- Join across multiple tables
- Every chart with its code, trace & data
- Share a clean report (export to PDF)
- Unlimited questions
- Everything in Free
- Curated reports — AI summary & custom pick-and-refine
- Cancel anytime
Ask your data something hard.
Put a real question to your spreadsheet — every answer comes with its receipts.
Open the workbenchNo credit card · Free to start