Data analysis with AI is only useful if you can see how the answer was reached. Rixx treats your file the way a careful analyst would: it loads the data, inspects it, writes code, runs it, checks the output and then explains the result. You get the conclusion and the working behind it.
When a question reaches past your file, such as "is this growth rate good for our industry?", Rixx researches the live web and cites the benchmarks it uses. Your numbers come from your file. Outside numbers come with a link.
What Rixx does with your data
Upload CSV, Excel, PDF, Word or PowerPoint files and ask a question. In a job, Rixx runs Python and other tools in its own private workspace with pandas, polars, DuckDB, NumPy, SciPy and matplotlib. That means real computation on every row, not a guess from a preview of the first few lines.
- Clean. Fix types and dates, standardise categories, remove duplicates, handle blanks and outliers, and log every change.
- Compute. Group, pivot, join files, calculate growth, margins, retention and cohorts, and run SQL over large files with DuckDB.
- Test. Correlations, regressions, t-tests and other statistics with SciPy, explained in plain English.
- Chart. Line, bar, scatter, heatmap and cohort charts, as interactive charts in chat or native charts inside Excel and PowerPoint.
- Explain. A plain-English summary of what changed, why it probably changed and what to check next.
- Add context. Industry benchmarks, market data and public company figures, researched and cited inline.
An AI data analyst for the questions you actually ask
Most data questions are not "run a regression". They are "why did revenue dip in March?" or "which customers should we worry about?". Rixx works from questions like these, the way an AI data analyst should: it picks the method, says which method it picked and why, and shows the numbers.
| You ask | What Rixx runs |
|---|---|
| "Which regions drove growth this year?" | Group by region and month, year-over-year change, contribution to total growth |
| "Are customers who use feature X less likely to churn?" | Cohort split, retention curves, a significance test on the difference |
| "Is our price increase hurting conversion?" | Before/after comparison, segmented by plan, with a chart and the caveats |
| "Merge these three exports and find duplicates" | Joins on cleaned keys, fuzzy matching on names, a duplicates report |
| "How does our growth compare with the industry?" | Your growth rate from the file, plus researched and cited benchmarks |
| "Summarise this 200,000-row log" | DuckDB queries over the full file, then summary tables and charts |
Analyze a CSV with AI, step by step
Here is a typical CSV job, from upload to finished file.
- Attach the file and ask. "Here is our support ticket export. What drives long resolution times?"
- Rixx profiles the data first. It reports the columns, types, row count, missing values and anything odd, such as dates stored as text or a category spelled three ways.
- It cleans and computes. It fixes what it found, then breaks resolution time down by channel, priority, team and weekday.
- It checks itself. Rixx checks totals against the raw file, so a filter or join that dropped rows is caught before you see the result.
- It explains and delivers. You get the key drivers in chat with charts, and, if you ask, an Excel file with the cleaned data and summary tabs or a short Word memo for your team.
Ask follow-up questions in the same chat. "Now split that by customer tier" reuses the cleaned data rather than starting again.
Answer or job: which one runs your analysis
Rixx has two speeds, and Auto picks for you. You can also choose Job yourself.
| Answer | Job | |
|---|---|---|
| Best for | A quick question about a small file or a table in a PDF | Real computation, cleaning, charts and files |
| Private workspace with a full terminal | Yes: Python (pandas, polars, DuckDB, SciPy, matplotlib), plus command-line and office tools | |
| Output | A researched, cited answer in chat | Answers, charts and finished Excel, Word, PowerPoint or PDF files |
| Timing | Seconds | Runs in the background; leave and come back |
For anything with numbers that matter, a job is the right choice: every figure is calculated from your data rather than read off a snippet.
Your data plus the web
A file tells you what happened. It rarely tells you whether that is good. Rixx closes the gap by joining your results with researched context:
- Your churn rate next to published churn benchmarks for your segment.
- Your sales by country next to population or GDP figures from official statistics.
- Your pricing next to competitors' published prices, each with a source link.
Every outside figure is cited inline, so a reader can tell your data from the market's. For bigger questions, a job can run deep research on the market side while it computes the numbers from your file.
Files you can upload
- CSV and Excel workbooks, including multi-sheet files.
- PDFs up to 1,000 pages, with tables inside them; Word and PowerPoint files; images of charts or tables.
- Up to 50 MB per file and 5 files per upload, with up to 100 documents in one chat.
Working with Excel specifically? See AI to analyze Excel data. Need a new spreadsheet built from research? Use the AI spreadsheet generator. Building a model? Try the AI financial model page.
Tips for better results
- Say who the analysis is for. "For the board" and "for the ops team" lead to different summaries.
- Name the metric definitions you use. If churn means "no order in 90 days", say so.
- Ask for the code when you want to reuse it. Rixx can share the Python it ran.
- Ask for a change log when cleaning. You get a list of every row and value it changed.
- Ask Rixx to separate fact from interpretation. It will label what the data shows and what it infers.
Frequently asked questions
Which AI is best for data analysis?
The best AI for data analysis is one that computes on the full file, shows its method and lets you check the numbers. Rixx runs Python on your data in its own private workspace, shows the code and results, and cites any outside figure it adds from the web.
Can I analyze a CSV with AI for free?
Yes. Every plan, including Free, gets every feature, including jobs that run Python. Free includes 50 credits a day plus 500 a month. A quick cited answer uses a few credits; a job that cleans data and builds files uses more. You only pay for what a job uses. See pricing.
How big can my file be?
Up to 50 MB per file and 5 files per upload, with up to 100 documents in one chat. Rixx uses DuckDB and polars for large files, so it works across every row.
Does Rixx show how it got the answer?
Yes. Rixx explains the method it chose, shows the numbers at each step and can give you the Python it ran. It checks totals against your raw file before it reports results.
Can Rixx combine my data with web data?
Yes. Ask for benchmarks, market figures or competitor prices, and Rixx researches the web and cites each one inline next to your own numbers.
What files does it return?
Answers and charts in chat, plus Excel workbooks with working formulas and native charts, Word reports, PowerPoint decks and PDFs. Rixx renders and reviews each file before handing it back.
Is my data private?
Analysis runs in your chat's own private, isolated workspace, and your uploaded files stay in your account.