CSV AI Analysis for Financial Data, Without Uploading It

Finance and accounting data is some of the most sensitive information a business handles. Revenue by customer, payroll runs, bank exports, unpaid invoices, and transaction ledgers may all require careful access and transfer controls. AskCSV lets you analyze financial CSV data with AI by opening the file in your browser, querying it there, and asking questions in plain English — with the SQL behind each answer on screen.

What changes when you analyze a financial export with AI

Many spreadsheet and analysis tools upload a file to their servers and keep it according to their own policies, with no read-only guarantee and no way to see what was actually calculated. A general ledger export or payroll CSV is exactly the kind of file where those details matter.

AskCSV is specific about each part of that:

• Transfer and storage. The file stays in your browser and is not uploaded. Your question, the columns you share with a sample, and up to 100 rows of each query result are sent over HTTPS.
• Read-only queries. Every question runs as read-only SQL over the local file, so a query cannot modify or delete your data, read other files, or reach the network.
• What the AI sees is kept to a minimum. The AI provider (OpenAI) gets only your question, the file's name and row count, the columns you chose to share with up to 10 sample rows, up to 100 rows of each query result plus summary figures, and the earlier messages in the chat — never the file itself. Ask for the top 10 customers and those 10 rows go, so turn off any column the AI should not see.
• Verifiable numbers. Totals, counts, and trends are computed in code from the query result, and the generated SQL is shown with every chart.
• Stated retention. Files and chats stay in this browser until you delete them or clear the site's data; guest credits expire 7 days after they are issued.

That combination is what makes a financial review tractable: a named sub-processor, a retention window you can point to, and numbers you can check.

What you can actually do with it

Once your file is loaded, you can ask the kinds of questions you'd normally build a pivot table or formula for — just in ordinary language:

• "What was total revenue by month, and which month grew fastest?"
• "Show me the top 10 customers by outstanding balance."
• "Flag any transactions above $10,000 in the last quarter."
• "What's our average days-to-payment per client?"
• "Compare this year's expenses by category against last year."

Because it understands your columns, you don't need to know SQL, write formulas, or clean up headers first. You ask, it answers — often with a chart you can read at a glance.

How to analyze your financial CSV

1. Open the app. Head to the AskCSV homepage at /. There's nothing to install, nothing to prepare, and no account needed to try it.
2. Open your CSV. Add your financial or accounting export, or paste the data directly. It is read in your browser and kept in this site's storage for your account or guest session.
3. Ask your question in plain English. Type what you want to know, exactly as you'd ask a colleague.
4. Read the answer. You'll get numbers, tables, and charts, with the SQL query that produced them.
5. Keep going or return later. Follow-up questions refine the same analysis. You can delete the file at any time, or leave it until you choose to remove it.

What this does and does not change

Working this way removes the guessing from a financial review: you can name the AI sub-processor, point to a retention window, and check the query behind a total instead of trusting prose. You should still evaluate the fit for your own requirements — whether the question, the sample and the query results you share may go to a model provider, who can reach your account, and what your contracts or regulators require.

If the question, a sample or a query result may not leave your machine under any circumstances, keep the analysis entirely offline. Otherwise, the useful question is which provider, which data, and how long — and those answers are on the privacy policy and the data-handling walkthrough.

Try it with your own file

If you've been holding back on analyzing financial data because the tools you looked at were vague about where the file goes, start with a non-sensitive sample. Open a file you are authorized to use at /, ask one question, and read the SQL under the chart. Guest use needs no account, and nothing needs to be installed.