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Data

Clean messy spreadsheets and reports

Everyone knows the half-hour that disappears into cleaning a sheet before you can use it. The data’s all there — it’s just wearing the wrong clothes. Dates in three formats, currencies with and without symbols, a “Region” column where “US,” “USA,” and “United States” are three different things to a pivot table. Tedious, easy to get wrong, and exactly the kind of work that quietly eats an afternoon.

The usual AI answer is to upload the file and get a “cleaned” one back — and now you’re squinting at two versions trying to figure out what it touched. This mini app works the opposite way. Your sheet opens in an interactive grid on screen. Skynet flags issues in place, you see each proposed fix highlighted in the cell it affects, and you decide.

How it works

step 01

Upload the sheet

Drop in the messy file. It opens in a live, editable grid inside Skynet — the same rows and columns you know, not a summary or a chat description of them.

step 02

See the flags in place

Skynet scans for the usual suspects — typos, duplicate and near-duplicate rows, inconsistent date and number formats, mismatched units, stray whitespace, values that don’t fit their column — and highlights each one right where it lives, with the fix it suggests.

step 03

Accept or adjust each fix

Click to accept a suggestion, tweak it if Skynet guessed wrong, or skip it. Approve a whole category at once — “normalise every date to ISO” — or go cell by cell on the ones that matter. Nothing changes until you say so, so a clean sheet never costs you a wrong overwrite.

step 04

Export the clean version

When the grid’s tidy, export it back out — ready to drop into a report, a dashboard, or whatever needed it clean in the first place.

You point it at the file and review its work rather than trusting it blind.

Where this lands

The pre-work that used to gate every analysis shrinks to a few minutes of clicking through flags. You get a clean sheet you can actually trust, because you watched it get clean instead of taking a black box’s word for it. What took an afternoon of find-and-replace now takes ten minutes — and the next report starts from good data instead of a mess you half-fixed.

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