Data Janitor for Small Business Spreadsheets
A drag-and-drop tool for non-technical small business owners that scans their CSV, Excel or SQLite files for type errors, broken values, and silent inconsistencies, then suggests fixes in plain English.
Small business owners and operations managers who keep customer or inventory data in spreadsheets
- Upload a spreadsheet or SQLite file and get a plain-English list of problems — text in a price column, dates in the wrong format, duplicate customer rows
- One-click cleanup that produces a corrected file with a change log the owner can review
- Watch mode that re-scans a shared Google Sheet or Dropbox file weekly and emails a digest
- Optional Zapier hook so a clean dataset flows straight into the CRM or accounting tool
The HN post about STRICT tables shows real frustration with databases that silently accept wrong types — small businesses hit the same pain daily in Excel and never know why their reports are wrong, so a plain-English auditor addresses a much bigger audience than the SQLite crowd.
Strong pain signal — 53% of ops pros deal with spreadsheet errors weekly and 94% of business spreadsheets reportedly contain errors — but the 'small business owner' buyer is rarely the one actively searching for a paid tool.Spreadsheet Errors: How Manual Data Mistakes Are Costing Operations Thousands ↗Spreadsheet Errors in Finance ↗
Sohovi explicitly markets itself as the non-technical data quality tool with plain-English reports and file-upload UX — essentially the same wedge. Sheetai.co also offers a free AI spreadsheet cleaner. The 'gap' the idea targets is already being filled.The Best Data Quality Tools for Non-Technical Users | Sohovi ↗Free AI Spreadsheet Cleaner | Clean Messy Excel & CSV Data Automatically ↗
Small businesses are price-sensitive — OpenRefine is free, SheetAI offers a free tier, Ablebits sells modest-priced Excel add-ins. Willingness to pay exists in the $10-50/mo range but not at enterprise pricing.Trifacta vs OpenRefine Cost (2026): One Winner for ROI ↗How to clean data in Excel with practical examples - Ablebits ↗
Spreadsheets and CSVs are structurally sticky for SMBs; the error problem is endemic and not going away with any near-term tech shift, giving the tool long shelf life.
Core tech (CSV/Excel parsing, type inference, duplicate/null detection) is commodity via pandas/openpyxl, and LLM-based plain-English explanations are straightforward — no infrastructure or data moat required.