I m building CSV Repair & Deduper and want to understand what proof matters before someone imports cleaned data into a CRM, store, or accounting system.
Which would give you the most confidence: a before/after row count, a list of duplicate groups, a change summary, column validation, or something else?
The tool runs locally in the browser, but local processing alone does not prove the output is correct. I d rather prioritize the audit evidence people actually use. Please don t share real customer data just the checks that matter in your workflow.
2. Data-quality issues exact duplicates and near-duplicates such as nickname or spelling variants.
I built CSV Repair & Deduper because both often need attention before a CRM, storefront, or mailing-list import. It runs locally in your browser and lets you review suggested duplicate removals before changing anything.
Repair malformed CSV exports and review exact or fuzzy duplicates without uploading customer data. This downloadable single-file tool runs locally in your browser, detects common delimiters and encoding issues, flags uneven rows, and lets you review, edit, undo, and export every change. Unlike automatic “black box” cleaners, near matches remain suggestions for human review. $19 once, no subscription.
