Fuzzy list match
Pair up items from two lists even when they differ by typos, spacing, or accents.
Fuzzy list match
Paste two lists and this tool pairs up the items that are alike, even when they are not written identically. It handles the everyday mess exact matching cannot: a customer list where "Jonathan Smith" needs to line up with "Jon Smith", an export where "café Latte" should match "cafe latte", or two columns where one entry has a stray comma the other lacks. Each pair is scored by similarity, so you see exactly how close a match is instead of guessing.
Two options control how forgiving the comparison is. The similarity threshold sets the minimum score, from 0 to 100, a pair needs to count as a match. The metric picks how that score is calculated: Levenshtein distance counts the edits needed to turn one item into the other, which suits short strings like names and codes, while character-trigram similarity compares overlapping three-letter fragments and copes better with reordered or partially rewritten text. Ignore diacritics, ignore case and ignore punctuation strip out formatting noise that should not count against a match, and normalize word order lets "Smith, Jonathan" match "Jonathan Smith" by comparing words as a set rather than in sequence.
By default each item matches at most once, to its single best counterpart — turn that off to let an item match everything above the threshold, useful when auditing near-duplicates rather than linking clean lists. Unmatched items are listed separately when that option is on, so nothing disappears silently. Choose plain pairs for a quick read, or CSV with score for a spreadsheet.
Everything runs locally in your browser: neither list is uploaded anywhere, which matters when the data is a customer or contact list. Copy the result, download it as a .txt file, or send it straight into another tool to keep working.