Just Upload.
AI finds every match.
Clean messy company lists in minutes. Handles typos, abbreviations & formatting differences that VLOOKUP and exact match can't catch.
Upload a messy file → AI finds fuzzy duplicates → download a clean sheet.
No install required — runs in your browser. CSV & Excel support. Zero setup.
What is fuzzy deduplication?
Classic deduplication only catches rows that match exactly. In practice, customer and vendor data rarely matches exactly: "Acme Corp" vs "ACME CORPORATION", "St." vs "Street", or two people sharing a name with a middle initial in one file and not the other. Fuzzy duplicate detection scores how similar two records are and surfaces likely duplicates for human or automated decisions.
DedupFuzzy focuses on this problem space: you upload structured data, explore candidate pairs, and use tooling tuned for AI-powered matching workflows—combining similarity signals with LLM judgment so you are not blindly auto-merging uncertain rows.
What you can do with DedupFuzzy
How it works
- Upload your tabular data—CSV or Excel spreadsheets.
- Select the company name column. AI handles abbreviations, typos, suffixes, and formatting differences.
- Review matches, download clean results. Golden records merge duplicates into one best row.
Who it is for
- RevOps and sales ops cleaning CRM and lead lists before campaigns.
- Data teams merging acquisitions or legacy databases with inconsistent naming.
- Anyone searching for a dedup or fuzzy matching tool online without standing up infrastructure.
Frequently asked questions
Is DedupFuzzy the same as exact duplicate removal?
No. Exact dedup only removes identical rows. DedupFuzzy emphasizes similar rows that humans would often merge—ideal when your priority is data quality, not just byte-identical copies.
Does this replace my database or ETL?
DedupFuzzy is a focused deduplication assistant. Many teams use it for ad hoc files and proof-of-concept merges, then feed results back into warehouses, CRMs, or MDM tools.
How accurate is the matching?
Our engine achieves 99% accuracy on company name matching by combining multi-signal fuzzy scoring with LLM verification on borderline cases. It handles abbreviations, typos, legal suffixes, and formatting differences that trip up traditional tools.