DedupFuzzy AI

AI fuzzy matching & deduplication — no code

2 followers

AI fuzzy matching & deduplication — no code

2 followers

DedupFuzzy is an online fuzzy duplicate detection tool for spreadsheets and lists. Use AI-assisted matching to find near-duplicates, merge records, and clean company and contact data.

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Launch tags:Productivity•Analytics•Spreadsheets

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Hi There, I spent hours trying to match company names across two spreadsheets. Same company. Different spellings. "Tesla" vs "Tesla Inc" "Amazon" vs "Amazon.com Inc." "Apple Inc" vs "Apple Incorporated" "JP Morgan" vs "JP Morgan Chase" VLOOKUP? Failed. Formulas? A nightmare. Copy-pasting manually? Don't even ask. I knew there had to be a better way — one that didn't require a data science degree or a Python script. So I built it. 👇 Introducing DedupFuzzy — AI-powered fuzzy matching & deduplication for everyone. No code. No install. No frustration. Just upload your file → let the AI find the duplicates → download your clean data. In under 5 minutes. Who is it for? → RevOps & Sales teams cleaning CRM data before campaigns → Data analysts merging messy spreadsheets → Anyone who's ever wasted an afternoon on duplicates We're live at 👉 dedupfuzzy.com Free tier available..🙏"

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2mo ago

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p/dedupfuzzy-ai

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1mo ago

You don't need Python to deduplicate your data

Every time someone mentions deduplication online, the replies are:

"Just use pandas dedupe()"

"Write a fuzzy match script"

"Use the fuzzywuzzy library"

Helpful? Sure.

Accessible? Not for most people.

The reality: most of the people dealing with duplicate data are:

Sales Ops managers

Marketing analysts

CRM admins

Operations leads

They're not developers. They shouldn't have to be.

DedupFuzzy was built for them.

Upload a CSV or Excel file.

AI finds the near-duplicates.

Download the clean file.

That's it.

Tag someone on your team who's still doing this manually.

dedupfuzzy.com free to start, no credit card needed

#NoCode #DataTools #SalesOps #MarketingOps #ProductLaunch

p/dedupfuzzy-ai

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1mo ago

How DedupFuzzy handles company name variations

One of our most-asked questions:

"How does DedupFuzzy know that 'Google LLC' and 'Alphabet Inc.' are related?"

Here's what happens under the hood:

Step 1 Tokenisation

We break names into meaningful tokens, removing noise words like "Inc", "Ltd", "Corp".

Step 2 Similarity scoring

Multiple fuzzy algorithms run in parallel and vote on the match quality.

Step 3 AI adjudication

Our model weighs the scores and flags pairs above your chosen confidence threshold.

Step 4 You decide

We show you the matches you approve, reject, or merge.

No black box. Full control.

This is why DedupFuzzy catches matches that simple exact-match or even basic fuzzy tools miss.

Curious how it handles YOUR data? Upload a sample free.

dedupfuzzy.com

#AITools #FuzzyMatching #DataEngineering #ProductFeature

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