Free Tool

Text Normalization Tool

Normalize text for matching — lowercasing, accent removal, whitespace standardization, and more.

Tilores uses text normalization in production — so you can automate matching with rules you configure.

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Upload a CSV or JSONL file. Fields will be detected automatically.

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.csv or .jsonl · max 10MB

How it works

Text normalization is the first step in any entity resolution pipeline. Before comparing strings, you need to standardize them: convert to lowercase, remove accents (é → e), normalize whitespace, strip punctuation, and handle special characters. This tool shows how normalization transforms your input, which helps you understand why "Müller" and "MUELLER" can be matched after proper normalization.

Use cases in entity resolution

Data cleaning before matching

Input standardization

Cross-system data integration

Search query normalization

Related tools

Levenshtein Distance

Calculate the minimum number of single-character edits (insertions, deletions, substitutions) needed to transform one string into another.

Soundex Phonetic Algorithm

Encode strings by their phonetic sound — names that sound alike produce the same Soundex code.

Cologne Phonetic Algorithm

Phonetic algorithm optimized for German-language names — "Müller" and "Mueller" encode identically.

Don't implement this yourself

Tilores Studio runs the full entity resolution engine — text normalization plus configurable matching rules and real-time resolution — locally on your machine. Free, no account, no cloud. Load your own data and see it working in minutes.

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