AI Data Cleaner

Standardise messy real-world columns automatically.

Company names spelled six ways, addresses in four formats, job titles with no convention. The AI cleaner proposes a canonical form for each cluster of values, shows you the mapping, and applies only the changes you approve.

Rating
4.8(1.1K)
Monthly uses
134K
Price
Free account

or drag it here

.xlsx, .xls, .csv · processed locally, never uploaded

Files stay on your device

What it does well

  • Fuzzy clustering that groups variants before the AI names each cluster
  • Every change reviewable and reversible — nothing is applied silently
  • Mapping exported so the same rules can be reapplied next month

How to use AI Data Cleaner

  1. 1

    Upload your file and select the messy columns.

  2. 2

    Let the cleaner cluster similar values.

  3. 3

    Review the proposed canonical value for each cluster.

  4. 4

    Apply the approved mappings and download.

Watch a walkthrough

How to use AI Data Cleaner

2 min 18 s · captions included

Watch on YouTube

Common problems and fixes

Two genuinely different companies were clustered together.

Split the cluster in the review panel and raise the similarity threshold before re-running.

Clustering is slow on a large column.

Deduplicate distinct values first — clustering runs on unique values, so a column with few distinct entries is fast regardless of row count.

Frequently asked questions

What people say

Small thing, but the error messages actually tell you what to fix. AI Data Cleaner flagged a hidden character that had been breaking my lookups for weeks.
Grace Adeyemi · Project Manager ·
Exactly what I needed. AI Data Cleaner used to be a twenty-minute job with a macro I did not trust; now it takes one drag and one click.
Nikolai Petrov · Business Analyst ·
Small thing, but the error messages actually tell you what to fix. AI Data Cleaner flagged a hidden character that had been breaking my lookups for weeks.
Tomás Rivera · Research Assistant ·

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