Data Cleaner & Normalizer
Smart Data Cleaner
Fix messy data in seconds with AI-assisted standardization, deduplication, and normalization.
Files Processed
AI Data Cleaner
Paste messy CSV data and get clean, normalized output in seconds.
Tell the AI how you want your data cleaned. Be specific for best results!
Want to process larger files automatically?
DatumFuse Pro integrates directly with AWS S3 for live cleaning pipelines.
From Messy Data to Flawless Datasets, Automatically
Stop wasting hours on manual data cleaning. Datum Fuse's AI assistant finds and helps you fix inconsistent formatting, typos, mixed data types, and more with just a few clicks.
Don't let data quality issues undermine your analysis. Our AI assistant scans your entire dataset for common errors and provides a simple, interactive dashboard to help you clean and standardize your data with confidence.
Your Interactive Data Quality Co-Pilot
A single typo, an extra space, or an inconsistent category name can break your entire analysis. Manually finding these errors in a large spreadsheet is a nightmare. Datum Fuse automates the detection process.
Our AI generates a clear, actionable report of all potential issues, from mixed-up casing and data types to semantically similar categories like "USA" and "United States". You review the suggestions, accept the changes you want, and apply them all at once.
A Comprehensive Suite of AI-Powered Cleaning Tools
Categorical Standardization
Unify "NY", "N.Y.", and "New York"
Our AI understands semantic context, finding and grouping variations of the same category. It intelligently handles typos, abbreviations, synonyms, and formatting differences.
Casing & Whitespace
Fix "Apple", "apple", and " Apple "
Instantly detect and correct inconsistent capitalization and pesky leading/trailing spaces that break filters and joins, with options to convert to UPPERCASE, lowercase, or Title Case.
Mixed Data Type Repair
Clean up columns with numbers and text
Identifies columns that are mostly numeric but contain stray text values like "N/A" or "-". You can choose to convert the entire column to a clean numeric type or keep it as text.
More Than Automation — It’s a Cleaning Co-Pilot
Smart Batch Suggestions
Our AI scans your entire dataset at once and presents a comprehensive dashboard of all potential quality issues, grouped by column.
You Are in Control
Datum Fuse suggests, you decide. Review every proposed change, see examples of affected data, and accept or ignore suggestions with a click. No "black box" cleaning.
Empty Column Detection
Automatically flags columns that are completely or mostly empty, allowing you to quickly remove them and reduce clutter in your dataset.
Coming Soon to the Data Cleaning Suite
Pattern & Format Validation
Ensure values in a column match a specific format (e.g., email, phone number, custom regex) and flag non-compliant entries.
Advanced Outlier Detection
Go beyond simple min/max. Our AI will use statistical methods (like Z-score or IQR) to identify potential outliers that could skew your analysis.
Automated Cleaning Pipelines
Save your accepted cleaning rules for a dataset and have them automatically applied to new data during our hourly syncs (Pro Feature).
Frequently Asked Questions
Ready to trust your data again?
Clean and standardize your entire dataset in minutes, not hours.
The AI Data Cleaner standardizes a messy dataset in a single pass. It normalizes inconsistent formatting — casing, dates, phone numbers, currencies — repairs malformed fields, and removes duplicate rows, then returns a tidy file. For file uploads it suggests specific cleaning actions per column so you stay in control of exactly what changes.
How it works
- 1
Add your messy data
Paste a CSV for a quick clean, or sign in to upload a file for guided, column-level cleaning.
- 2
Review suggested fixes
For uploads, the AI proposes normalization and standardization steps for each column that you can accept or skip.
- 3
AI applies the cleaning
It standardizes formats, fixes inconsistent values, and removes exact duplicate rows in one operation.
- 4
Download the tidy result
Export a consistent, analysis-ready dataset with the issues resolved.
Use cases
CRM & contact hygiene
Standardize names, emails, and phone formats and strip duplicates before importing into a CRM.
Spreadsheet consolidation
Normalize data collected from multiple people or sources into one consistent format.
Pre-import preparation
Clean an export so it passes the strict format rules of a downstream system or API.
Reporting consistency
Fix inconsistent categories and casing so group-bys and pivots aggregate correctly.
Why DatumFuse
One-pass normalization
Formatting, field repair, and deduplication happen together instead of across many manual steps.
Column-level control
On uploads you approve each suggested action, so nothing changes without your sign-off.
Smart deduplication
Removes exact duplicate rows while keeping your dataset structure intact.
Spreadsheet-friendly
Output is a clean CSV that drops straight into Excel, Sheets, or a database load.