Clean, Standardize, and Transform Your Spreadsheets in Seconds.
For data analysts, RevOps, and growth operators who want to spend less time maintaining data workflows and more time using them.
Upload your dataset
Drag and drop a CSV file here, or click to browse. A free account is required to clean your own files.
Watch the instant data clean, diff view, and audit receipt live, with zero friction.
Spreadsheets Are Fragile. Manual Sanitization Drains Analyst Bandwidth.
Data analysts and operations teams lose hours every week debugging regex, parsing mixed currencies, and standardizing formats by hand.
Mixed Numbers & Currencies Break Pivot Tables
A single column containing $1,200.50, €45.00, and ¥6,000 gets parsed as text strings, forcing manual regex across dozens of spreadsheet tabs.
Throwaway Python Scripts Consume 5+ Hours
Spinning up a Jupyter notebook just to strip whitespace, deduplicate email addresses, and standardize date formats breaks momentum and wastes senior technical bandwidth on commodity tasks.
Excel ‘Find & Replace’ Destroys Raw Data Lineage
Overwriting edge cases directly in source sheets leaves zero audit trails. When financial totals fail to reconcile with Stripe or your CRM, you are forced to re-download the raw exports and start over.
Automated Data Cleaning Without Leaving Your Workflow.
Engineered for precision and explicit data handling. Deterministic processing, auditable exports, and a clear retention window.
Dimensional Disentanglement
Automatically isolates numerical magnitudes from currency symbols and physical units without destroying source values. Normalizes currency formatting; optional FX conversion uses published rates.
Native Google Sheets Extension
Clean and standardize up to 50,000 spreadsheet rows directly from an in-sheet dark console sidebar. Non-destructive by design: writes outputs to an isolated Cleaned_Data tab.
4-Category EDA & Code Export
Inspect Pearson correlation heatmaps, null density charts, and value cardinality. Export clean data along with the self-contained, reproducible Python script that reproduces it.
From Messy Raw Data to Clean Outputs in Under 5 Minutes
A reliable four-step pipeline from raw spreadsheet ingestion to isolated execution and auditable exports.
Connect Your Data
Drag and drop any raw CSV or TSV file, or select a cell range directly in Google Sheets.
Configure Rules
Review automatically inferred datatypes, set target currencies, dates, and column actions.
Run the Clean
Automated rules and deterministic algorithms process your dataset server-side. Timing scales with row and column count.
Export Clean Data
Download clean CSV, Excel, Parquet files, or export the standalone Python cleaning code.
Data handling
Security posture you can describe to a reviewer.
Explicit retention, visible failures, and controlled execution — without unverifiable certification claims.
Temporary Processing Files
Uploaded and derived files are temporary. They are deleted within 60 minutes by default.
Sensitive Field Redaction
Sensitive fields are excluded or redacted before any optional model-assisted step. The default cleaning path does not call a model.
Controlled Execution
Model-assisted transformations are validated before they run, and all execution is restricted with resource limits. Not a hardware micro-VM.
Diff & Data-Lost Report
Every run reports rows in/out, cells modified, and dropped rows. When exact row identity cannot be reconstructed, the report says so.
Frequently Asked Questions
Everything you need to know about processing limits, data privacy, and workflow integrations.
Stop Wasting Hours Cleaning Spreadsheets by Hand.
Join analysts and operators who process clean, production-ready data in seconds. No credit card required.