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Turn messy CSVs intoproduction-ready data.
Upload a spreadsheet, map columns to your template, and CSV Engine handles the rest — sanitization, validation, dedupe, and export. No scripts, no spreadsheet acrobatics.
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contacts-q4.csv → Customers template
| # | Full name | Company | Status | |
|---|---|---|---|---|
| 1 | Ada Lovelace | ada@analytics.io | Acme Co | ✓ |
| 2 | Grace Hopper | grace@navy.mil | USN | ✓ |
| 3 | Alan Turing | alan @ bletchley.uk | Bletchley | → alan@bletchley.uk |
| 4 | Linus Torvalds | LINUS@kernel.org | Linux Foundation | → linus@kernel.org |
| 5 | Margaret Hamilton | — | MIT | missing email |
Trusted by data teams shipping clean imports every day
NorthwindAcme CoLumen LabsHelixParallaxFoundry
Built for clean data
Every step from raw CSV to clean record.
Replace brittle scripts and one-off spreadsheets with a repeatable import pipeline.
Drag-and-drop CSV
Upload spreadsheets up to millions of rows. Auto-detects delimiters, encodings, and headers.
Smart column mapping
Map source columns to your template with aliases and fuzzy matching — saved per template.
Sanitization rules
Trim whitespace, normalize casing, validate emails, parse phone numbers, fix dates.
Dedupe with confidence
Match on one or many fields, choose merge strategies, review conflicts before commit.
Validate before import
Preview every row, flag failures, and export only the records that pass your rules.
Reusable templates
Define a schema once. Reuse it across every import, every team, every customer.
How it works
From spreadsheet to source-of-truth in four steps.
01
Define a template
Describe the fields you accept, their types, and validation rules. Save it once.
02
Upload & map
Drop in a CSV. Map columns visually — aliases let mappings stick across files.
03
Clean & preview
Sanitize values, dedupe, see every transformation, fix edge cases before commit.
04
Export or sync
Download a clean CSV / Excel file or push the dataset into your database via API.
Sanitization, your way
Rules that turn human data into machine data.
Email normalization, phone parsing, currency stripping, casing rules — pick the transformations your team needs and apply them consistently across every import.
- Email: lowercase, trim, validate MX format
- Phone: parse E.164, drop invalid
- Names: title-case, strip emoji
- Dates: ISO 8601, locale-aware parsing
# sanitization-rules.yml
fields:
email:
transforms: [trim, lowercase]
validate: [format:email]
phone:
transforms: [parse:e164]
on_invalid: drop
full_name:
transforms: [trim, titlecase]
signup_date:
transforms: [parse:iso8601]
dedupe:
on: [email]
strategy: keep_latestReady to import clean data?
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