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CSV import for SaaS

Add CSV import to your SaaS in minutes - not weeks

Auto-map columns, clean messy data, and import via API or UI widget - without building everything from scratch

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CSV import is a never-ending edge case nightmare

  • Every file is different - and breaks your logic
  • You keep patching edge cases instead of shipping features
  • Users don't understand what went wrong
  • Bad data silently corrupts your database
  • Support keeps getting "CSV doesn't work" tickets

Why teams choose csvy.io

Save an average of 80+ engineering hours

Building drag-and-drop, parsing edge cases, and validation UX is weeks of work. csvy.io gives you a focused path: configure your schema, embed, and move on to features your roadmap actually needs—instead of burning those hours on custom import UI.

Reduce data-related support tickets by 80%

When onboarding depends on spreadsheets, unclear errors kill momentum. Give users a flow that explains what broke and how to fix it—so “file won’t upload” tickets stop piling up and your team spends less time firefighting imports.

Product deep-dive

A calm path from spreadsheet to clean records

Your users see what will import, what won’t, and how to fix it—before you get bad data.

Scroll once. See each import step in context.

Keep this panel pinned while the product flow moves beside it. Users understand what happens at every stage.

Step 0

Configure once. Reuse forever.

Set your schema and validation rules once for predictable onboarding.

Step 1

Upload the file your user actually has

Preview rows and headers before anything touches your system.

Step 2

Auto-map columns to your schema

Match headers, resolve missing fields, and normalize values early.

Step 3

Validate with row-level errors

Catch bad rows with clear messages users can fix immediately.

Step 0

Configure once. Reuse forever.

Set your schema and validation rules once for predictable onboarding.

Reusable templates: 1 source of truth
Wireframe mockup showing destination table setup with columns, required fields, and validation rules.

Step 1

Upload the file your user actually has

Preview rows and headers before anything touches your system.

Rows scanned: 1,495
Wireframe showing CSV upload with invalid cells highlighted in a preview table.

Step 2

Auto-map columns to your schema

Match headers, resolve missing fields, and normalize values early.

Columns matched: 28 / 29
Wireframe showing column mapping with one unresolved field.

Step 3

Validate with row-level errors

Catch bad rows with clear messages users can fix immediately.

Rows ready: 1,482
Wireframe showing validation summary with ready-to-import state.

Import only validated records

No silent corruption and no cleanup week after launch.

Fewer stalled onboardings

Users fix files without opening a support thread.

Lead capture

Leave your request and we’ll set everything up for you in 10 minutes.

What you’ll get

  • Save an average of 80+ engineering hours
  • Reduce data-related support tickets by 80%

Step 1 of 4

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