ImportsStable3 steps

Clean Customer Import

Take a raw customer import, drop empty padding, coalesce a display name, and normalize contact fields into a clean, load-ready shape.

How it works

Pipeline

Trim, fill a name from fallbacks, then normalize email/phone/company.

  1. Transform
    • Trim stray whitespace from every field.
  2. Transform
    • Fill "name" from the first available of name, full_name, and contact.
  3. Normalize
    • Standardize "email" into a consistent email format.
    • Standardize "phone" into a consistent phone format.
    • Standardize "company" into a consistent company format.

Frequently asked

FAQ
Is this recipe ready to run?
Yes. This recipe is stable — every step maps to a shipped capability, so it runs and returns structured records today.
Can I customize the steps?
Yes. A recipe is a starting configuration. Install it into a project and you can add, remove, or reorder steps to match your own data.
What does it cost to run?
Recipes run on the same usage-based pricing as every capability. Start free with 1,000 usage units a month across everything — no credit card required.
How do I run it?
Install the recipe into a project from your dashboard to get a saved pipeline, then call it over the REST API, an SDK, or MCP — one request in, clean records out.
clean-customer-import · 3 steps · Stable

Run this recipe on your own data

Start free with 1,000 usage units a month across every capability — no credit card. Install the recipe, adjust the steps, and call it in one request.

Turn messy spreadsheet and customer imports into clean, load-ready data.