👤 For pipe administrators and members
🔐 Available on all plans
🎯 For those who want to bring an existing database into Pipefy without creating records manually
Every operation that migrates to Pipefy carries a history. Employee lists, customer records, supplier databases — information that took months to build and needs to be available from day one.
The Importer App makes this transition straightforward. With it, you bring structured data from an Excel spreadsheet into Pipefy — creating cards in bulk, without manual entry and without relying on a technical team. No programming knowledge required.
📖 What you’ll learn here:
What the Importer App does
The Importer App reads an Excel spreadsheet (.xlsx) and creates a card in the pipe for each row. Each column in the spreadsheet is mapped to a field in the pipe — the employee name becomes the card title, the start date becomes the date field, the contract type becomes the select field, and so on.
The result: a database that would take hours to migrate manually becomes available in Pipefy in minutes.
The Importer App works for both creating cards in pipes and populating records in databases. This article covers importing into pipes — the most common case for those just getting started. Importing into databases is covered in a separate article in the trail.
Before you start: prepare your spreadsheet
The most important step in the import process happens before you open Pipefy. A poorly formatted spreadsheet is the cause of most errors.
A few mandatory rules:
Structural rules
- The file must be in XLSX format — not CSV, not XLS
- The first row must contain column headers — these are what will be mapped to the pipe fields
- Do not use merged cells or columns
- Remove filters and conditional formatting before saving
- Each row in the spreadsheet will become a card — make sure each row represents a complete request
Formatting rules by field type
Each field type in Pipefy expects a specific format in the spreadsheet. The table below summarizes the most common ones:
| Field type | Expected format in the spreadsheet | Exemplo |
| Short text / long text | Plain text, no formatting | John Smith |
| Data | MM/DD/YYYY or DD/MM/YYYY depending on account language | 03/15/2025 |
| Date and time | MM/DD/YYYY HH:MM | 03/15/2025 09:00 |
| Number | Numeric value without formatting | 1500 |
| Currency | Number without currency symbol or thousand separator, with decimal point | 1500.00 |
| Single or multiple select | Options separated by comma, no space | Full-time,Contractor,Intern |
| | Valid address in lowercase | john@company.com |
| Phone | Country code + number, no spaces or symbols | 5511999990000 |
| Tax ID | 11 digits in the format 000.000.000-00 | 123.456.789-09 |
| Company Tax ID | 14 digits in the format 00.000.000/0000-00 | 12.345.678/0001-99 |
| Assignee | Username, email, or user ID | john@company.com |
Date fields are the most frequent cause of import errors. Verify that the cell format in Excel matches the language configured in your Pipefy account — MM/DD/YYYY for accounts in English.
Always test with a small file first. Before importing 500 rows, validate the process with 5 to 10 records to ensure the mapping is correct.
- Complete formatting guide: Preparing spreadsheets for the Importer App
Step 1 — Activate the Importer App in the pipe
Access the pipe where you want to import the data. In the top menu, click Apps and search for Importer App. Click Activate.
After activating, the Importer App appears in the pipe side menu. Click it to get started.
Step 2 — Upload the spreadsheet
In the Importer App screen, click Import data and select the XLSX file you prepared.
Pipefy will read the spreadsheet and display a preview of the identified columns. Verify that all columns were recognized correctly before proceeding.
If any column doesn’t appear correctly, go back to the spreadsheet and check the cell formatting for that column. Columns with mixed formatting — numbers and text in the same column — are the most error-prone.
Step 3 — Map the columns to the pipe fields
This is the central step of the import. For each column in the spreadsheet, you indicate which pipe field should receive that information.
Pipefy tries to map automatically when the names match. Review each association before confirming — an incorrect mapping puts the information in the wrong field on every card created.
Mapping example for employee onboarding:
- Column "Name" → Short text field "Full name"
- Column "Start Date" → Date field "Start date"
- Column "Job Title" → Short text field "Job title"
- Column "Contract Type" → Single select field "Contract type"
- Coluna "Email" → campo Email "Email corporativo"
Spreadsheet columns that have no corresponding field in the pipe can be ignored during mapping. They simply won’t be imported — the other fields are not affected.
Step 4 — Confirm and import
With the mapping reviewed, click Import. Pipefy will process the spreadsheet rows and create a card for each one in the first phase of the pipe.
At the end, you’ll see an import summary: how many cards were successfully created and whether there were any errors on specific rows.
Rows with errors don’t interrupt the import of the others. Pipefy processes what it can and indicates which rows need correction. You can fix and reimport only the problematic rows.
Important limitations
Some information is not transferred by the Importer App — it’s important to know this before planning the migration:
- Attachments and files: not compatible with XLSX import. Must be added manually after the import
- Card IDs: automatically generated by Pipefy — custom IDs cannot be set
- Dynamic content: information that depends on other phases or automations needs to be configured separately
- Connection fields: require the record ID in the target database — do not accept free text
What about reference data? When to use a database
There’s an important distinction worth knowing: not every piece of data you bring into Pipefy needs to become a card.
Cards represent active requests — processes with a beginning, middle, and end. But reference data — like supplier lists, product catalogs, active employee records — is better stored in databases.
A database is a repository of structured information that can be connected to multiple pipes. Instead of typing the supplier name on every purchase card, you select a record from the database — and all associated information is already there.
If you have this type of data to migrate, the import process is similar — the Importer App also works for databases — but the flow has an additional configuration step.
- Learn more: What is a database in Pipefy
- How to import: How to import data into a database
Completion checklist
Before considering the import complete, verify:
☐ The spreadsheet is saved in XLSX format
☐ The first row contains the column headers
☐ There are no merged cells or active filters
☐ Date formats match the correct standard for the account language
☐ The column mapping was reviewed before confirming the import
☐ A test with a few rows was done before the full import
☐ Cards were created correctly and information is in the right fields
