Extract Form Data From PDF in n8n

Extract Form Data From PDF is a PDF4me node action in n8n that reads the filled values out of a fillable PDF and returns them as a structured formData JSON object. Use it to turn returned application forms, signed intake sheets, or survey PDFs into database rows without anyone retyping the answers.

What this node does

PDF4me: Extract Form Data From PDF takes a completed fillable PDF from Binary Data, a Base64 String, or a URL, reads its interactive form layer, and returns every field as a name and value pair inside a single formData object. Text inputs, checkboxes, radio buttons, and dropdown selections all come back together, ready to map onto a spreadsheet row, a CRM record, or a conditional branch in the workflow.

Authenticating Your API Request

Every PDF4me node in n8n requires a valid Credential to connect with. Create or select one that holds your PDF4me API key so the workflow can authenticate extraction requests securely.

Get your API Key

Important Facts You Should Not Miss

The PDF must have real form fields

This node reads the interactive AcroForm layer. A scanned page or a flattened PDF has no field objects left to read, so route those to an OCR or AI parsing node instead.

Blank fields still appear in the output

An unfilled field comes back with an empty string rather than being omitted, so test for empty values downstream instead of assuming the key is missing.

Field names come from the form author

Keys match whatever the PDF designer named each field, and checkboxes return their export value rather than a guaranteed true or false. Run one sample file first and inspect the real output.

PDF4me node in n8n set to Action Extract Form Data From PDF, Input Data Type Binary Data, Input Binary Field data, Document Name document.pdf, and Custom Profiles under Advanced Options — PDF4me Extract Form Data From PDF parameters panel in n8n

Form Data Extraction vs Plain Text Extraction

Both approaches pull content out of a PDF, but only one gives you named fields. The distinction decides which node belongs in your workflow.

Approach	What you get back	Best fit
Extract Form Data From PDF	Named field and value pairs from the interactive form layer	Genuine fillable PDFs where every answer already sits in a named field
Plain text extraction	The visible page content as one flat string, with no field names	Static PDFs with no form layer, where you will parse the text yourself
AI document parsing	Model-inferred fields from any layout, including scans	Scanned, flattened, or wildly inconsistent documents with no usable form structure

What Parameters Does Extract Form Data From PDF Need?

Required: Action, Input Data Type, the field matching that input type, and Document Name. Custom Profiles under Advanced Options is optional.

Parameter	Required	What it does	Example
Action	Required	Selects the PDF4me node action to run. Choose Extract Form Data From PDF.	`Extract Form Data From PDF`
Input Data Type	Required	Format of the source PDF input. Choose Binary Data (from a previous node), Base64 String, or URL.	`Binary Data`
Input Binary Field	Conditional	Name of the binary property on the incoming n8n item that holds the filled PDF. Required when Input Data Type is Binary Data. Defaults to data.	`data`
Base64 Document Content	Conditional	Base64-encoded content of the filled PDF. Required when Input Data Type is Base64 String.	`JVBERi0xLjQK...`
File URL	Conditional	Publicly reachable HTTPS URL to the filled PDF. Required when Input Data Type is URL.	`https://example.com/application_form.pdf`
Document Name	Required	Filename of the source PDF, used for reference and tracking in the extraction request. Include the .pdf extension.	`application_form.pdf`
Custom Profiles	Optional	Advanced Options field for extra processing settings, supplied in a JSON-like format. Leave blank unless you have a specific profile to apply.	`{ 'outputDataFormat': 'json' }`

Output Fields

A successful run returns one n8n item carrying the extracted form values as JSON.

Field	Type	What it contains
`formData`	Object	Every form field read from the PDF, as a set of field name and field value pairs.
`formData.<fieldName>`	String	The name of an individual field exactly as the PDF author defined it, for example name, email, or country.
`formData.<fieldValue>`	String, Number, or Boolean	The value entered or selected for that field. Blank fields return an empty string, and checkboxes return their export value.

A typical response body looks like this:

{
  "formData": {
    "name": "PDF4me",
    "email": "",
    "country": "USA"
  }
}

How Do I Set Up Extract Form Data From PDF in n8n?

Add PDF4me to your n8n workflow and choose the Extract Form Data From PDF action.
In Credential to connect with, select your PDF4me credential or click Create New Credential and paste your API key.
Set Input Data Type to Binary Data (default), Base64 String, or URL and supply the matching filled PDF field.
Set Document Name to the source filename, for example application_form.pdf.
Leave Custom Profiles under Advanced Options blank unless you need a specific processing profile.
Execute the node, then map values from the returned formData object into the next step of your workflow.

Typical Setups

Workflow ExamplesCommon n8n workflow patterns using Extract Form Data From PDF.

Emailed application forms to a spreadsheet

An email trigger fires when a completed application PDF arrives.
Extract Form Data From PDF reads the attachment into a formData object.
A Google Sheets or Excel node appends one row, mapping each field name to a column.

CRM lead creation from intake forms

A cloud storage trigger fires on a newly uploaded intake PDF.
Extract Form Data From PDF pulls the contact details out of the form layer.
A CRM node creates or updates the record using the extracted name, email, and company values.

Conditional approval routing

A webhook receives a signed request form from an external portal.
Extract Form Data From PDF returns the requested amount and department fields.
An IF node branches to the right approver based on those values.

Batch digitisation of an archive

A Loop Over Items node iterates a list of archived form URLs.
Extract Form Data From PDF runs with Input Data Type set to URL for each file.
Each formData object is written to a database table keyed by the source document name.

Practical Tips

Run one sample file before you map anything

Field names and checkbox export values are set by whoever designed the form, so inspect the real formData output first instead of guessing the key names.

Test for empty strings, not missing keys

Unfilled fields are still present in the output with an empty value, so a simple key existence check will not tell you whether the user answered.

Check the PDF is not flattened

A form that looks fillable in a viewer may have been flattened on save, which strips the field layer. If formData comes back empty, that is usually why.

Send scans to an AI parser instead

Scanned paper forms have no interactive fields at all. Route those to Parse Document rather than expecting this node to read them.

Keep Document Name meaningful

It is used for reference and tracking on the request, so passing the real source filename makes execution logs far easier to audit later.

Validate before writing to a system of record

Add a check on required fields after extraction so an incomplete submission is flagged rather than silently creating a half-empty CRM record.

Cheat Sheet

Field	Value
Action	`Extract Form Data From PDF`
Input Data Type	`Binary Data`
Input Binary Field	`data`
Document Name	`document.pdf`
Custom Profiles	`{ 'outputDataFormat': 'json' }`
Credentials	`PDF4me API credential`
Returns	`formData object of field name and value pairs`

Common Questions

Does Extract Form Data From PDF work on a scanned or flattened PDF?+

No. This node reads values from real interactive form fields, the AcroForm layer described in the ISO 32000 PDF specification. A scanned page is just an image, and a flattened PDF has had its fields painted into static content, so in both cases there are no field objects left to read. For those files use an OCR or AI parsing node instead, such as Parse Document.

What do empty form fields return?+

A field the user left blank still appears in the formData object, with an empty string as its value. The key set reflects the fields defined in the PDF, not only the ones that were filled in, so downstream nodes should test for empty values rather than assume a missing key.

How are checkboxes and radio buttons returned?+

Checkbox and radio button fields return their underlying export value as defined in the PDF, not always a literal true or false. Common values include Yes, Off, or a named choice set by whoever built the form. Run the node once on a sample filled PDF and inspect the actual output before writing comparison logic against it.

Can I send extracted PDF form data straight to Excel or a database?+

Yes. The formData object is standard JSON, so any node that accepts item fields can consume it. Map formData keys onto columns in a spreadsheet, database, or CRM node placed after the PDF4me node, using the standard n8n data mapping approach.

What is the difference between extracting form data and extracting text from a PDF?+

Extracting form data reads named field values from the interactive form layer, so you get reliable key and value pairs such as email mapped to its entered address. Extracting text returns the visible page content as a flat string with no field names attached, leaving you to parse it. Prefer form data extraction whenever the PDF is a genuine fillable form.

Fill a PDF Form

The reverse operation, writing values into a fillable PDF instead of reading them out.

Parse Document

The fallback for scanned or flattened forms that have no interactive field layer left.

Extract Table From PDF

For tabular data laid out in rows and columns rather than named form fields.

Add Form Fields to PDF

Build the fillable layer in the first place, so later extraction has named fields to read.