Tired of manually extracting data from PDFs? This tutorial shows how to build a PDF data extraction workflow in Needle that converts unstructured PDF content into structured, usable data.

Overview

The workflow automatically reads PDF files, extracts key information using AI, and outputs structured data to Google Sheets, databases, or JSON—turning static documents into queryable data in minutes.

Key Actions

1. PDF Upload or Trigger – Upload a PDF manually or trigger via file upload to Dropbox/Drive
2. PDF Content Extraction – Reads and extracts all text content from the PDF
3. AI Data Parsing – Identifies and extracts structured information (names, dates, amounts, addresses)
4. Data Structuring – Organizes extracted data into defined fields
5. Output – Exports to Google Sheets, database, or JSON file

What You'll Need

• PDF Files – Invoices, contracts, forms, reports, or any document type Tip: Works best with text-based PDFs (not scanned images, unless OCR is applied)
• Data Schema – Define what fields you want to extract (e.g., Invoice Number, Date, Total Amount, Vendor)
• Output Destination – Google Sheets, Airtable, database, or JSON file

How It Works

1. A PDF file is provided to the workflow (manual upload or automatic trigger)
2. The PDF content is extracted as text
3. AI analyzes the document to identify:
   • Document type (invoice, contract, resume, report)
   • Key entities (names, dates, monetary values, addresses, phone numbers)
   • Custom fields based on your schema
4. For example, for an invoice:
   • Invoice Number: INV-2025-001
   • Date: October 1, 2025
   • Vendor: Acme Corp
   • Total Amount: $1,250.00
   • Due Date: October 31, 2025
   • Line Items: Table of products/services
5. Extracted data is validated and structured
6. Output is sent to your chosen destination:
   • Google Sheets: New row added with all fields
   • Airtable: New record created
   • Database: INSERT query executed
   • JSON: File saved to cloud storage

Wrap-up

With this Needle workflow, you can automate the extraction of data from hundreds of PDFs—perfect for finance teams processing invoices, HR departments reviewing resumes, legal teams parsing contracts, or anyone dealing with document-heavy workflows.