This article provides a complete, practical walkthrough of the Extractfromfile Converttofile Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automating PDF and Image Text Extraction Into CSV Using n8n and Vertex AI
   
   Meta Description:
   Learn how to automate text extraction from PDFs and images using n8n, Google Drive, Vertex AI, and large language models like Gemini and OpenRouter. Convert complex documents into categorized CSV files with zero manual data entry.
   
   Keywords:
   n8n workflow, Google Vertex AI, Google Gemini, OpenRouter API, extract text from PDF, extract text from image, automate data entry, convert image to CSV, AI PDF parser, LLM-powered CSV generator, Google Drive automation, intelligent data extraction, Google PaLM, n8n Google integrations
   
   Article:
   
   Level Up Your Document Automation: Extract Text from PDF and Images to CSV Using n8n and Vertex AI
   
   Manual data entry is tedious, error-prone, and—let's face it—ripe for automation. Fortunately, modern AI tools can read PDFs and images with remarkable accuracy. Combine that with a no-code automation tool like n8n, and you’ve got yourself a powerful document processing workflow—fully automated and highly scalable.
   
   In this guide, we’ll explore a smart n8n workflow that extracts data from PDFs and images, uses AI to categorize it, and uploads neat CSV files directly to Google Drive. Thanks to integrations with Google Drive, Vertex AI, Gemini, and OpenRouter, you don’t need to write a single line of code.
   
   Let’s break down how this works.
   
   🧠 What This Workflow Does
   
   The workflow, titled "Extract text from PDF and image using Vertex AI (Gemini) into CSV", is built in n8n. It monitors a specific Google Drive folder for new PDF or image files. As files arrive, they’re automatically:
   
   - Downloaded,
   - Processed using AI to extract and categorize data,
   - Converted into structured CSV files, and
   - Uploaded back to a designated Google Drive folder.
   
   📁 Step-by-Step Overview
   
   1. Upload Files to Google Drive
      You'll start by uploading PDFs (e.g., bank statements) or images (e.g., photos of payment receipts) to a designated Google Drive folder. n8n watches this folder using a Google Drive Trigger set to poll every minute.
   
   2. File Type Routing
      A Switch node checks each file’s mimeType to determine if it’s a PDF or an image. It routes PDFs and images to separate download handlers.
   
   3. Download and Process File
      Depending on the file type:
      - PDFs are downloaded and passed to a text extraction node.
      - Images are downloaded and sent to Google's Vertex AI for optical character recognition (OCR).
   
   4. AI-Powered Data Categorization
      For PDFs:
      - Extracted text is sent to OpenRouter using the LLaMA 3.1 70B model for intelligent parsing.
      - The task prompt tells the AI to read and convert the bank statement into CSV format and categorize each transaction (e.g., "Groceries", "Utilities").
   
      For Images:
      - The image binary is fed into Vertex AI with a message to identify transaction records and return them as CSV rows with additional categorization.
   
   5. Convert & Export CSV
      Once the raw CSV is prepared by the AI, it’s passed to a Converter node and saved as a local file. This file is then uploaded to a separate “CSV Exports” folder in Google Drive as an organized data asset ready for use.
   
   🎯 What’s Inside the CSV?
   
   Each CSV file contains:
   - Date
   - Description
   - Amount
   - Category (inferred by AI)
   
   This makes the output ideal for further analytics using tools like Google Sheets, Microsoft Excel, or even business intelligence platforms like Looker Studio.
   
   🛠️ Technologies and APIs Used
   
   Here's a full list of all third-party services powering this workflow:
   
   1. Google Drive API
      - Triggers on file uploads
      - Downloads files
      - Uploads CSVs
   
   2. Google Vertex AI (Gemini + image OCR)
      - Processes images to recognize text
      - Interprets screenshots or photos of bank statements
   
   3. Google Gemini Chat Model (PaLM API)
      - Integrated via LangChain node
      - Helps process image data when passed by the workflow
   
   4. OpenRouter API (using Meta’s LLaMA 3.1 model)
      - Analyzes PDF text
      - Extracts and structures data
      - Categorizes transactions intelligently
   
   5. LangChain
      - Facilitates interaction between n8n and language models (such as Gemini and OpenRouter)
   
   6. n8n HTTP Request Node
      - Sends JSON-formatted queries with extracted text to language models
   
   📌 Setup Notes
   
   To make this workflow work seamlessly:
   
   - Enable your Google Cloud service account with:
     - Google Drive API access
     - Vertex AI access
   - For OpenRouter:
     - Create an account at openrouter.ai
     - Use Header Auth with the format: Authorization: Bearer {your API token}
   - Share your monitored Google Drive folder with the n8n service account:
     n8n-server@[your_project_id].iam.gserviceaccount.com
   
   💡 Pro Tip:
   Be sure to test with varied document layouts. The accuracy of extraction and categorization improves with clearer source files.
   
   🙌 Conclusion
   
   This n8n workflow automates the end-to-end process of reading financial documents, parsing them via AI, and generating structured CSV data—all without manual data entry. Whether it’s receipts, bank statements, or invoices, the combination of Google's AI models and OpenRouter’s high-performance LLMs makes it powerful yet cost-effective.
   
   By investing just a few minutes into setup, you’ll be saving hours weekly that would otherwise be lost to repetitive tasks. Welcome to the future of document processing.
   
   —
   
   Ready to deploy? Download this workflow or build your own using the modular components from this guide. Your business data deserves better than manual effort—and now, it can have it.
   
   — Written by AI Assistant for Smart Data Teams
   
   — 
   If you’d like to read more about advanced AI automations using n8n, check out this companion post by Rumjahn:  
   [Create an AI Agent for Analytics in n8n](https://rumjahn.com/how-to-create-an-a-i-agent-to-analyze-matomo-analytics-using-n8n-for-free/)

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.