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:
   How to Automatically Extract Text from PDFs & Images Using AI and Export to CSV with n8n
   
   Meta Description:
   Discover how to automate the extraction of transactional data from PDFs and images using n8n, Google Gemini, Vertex AI, and OpenRouter. Learn how to transform files into categorized CSVs with zero manual entry.
   
   Keywords:
   n8n, PDF text extraction, OCR automation, Vertex AI, Google Gemini, OpenRouter, AI CSV generation, Google Drive, no-code automation, AI workflow, image to text, document processing, LLM integration, file automation, extract CSV from images, bank statement parsing
   
   Article:
   
   Effortlessly Extract Text from PDFs and Images into CSV Using n8n and AI Models
   
   In today’s data-driven world, automating repetitive tasks like extracting transaction data from PDFs or scanned images can save businesses countless hours. Whether you're parsing bank statements, invoices, or receipts, manual extraction is tedious and error-prone. Luckily, with n8n—a popular open-source workflow automation tool—and the power of large language models (LLMs), you can streamline this process without writing a single line of code.
   
   In this article, we'll walk you through an innovative n8n workflow that uses Google Gemini, Vertex AI, and OpenRouter to automatically extract text from PDF and image files, classify the information, and save it all in a categorized CSV file directly to Google Drive.
   
   Let’s break down how this powerful automation works.
   
   Workflow Overview
   
   This n8n workflow listens for new files (PDF or image) in a specified Google Drive folder. When a new file is detected, the system:
   
   1. Downloads the file (whether it’s a PDF or image).
   2. Determines the file type (PDF or image).
   3. For PDFs: Extracts textual content and sends it to OpenRouter’s LLM for intelligent categorization and formatting into CSV.
   4. For images: Sends it to Google’s Vertex AI via the Gemini model for OCR and CSV conversion.
   5. Converts the AI-generated output into an actual CSV file.
   6. Uploads the final CSV to a separate Google Drive folder for easy sharing and storage.
   
   It’s an end-to-end smart pipeline for turning unstructured data into structured insights.
   
   Let’s dive into the components that make this workflow tick.
   
   1. Google Drive Trigger
   The automation begins with a Google Drive Trigger node that monitors a specific folder for newly uploaded files. As soon as a file is added—be it a PDF or image—the system routes it to the appropriate next step. This trigger is configured using a service account credential to ensure continuous and secure access.
   
   2. File Type Detection and Routing
   Using a built-in 'Switch' node, the workflow checks the MIME type of the uploaded file. It directs PDFs to a PDF-specific extraction path and images down an OCR-based image-processing route.
   
   3. PDF Extraction and AI Categorization
   PDFs are downloaded using the Google Drive node and sent to the "Extract from File" module to convert the byte stream into readable text. This raw text is then submitted to OpenRouter’s LLM model—Meta LLaMA 3—via HTTP request. The prompt instructs the model to:
   - Extract all transactions
   - Format them as a properly labeled CSV
   - Classify each transaction into a category
   
   The LLM returns a CSV-formatted string which is then converted into a CSV file using the Convert to File node.
   
   4. Image Text Extraction via Vertex AI
   For image files (e.g., screenshots or scanned receipts), the workflow utilizes Google’s Vertex AI through the Gemini 1.5 Pro model. The image is passed to the “Vertex AI extract text” node, configured with defined prompts to extract transactions, categorize them, and format the output as CSV—just like for PDFs.
   
   5. Conversion and Storage
   After the AI models return their text in CSV format, n8n’s Convert to File nodes convert the data into actual .csv files. These are uploaded to a designated Google Drive folder (“CSV Exports”), making the final files easy to access and share across teams.
   
   No Repetitive Work. Just Real Results.
   This workflow eliminates the need to manually copy, paste, and enter data from PDFs or image-based bank statements. Instead, AI handles the heavy lifting—analyzing, classifying, and formatting data into clean CSV exports that are ready for analytics, accounting, or archiving.
   
   Setting It Up
   To configure this automation, you’ll need:
   - A Google Drive workspace (with folders set for uploads and exports)
   - A Google Service Account with Drive and Vertex AI permissions
   - An OpenRouter account and API key
   - Access to n8n (either self-hosted or via n8n.cloud)
   - The required credentials integrated into your n8n workflow
   
   Sticky notes embedded in the workflow offer setup instructions that help guide even non-technical users through this process—explaining everything from folder permissions to API key configuration.
   
   Use Cases
   - Automated bank statement processing
   - Invoice and receipt digitization
   - Company expense reports
   - Medical record extraction
   - OCR pipeline for handwritten forms
   
   Third-party APIs Used
   Here are the external services integrated into this solution:
   1. Google Drive API — For file monitoring, downloads, and uploads
   2. Google Vertex AI — For OCR and LLM processing of image input
   3. OpenRouter API — For LLM processing of PDF text using Meta’s LlaMA 3
   4. Google Gemini API — Used as the underlying model provider inside Vertex AI
   
   Conclusion
   
   If your workflow involves handling documents regularly, this AI-enhanced n8n automation can transform your operations. It is a testament to how intelligent automation and no-code tools can work together—replacing hours of manual labor and enabling smarter, faster business decisions.
   
   Start saving time, reducing errors, and focusing more on what matters—while your digital assistant handles PDFs and images like a pro.
   
   🔗 Pro Tip: You can explore the full setup step-by-step in this tutorial: https://rumjahn.com/how-to-create-an-a-i-agent-to-analyze-matomo-analytics-using-n8n-for-free/
   
   Ready to build your own AI-powered document workflow? With n8n and the right integrations, it’s easier than ever.
   
   — Written by your helpful AI assistant 💡

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.