Automate Pitch Deck Analysis with AI Vision & Data Extraction
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This workflow automates the intricate process of analyzing pitch decks and other visually rich PDF documents. It leverages AI vision to convert PDF pages into descriptive markdown, enabling efficient extraction of key data points for storage and further analysis in tools like Airtable.
About This Workflow
This n8n workflow provides a powerful solution for transforming complex, visual PDF documents like pitch decks into structured, actionable data. Beginning with a manual trigger, it ingeniously converts each PDF page into high-resolution JPG images using the Stirling PDF service (with a privacy-conscious note on self-hosting). These images are then resized and fed into a multimodal AI Vision LLM, which transcribes their content into detailed markdown, including descriptions of visual elements, charts, and graphs. Finally, an Information Extractor confidently pulls key data points from the markdown, updating your Airtable database to facilitate reporting, comparisons, and strategic decision-making.
Key Features
- Multimodal AI Vision Integration: Leverages cutting-edge AI to "read" and describe content from visual PDF pages, including charts and images.
- Automated PDF to Image Conversion: Seamlessly converts multi-page PDFs into individual image files (JPG at 300 DPI) for AI processing.
- Intelligent Data Extraction: Confidently extracts structured data points from the AI-generated markdown content using an Information Extractor.
- Database Integration (Airtable): Automatically updates your Airtable records with extracted insights, centralizing critical business information.
- Customizable & Privacy-Aware: Offers flexibility to swap PDF conversion services and notes self-hosting options for sensitive data.
How To Use
- Initiate Workflow: Manually trigger the workflow using the 'When clicking ‘Test workflow’' node to begin processing.
- Provide PDF Input: Ensure your PDF document is correctly passed into the 'Split PDF into Images' HTTP Request node, typically as binary data from a preceding node (not fully shown but implied by the setup).
- Review Stirling PDF Service: Note the privacy warning on 'Sticky Note5'. For sensitive data, consider self-hosting Stirling PDF or using an alternative PDF-to-image converter.
- Configure LLM & Information Extractor: Customize the 'Basic LLM Chain' and 'Information Extractor' nodes (refer to 'Sticky Note3' and 'Sticky Note4' for guidance) to specify what information should be transcribed and extracted from your specific documents.
- Set Up Airtable Integration: Configure the 'Update Row' Airtable node with your API key, Base ID, and Table Name (
Pitch Decksis suggested by the snippet) to ensure extracted data is correctly stored. - Execute and Monitor: Run the workflow and monitor the output in Airtable to see your automatically extracted and structured data.
Apps Used
Workflow JSON
{
"id": "1cf8f259-1462-485f-bcd0-c9eaaf0da2a4",
"name": "Automate Pitch Deck Analysis with AI Vision & Data Extraction",
"nodes": 13,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 1cf8f259-1462...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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