Build a PDF Document RAG System with Mistral OCR, Qdrant and Gemini AI

About This Workflow

What This Workflow Does

This workflow automates the process of extracting text from PDF documents using Mistral's Optical Character Recognition (OCR) capabilities, storing the extracted text in a Qdrant vector database, and utilizing Gemini AI for further analysis. The result is a comprehensive RAG (Red, Amber, Green) system for PDF documents, enabling efficient categorization and decision-making. This workflow streamlines document processing and analysis, saving time and effort.

Who Should Use This

This workflow is suitable for developers, data analysts, and business owners who need to process large volumes of PDF documents, extract valuable insights, and categorize them based on specific criteria. It's particularly useful for organizations in industries such as finance, healthcare, and government, where document analysis is critical.

Key Features

• PDF Text Extraction: Utilizes Mistral's OCR capabilities to extract text from PDF documents, ensuring accurate and reliable results.
• Qdrant Vector Database: Stores the extracted text in a Qdrant vector database, enabling efficient querying and analysis.
• Gemini AI Integration: Leverages Gemini AI for further analysis and categorization of the extracted text, providing a comprehensive RAG system.
• Scalable and Customizable: Designed to handle large volumes of documents and can be customized to meet specific business needs.

How to Get Started

To use this workflow, simply import it into your n8n environment and customize it according to your specific requirements. You can adjust the workflow's parameters, such as the OCR settings and Qdrant database configuration, to fit your organization's needs.