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Mistral OCR, GPT-4o-mini, and Google Sheets integration for enhanced data processing

Antonio GassoAntonio Gasso
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2/3/2026
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Process multiple invoices automatically using Mistral's dedicated OCR model—at approximately $0.002 per page. Upload batches of PDF, PNG, or JPG invoices through a simple form, extract structured financial data with AI, validate results with confidence scoring, and save everything to Google Sheets.

What this workflow does

  1. Accepts multiple invoice uploads via n8n Form Trigger
  2. Processes files in batch with rate limiting
  3. Converts each file to base64 and sends to Mistral OCR API
  4. Extracts 9 standard fields using GPT-4o-mini Information Extractor
  5. Validates data and assigns confidence scores (high/medium/low)
  6. Saves all results to Google Sheets with status tracking

Fields extracted

Invoice Number, Date, Vendor Name, Tax ID, Subtotal, Tax Rate, Tax Amount, Total Amount, Currency

Use cases

  • Accountants processing client invoices in bulk
  • Small businesses digitizing paper receipts
  • Bookkeepers automating repetitive data entry
  • Finance teams building searchable invoice databases

Setup requirements

  • Mistral API Key (console.mistral.ai) — HTTP Header Auth credential
  • OpenAI API Key (platform.openai.com)
  • Google Sheets OAuth connection
  • Google Sheet with 15 columns (template in workflow notes)

n8n Workflow: Mistral OCR, GPT-4o Mini, and Google Sheets Integration for Enhanced Data Processing

This n8n workflow automates the process of extracting structured information from text using a Large Language Model (LLM) and then storing that information in a Google Sheet. It's designed to streamline data entry and analysis by leveraging AI for intelligent data extraction.

What it does

This workflow simplifies and automates the following steps:

  1. Triggers on Form Submission: The workflow starts when an n8n form is submitted, likely containing text data to be processed.
  2. Extracts Information with AI: It uses an "Information Extractor" node (likely powered by an LLM like Mistral or GPT-4o Mini, based on the directory name) to parse the submitted text and extract structured data based on a defined schema.
  3. Processes with OpenAI Chat Model: The extracted information is then further processed or refined using an OpenAI Chat Model (e.g., GPT-4o Mini), allowing for more nuanced understanding or transformation of the data.
  4. Loops for Batch Processing: The workflow includes a "Loop Over Items" node, indicating it can handle multiple items or batches of data, ensuring efficient processing.
  5. Adds Extracted Data to Google Sheets: Finally, the structured and processed data is appended as new rows to a specified Google Sheet, providing a centralized and organized repository for the extracted information.
  6. Includes Delay for Rate Limiting: A "Wait" node is integrated, likely to manage API rate limits or introduce pauses between processing batches.
  7. Custom Logic with Code: A "Code" node allows for custom JavaScript logic to be executed at a specific point in the workflow, offering flexibility for data manipulation or conditional processing.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • Google Sheets Account: Access to a Google Sheets spreadsheet where the extracted data will be stored.
  • OpenAI API Key: An API key for OpenAI to use the Chat Model.
  • Langchain Credentials: Appropriate credentials for the Langchain nodes (Information Extractor, OpenAI Chat Model) within n8n.
  • n8n Form: A configured n8n Form Trigger to initiate the workflow.

Setup/Usage

  1. Import the Workflow: Download the JSON provided and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your Google Sheets credentials.
    • Configure your OpenAI API key within the "OpenAI Chat Model" node.
    • Ensure all Langchain-related credentials are correctly set up.
  3. Configure Google Sheets Node: Specify the Spreadsheet ID and Sheet Name where you want the data to be added.
  4. Configure Form Trigger: Customize the n8n form fields to match the input you expect for your data extraction.
  5. Configure Information Extractor: Define the schema or instructions for the "Information Extractor" node to guide the AI on what data to extract from the input text.
  6. Customize Code Node (Optional): If needed, modify the JavaScript code in the "Code" node to perform any specific data transformations or logic.
  7. Activate the Workflow: Once configured, activate the workflow. It will now run automatically upon form submissions.

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