Hosted by Microsoft Developer, this episode features April demonstrating how to use Mistral Document AI in Azure AI Foundry for parsing and structuring complex document data.

Mistral Document AI Integration with Azure AI Foundry

Presented by Microsoft Developer

Overview

In this episode, April demonstrates the capabilities of the Mistral Document AI model within Azure AI Foundry. The focus is on translating unstructured documents—such as PDFs with complex layouts and handwritten notes—into actionable, structured JSON data.

Key Topics Covered

• Deploying the Mistral Document AI model within Azure AI Foundry
• Accessing and running sample code to process documents
• Parsing PDFs and images using base64 samples
• Generating structured JSON outputs for integration with various data systems
• Connecting outputs to databases, AI agents, and Retrieval-Augmented Generation (RAG) workflows to enable broader use cases

Main Steps

1. Deploy the Model:
   Start by deploying Mistral Document AI in your Azure AI Foundry workspace.
2. Access Sample Code:
   Download example code to interact with the model (get the code here).
3. Process Documents:
   • Run the model using a base64-encoded PDF to obtain structured outputs.
   • Repeat the process for images, including handwritten notes.
4. Review Outputs:
   Inspect the JSON output, which organizes extracted data for downstream integration.
5. Integrate:
   Feed the structured data into your preferred databases, AI workflows, or RAG pipelines.

Try It Yourself

• Explore Azure AI Foundry: ai.azure.com
• Learn more about Mistral Document AI: Documentation
• Join the community:
  • Discord: insideAIF/discord
  • Forum: insideAIF/forum

For code examples and deployment guidance, see this link.