Building a content analyzer in Azure AI Foundry
Here you start with a sample of the content you want to analyze. Upload your sample to Azure AI Foundry, and the service will suggest templates from its own library based on your document. Choose the most appropriate and edit it to add your own fields and types. It’s a good idea to add descriptions to your edited schema to help with debugging and to support other developers. Once you’ve saved your customized schema, you can test the analyzer against a selection of sample documents. Once saved, the Azure AI Foundry tool builds your analyzer, ready for use. This will generate endpoint URLs to add to your code.
The sample templates are split across the four content categories: text, image, audio, and video. Some, like retail inventory management or media asset management, are industry-specific, and Microsoft will likely add more as different use cases emerge. If you’ve used any of the Azure Cognitive Services in the past, you should find this a lot easier to use, with support for more complex documents and other content.
Each analyzer is a pipeline in its own right, processing inputs, extracting content, and then providing insights as well as application-ready information. There’s more to the process than basic recognition, and the document analyzer add-on tools offer more features, including the ability to recognize and process barcodes and mathematical formulas in documents. The service will process handwritten content as well as type.
