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articles/ai-services/content-understanding/concepts/analyzer-templates.md

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There are analyzer templates specific to common scenarios in each modality, such as call center audio analytics and advertising analysis for videos. Templates are also fully customizable, allowing you to adjust any
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fields in the schemas to better fit your needs. Learn more about the analyzer templates offered for each modality by viewing the tabs below.
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The following analyzer templates are available for use in the [Azure AI Foundry Content Understanding experience](https://ai.azure.com/). Check out [Use Content Understanding in the Azure AI Foundry](../ai-services/content-understanding/quickstart/use-ai-foundry.md) for a step-by-step
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The following analyzer templates are available for use in the [Azure AI Foundry Content Understanding experience](https://ai.azure.com/). Check out [Use Content Understanding in the Azure AI Foundry](../quickstart/use-ai-foundry.md) for a step-by-step
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on how to create your first analyzer using the below templates.
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|Document analysis |Analyze documents to extract text, layout, structured fields, and more.|
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|Text analysis |Analyze texts and extract structured fields.|
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:::image type="content" source="../media/analyzer-template/image-templates.png" alt-text="Screenshot of document analyzer template.":::
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:::image type="content" source="../media/analyzer-template/scenario-template-document.png" alt-text="Screenshot of document analyzer template.":::
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# [Image](#tab/image)
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articles/ai-services/content-understanding/quickstart/use-ai-foundry.md

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## Build your first analyzer
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Now that everything is configured to get started, the following is a setep-by-step walkthrough of how to build your first analyzer, starting with building the schema. The schema is the customziable framework that allows the analyzer to extract insights from your data. In this example, the schema is created to extract key data from an invoice document, but you can bring in any type of data and the steps to follow will remain the same. For a complete list of supported file types, see [input file limits](../service-limits.md#input-file-limits).
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Now that everything is configured to get started, the following is a step-by-step walkthrough of how to build your first analyzer, starting with building the schema. The schema is the customziable framework that allows the analyzer to extract insights from your data. In this example, the schema is created to extract key data from an invoice document, but you can bring in any type of data and the steps to follow will remain the same. For a complete list of supported file types, see [input file limits](../service-limits.md#input-file-limits).
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1. Upload a sample file of an invoice document or any other data relevant to your scenario.
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