resolve build issues

Author: laujan

articles/ai-services/content-understanding/concepts/analyzers-overview.md

@@ -27,7 +27,9 @@ Analyzers are the core processing units in Content Understanding that define how
 * Content extraction configurations - determining what foundational elements to extract.
 * Field extraction schemas - specifying how to get the fields(extract/generate/classify) from the content.
 
-Key benefits of analyzers include:
+:::image type="content" source="../media/concepts/analyzer-architecture.png" alt-text="Screenshot of analyzer architecture.":::
+
+Key features of analyzers include the following benefits:
 
 * **Consistency**: Analyzers ensure uniform processing across all content by applying the same extraction rules and schemas, delivering reliable and predictable results.
 

articles/ai-services/content-understanding/concepts/prebuilt-analyzers

@@ -0,0 +1,106 @@
+---
+title: Azure AI Content Understanding Prebuilt analyzers
+titleSuffix: Azure AI services
+description: Learn about prebuilt analyzers, their scenarios, customization options, billing, roadmap in Azure AI Content Understanding.
+author: laujan
+ms.author: additi
+manager: nitinme
+ms.service: azure-ai-content-understanding
+ms.topic: overview
+ms.date: 05/19/2025
+---
+
+# Prebuilt analyzers in Azure AI Content Understanding
+
+## Overview
+
+Azure AI Content Understanding employs analyzers to derive structured insights from unstructured content, spanning documents, images, audio, and video files. Its prebuilt analyzers are ready-to-use solutions tailored for common content processing tasks, including document ingestion, search indexing, and retrieval-augmented generation (`RAG`).
+
+These analyzers streamline trial experiences and can be adapted by extending their functionality to meet specific workflow requirements. Key offerings include:
+
+* **[Content parsers](#content-parsers-for-search-and-ingestion)** for general search and ingestion scenarios.
+* **[Scenario-specific predefined analyzers](#scenario-specific-predefined-analyzers)** for targeted use cases like invoices or call center transcripts.
+* **[Inheritance from prebuilt analyzers](#inheriting-and-customizing-prebuilt-analyzers)** to customize configuration and fields.
+
+## Content parsers for search and ingestion
+
+To streamline common content ingestion scenarios, Azure AI Content Understanding offers general purpose **prebuilt content analyzers**. These analyzers extract text, layout, and metadata from various content types.
+
+
+| Analyzer                  | Description                                                                 | Supported File Types |
+|:-------------------------|:-----------------------------------------------------------------------------|:--------------------|
+| `prebuilt-documentAnalyzer` | Extracts text, layout, and metadata using `OCR` for images and rendered files. Users can customize prebuilt content analyzers to modify configuration and add/remove fields. | `.pdf`, `.tiff`, `image`, `.docx`, `.rtf`, `.html`, `.md`, `.json`, `.xml`, `.csv`, `.tsv`, and `.txt` |
+| `prebuilt-imageAnalyzer`    | Generates a descriptive caption of an image and `OCR` is conceptually disabled. Users refine the description and/or add new fields by creating analyzer with baseAnalyzerId=prebuilt-imageAnalyzer.  | image                |
+| `prebuilt-audioAnalyzer`    | Produces a transcript, speaker diarization, and a summary for audio files. Users can add new fields by creating analyzer with baseAnalyzerId=prebuilt-audioAnalyzer.  | audio                |
+| `prebuilt-videoAnalyzer`    | Extracts keyframes, transcript, and video segmentation. Segmentation is enabled by default. Users can disable/customize segmentation by creating an analyzer with baseAnalyzerId=prebuilt-videoAnalyzer and changing segmentationMode property.                | video                |
+
+Analyzers are optimized for `RAG` ingestion and search workflows, offering default behaviors suitable for indexing and summarizing large volumes of content.
+
+> [!NOTE]
+>
+> * Currently, `OCR` is supported for `.pdf` and `.tiff` image files. Content elements from such files include span properties and bounding boxes via their source properties.
+> * For unsupported files, contents are extracted digitally. Content elements from these files include span properties to indicate their position in the returned markdown.
+> * There are no prebuilt models for `agentic` mode. Instead, users can create an analyzer with mode=pro starting from any document base analyzer to test out `agentic` behavior.
+
+## Scenario-specific predefined analyzers
+
+In addition to general content analyzers, Azure AI Content Understanding provides **prebuilt analyzers for specific business scenarios**  to target common scenarios. They can be further customized by setting them as the `baseAnalyzerId`:
+
+| Analyzer             | Description                                                     | Supported File Types |
+|:--------------------|:----------------------------------------------------------------|:--------------------|
+| `prebuilt-callCenter` | Extracts summary, sentiment, topics, and insights from call center transcripts. | audio |
+| `prebuilt-invoice`    | Extracts structured fields such as InvoiceId, Date, and Vendor from invoices. | `.pdf`, `.tiff`, and `image` files.|
+
+These analyzers bundle best practices and hidden configurations to deliver accurate extractions for their intended use cases while simplifying deployment by abstracting internal implementation details.
+
+
+## Inheritance and customizing prebuilt analyzers
+
+With the **`2025-05-01-preview`**, any prebuilt analyzer can be inherited using `baseAnalyzerId` to create a custom analyzer. Inheritance allows for modification of existing fields, descriptions, types, and methods. Additionally, configuration settings such as `enableFormula`, `segmentationMode`, and others can be customized.
+
+***Example***
+
+
+### Inherit from `prebuilt-documentAnalyzer`
+
+```json
+{
+  "baseAnalyzerId": "prebuilt-documentAnalyzer",
+  "fields": [
+    { "name": "InvoiceId", "type": "string", "method": "regex" },
+    { "name": "TotalAmount", "type": "currency", "method": "extractive" }
+  ],
+  "configuration": {
+    "enableFormula": true,
+    "tableFormat": "markdown"
+  }
+}
+```
+
+> [!IMPORTANT]
+> With the `2025-05-01-preview`, modifying a field description overwrites the internal refined description, potentially reducing extraction quality.
+> The `baseAnalyzerId` must be a prebuilt analyzer. Custom analyzers can't currently inherit from other custom analyzers.
+
+## Analyzer details and configurations
+
+* **Document Analyzer**: Uses `OCR` for `.pdf`,`.tiff`, and `image` files.
+* **Image Analyzer**: Doesn't use `OCR`but generates image descriptions.
+* **Audio Analyzer**: Returns transcript and summary extraction.
+* **Video Analyzer**: Returns keyframes, transcript, and segmentation.
+* **Call Center Analyzer**: Summarizes and extracts insights from audio. Supports audio text.
+* **Invoice Analyzer**: Returns structured field extraction from invoices. Supports `.pdf`, `.tiff`, and `image` files.
+
+
+## Billing and limits
+
+* **Documents**: Billing is calculated per page, slide, or sheet. For`.docx`, `.rtf`, `.html`, `.md`, `.msg`, `.eml`, `.json`, `.xml`, `.csv`, `.tsv`, and `.txt`, we count every 3k `UTF16 `characters as a page. Field extraction has a `fixed-per-1k` page rate
+* **Images**: There's no cost for image content extraction, however, generating a description invokes image field extraction charges.
+* **Audio/Video**: Billing is calculated on a per hour basis with 1-minute granularity. Charges are calculated for both audio/video content extraction and field extraction.
+* Maximum field limit: Currently there are 90 user-defined fields with 100 total to include reserved fields.
+
+## Next steps
+
+* [Analyzer templates](analyzer-templates.md)
+* [Analyzers overview](analyzers-overview.md)
+
+

articles/ai-services/content-understanding/concepts/prebuilt-analyzers.md

@@ -7,7 +7,7 @@ manager: nitinme
 ms.service: azure-ai-content-understanding
 ms.topic: how-to
 ms.date: 05/19/2025
-ms.custom: ignite-2024-understanding-release, references_regions
+ms.custom: references_regions
 ms.author: lajanuar
 ---