Merge pull request #28618 from MicrosoftDocs/chucked-working

Chucked working - custom and prebuilt model reference updates

Author: chuckedmonson

microsoft-365/syntex/document-understanding-overview.md

@@ -39,12 +39,12 @@ Use the unstructured document processing model ([teaching method](create-syntex-
 
 ## Introduction to unstructured models
 
-The unstructured document processing model uses artificial intelligence (AI) to process documents. These documents must have text that can be identified based on phrases or patterns. The identified text designates both the type of file it is (its classification) and what you'd like to extract (its extractors).
+Unstructured document processing models use artificial intelligence (AI) to analyze and extract information from documents. These models rely on identifiable text—based on phrases or patterns—to determine both the document’s classification and the data to extract.
 
 > [!NOTE]
 > For more information about how to use Syntex and scenario examples, see [Get started driving adoption of Microsoft Syntex](./adoption-getstarted.md) and [Scenarios and use cases for Microsoft Syntex](./adoption-scenarios.md).
 
-Unstructured document processing models are created and managed in a type of SharePoint site called a [content center](create-a-content-center.md). When applied to a SharePoint document library, the model is associated with a content type has columns to store the information being extracted. The content type you create is stored in the SharePoint content type gallery. You can also choose to use existing content types to use their schema.
+You create and manage unstructured document processing models in a SharePoint content center. When you apply a model to a SharePoint document library, it’s associated with a content type that includes columns for storing extracted information. You can create a new content type or use an existing one from the SharePoint content type gallery.
 
 > [!NOTE]
 > Read-only or sealed content types can't be updated, so they can't be used in a model.
@@ -55,7 +55,7 @@ Add [classifiers](create-a-classifier.md) and [extractors](create-an-extractor.m
 
 - Extractors pull information from these documents. For example, for each contract renewal document identified in your document library, columns display that show the *Service Start Date* and *Client* for each document.
 
-You can use example files to train and test your classifiers and extractors in your model. Example files provide your model examples of what to look for when trying to identify and extract data from files. For example, you would train your contract renewal classifiers and extractors with examples of contract renewal documents your company works with. You can also use example files to test the effectiveness of your model.
+Use example files to train and test your classifiers and extractors. These files help the model learn what to look for when identifying and extracting data. For example, train your contract renewal model using real contract renewal documents from your organization. You can also use these files to validate your model’s accuracy.
 
 After publishing your model, use the content center to apply it to any SharePoint document library that you have access to.  
 

microsoft-365/syntex/form-processing-overview.md

@@ -4,7 +4,7 @@ ms.author: chucked
 author: chuckedmonson
 manager: jtremper
 ms.reviewer: ssquires
-ms.date: 01/22/2025
+ms.date: 03/22/2025
 audience: admin
 ms.topic: concept-article
 ms.custom: intro-overview
@@ -38,28 +38,26 @@ Use the freeform document processing model ([freeform selection method](create-s
 
 ## Introduction to structured and freeform models
 
-Microsoft Syntex uses Microsoft Power Apps [AI Builder](/ai-builder/form-processing-model-overview) document processing to create structured and freeform document processing models within SharePoint document libraries.
-<!---
- ![AI Builder.](../media/content-understanding/ai-builder.png)
---->
-You can use AI Builder document processing to create structured or freeform document processing models that use machine learning technology to identify and extract key-value pairs and table data from structured or semi-structured documents, such as forms and invoices, and unstructured or freeform documents, such as contracts and correspondence.
+Microsoft Syntex uses Microsoft Power Apps [AI Builder](/ai-builder/form-processing-model-overview) to enable both structured and freeform document processing directly within SharePoint document libraries.
 
-Organizations often receive invoices in large quantities from various sources, such as mail, fax, and email. Processing these documents and manually entering them into a database can take a considerable amount of time. By using AI to extract the text, key-value pairs, and tables from your documents, Syntex automates this process.
+With AI Builder, you can create models that use machine learning to identify and extract key-value pairs and table data from various document types—including structured or semi-structured formats like forms and invoices, as well as unstructured formats like contracts and correspondence.
+
+For example, organizations often receive large volumes of invoices through mail, fax, or email. Manually processing and entering this data can be time-consuming. Syntex streamlines this process by using AI to extract text, key-value pairs, and tables—automating data capture and reducing manual effort.
 
 > [!NOTE]
 > For more ideas about how to use these models in your organization, see [Get started driving adoption](adoption-getstarted.md) and [Scenarios and use cases](adoption-scenarios.md).
 
-For example, you can create a structured or freeform document processing model that identifies all documents that are uploaded to the document library. From each document, you can then extract and display specific data that is important to you.
+You can create structured or freeform document processing models that automatically identify and extract important information from files uploaded to a SharePoint document library.
 
 ![Screenshot showing the document library view.](../media/content-understanding/doc-lib-done.png)  
 
-You use example files to train your model and define the information to be extracted from your form. The layout of your document is learned by training your model. You only need five form documents to get started. Syntex analyzes your example files for key-value pairs, and you can also manually identify ones that might not have been detected.  AI builder lets you test the accuracy of your model on your example files.
+To get started, you use example files to train your model. Microsoft Syntex uses these examples to learn the layout of your documents and identify key-value pairs and tables. You only need five sample documents to begin. During training, you can review and manually tag any fields that weren’t automatically detected. AI Builder also lets you test your model’s accuracy using your example files.
 
-You can only create a structured or freeform document processing model in SharePoint document libraries for which it's enabled. If it's been enabled, you're able to see the **Classify and extract** option in your document library.
+You can only create document processing models in SharePoint libraries where Syntex has been enabled. If it’s available, you see the **Classify and extract** option in the library’s command bar.
 
 ![Screenshot showing the AI Builder model.](../media/content-understanding/create-ai-builder-model2.png)
 
-If you need it enabled on your document library, contact your Microsoft 365 admin.
+If you don’t see this option, contact your Microsoft 365 admin to enable Microsoft Syntex for your library.
 
 ## Requirements and limitations
 

microsoft-365/syntex/prebuilt-overview.md

@@ -4,7 +4,7 @@ ms.author: chucked
 author: chuckedmonson
 manager: jtremper
 ms.reviewer: ssquires
-ms.date: 01/22/2025
+ms.date: 03/22/2025
 audience: admin
 ms.topic: concept-article
 ms.custom: intro-overview
@@ -23,20 +23,20 @@ description: Learn about prebuilt document processing in SharePoint.
 > [!NOTE]
 > Through June 2025, you can try out a [limited amount](promo-syntex.md#monthly-included-capacity) of prebuilt document processing and other selected content services at no cost if you have [pay-as-you-go billing](syntex-azure-billing.md) set up. For information and limitations, see [Try out pay-as-you-go services](promo-syntex.md).
 
-In addition to [custom models](model-types-overview.md#custom-models), Microsoft Syntex provides *prebuilt models* to automate the extraction of information.
+In addition to using [custom models](model-types-overview.md#custom-models), Microsoft Syntex offers prebuilt models that help automate information extraction from documents—no training required. These models are ready to use and designed to recognize common document types and data patterns, so you can get started quickly and scale efficiently.
 
 > [!NOTE]
 > Microsoft respects the privacy and ownership of data you use to train and process models in Syntex. None of your organization's data is used or transferred by Microsoft to train AI models, large-language models, or any other models. Your data remains securely within your organization’s tenant. For more information, see [Microsoft data protection and privacy](https://www.microsoft.com/en-us/trust-center/privacy).
 
 ## Introduction to prebuilt models
 
-Prebuilt document processing uses [prebuilt models](#available-prebuilt-models) that are preconfigured to recognize documents and the structured information in the documents. Instead of having to create a new custom model from scratch, you can iterate on an existing pretrained model to add specific fields that fit the needs of your organization.
+Prebuilt document processing uses pretrained models that are already configured to recognize common document types and extract structured information. Instead of building a custom model from scratch, you can start with a prebuilt model and tailor it by adding fields specific to your organization’s needs.
 
-Prebuilt models use optical character recognition (OCR) combined with deep learning models to identify and extract predefined text and data fields common to specific document types. You start by analyzing one of your files against the prebuilt model. You then select the detected fields that make sense for your purpose. If the model doesn't detect the fields that you need, you can analyze again by using a different file.
+These models combine optical character recognition (OCR) with deep learning to identify and extract predefined text and data fields. To get started, analyze a sample file using a prebuilt model. Then, select the fields that are relevant to your scenario. If the model doesn’t detect the fields you need, try analyzing a different file.
 
-Like other models, prebuilt models are created and managed in the [content center](create-a-content-center.md). When applied to a SharePoint document library, the model is associated with a content type and has columns to store the information being extracted.
+Like other models, prebuilt models are created and managed in the [content center](create-a-content-center.md). When you apply a model to a SharePoint document library, it links to a content type and includes columns to store the extracted information.
 
-After publishing your model, use the content center to apply it to any SharePoint document library that you have access to.  
+After publishing your model, use the content center to apply it to any SharePoint document library you have access to. 
 
 ## Available prebuilt models