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laujan · laujan · commit d222a5f0acee · 2021-10-24T13:24:29.000-07:00
diff --git a/articles/applied-ai-services/form-recognizer/concept-business-card.md b/articles/applied-ai-services/form-recognizer/concept-business-card.md
@@ -21,6 +21,20 @@ The business card model combines powerful Optical Character Recognition (OCR) ca
 
 :::image type="content" source="./media/studio/overview-business-card-studio.png" alt-text="sample business card" lightbox="./media/overview-business-card.jpg":::
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------|
+|**Business card model**|  <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/prebuilts-analyze)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-business-cards)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=business-card#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources | Model ID |
+|----------|-------------|-----------|
+|**Business card model**| <ul><li>[**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul>|**prebuilt-businessCard**|
+
 ### Try Form Recognizer
 
 See how data, including name, job title, address, email, and company name, is extracted from business cards using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/concept-custom.md b/articles/applied-ai-services/form-recognizer/concept-custom.md
@@ -30,6 +30,20 @@ A custom model is a machine learning program trained to recognize form fields wi
 
 With composed models, you can assign multiple custom models to a composed model called with a single model ID. It is useful when you have trained several models and want to group them to analyze similar form types. For example, your composed model may include custom models trained to analyze your supply, equipment, and furniture purchase orders. Instead of manually trying to select the appropriate model, you can use a composed model to determine the appropriate custom model for each analysis and extraction.
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------|
+|**Custom model**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-forms-with-a-custom-model)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=custom#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources |
+|----------|-------------|
+|**Custom model**| <ul><li>[**Form Recognizer Studio**](https://fott-2-1.azurewebsites.net)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul>| 
+
 ### Try Form Recognizer
 
 See how data is extracted from  your specific or unique documents using custom models. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/concept-general-document.md b/articles/applied-ai-services/form-recognizer/concept-general-document.md
@@ -19,10 +19,28 @@ The General document preview model combines powerful Optical Character Recogniti
 
 The general document API supports most form types and will analyze your documents and associate values to keys and entries to tables that it discovers. It is ideal for extracting common key-value pairs from documents. You can use the general document model as an alternative to [training a custom model without labels](compose-custom-models.md#train-without-labels).
 
+## General document features
+
+* There is no need to train a custom model to extract key-value pairs.
+
+* A single API is used to extract key value pairs, entities, text, tables, and structure from documents.
+
+* It is a pre-trained model that will be periodically trained on new data to improve coverage and accuracy.
+
+* The general document model supports structured, semi-structured, and unstructured data.
+
 ***Sample document processed in the Form Recognizer Studio***
 
 :::image type="content" source="media/studio/general-document-analyze.png" alt-text="Screenshot: general document analysis in the Form Recognizer Studio.":::
 
+## Development options
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources |
+|----------|-------------------------|
+|🆕 **General document model**|<ul ><li>[**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul> |
+
 ### Try Form Recognizer
 
 See how data, including tables, values, and entities, is extracted from forms and documents using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
@@ -49,16 +67,6 @@ See how data, including tables, values, and entities, is extracted from forms an
     > [!div class="nextstepaction"]
     > [Try Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=document)
 
-## General document features
-
-* There is no need to train a custom model to extract key-value pairs.
-
-* A single API is used to extract key value pairs, entities, text, tables, and structure from documents.
-
-* It is a pre-trained model that will be periodically trained on new data to improve coverage and accuracy.
-
-* The general document model supports structured, semi-structured, and unstructured data.
-
 ## Key-value pairs
 
 Key value pairs are specific spans within the document that identify a label or key and its associated response or value. In a structured form, this could be the label and the value the user entered for that field or in an unstructured  document it could be the date a contract was executed on based on the text in a paragraph.  The AI model is trained to extract identifiable keys and values based on a wide variety of document types, formats, and structures.
diff --git a/articles/applied-ai-services/form-recognizer/concept-id-document.md b/articles/applied-ai-services/form-recognizer/concept-id-document.md
@@ -21,6 +21,14 @@ The ID document model combines powerful Optical Character Recognition (OCR) capa
 
 :::image type="content" source="./media/studio/drivers-license.png" alt-text="sample identification card" lightbox="./media/overview-id.jpg":::
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------|
+|**ID document model**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/prebuilts-analyze)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-identity-id-documents)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=id-document#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
 ### Try Form Recognizer
 
 See how data, including name, birth date, machine-readable zone, and expiration date, is extracted from ID documents using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/concept-invoice.md b/articles/applied-ai-services/form-recognizer/concept-invoice.md
@@ -21,6 +21,20 @@ recommendations: false
 
 :::image type="content" source="media/studio/overview-invoices.png" alt-text="sample invoice" lightbox="media/overview-invoices-big.jpg":::
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------|
+|**Invoice model**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/prebuilts-analyze)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-invoices)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=invoice#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources | Model ID |
+|----------|-------------|-----------|
+|**Invoice model** | <ul><li>[**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul>|**prebuilt-invoice**|
+
 ### Try Form Recognizer
 
 See how data, including customer information, vendor details, and line items, is extracted from invoices using  the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/concept-layout.md b/articles/applied-ai-services/form-recognizer/concept-layout.md
@@ -26,6 +26,20 @@ Azure the Form Recognizer Layout API extracts text, tables, selection marks, and
 | --- | --- | --- | --- |
 | Layout  | ✓  | ✓  | ✓  |
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------| 
+|**Layout API**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/layout-analyze)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-layout)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?branch=main&tabs=layout#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources | Model ID |
+|----------|------------|------------|
+|**Layout model**| <ul><li>[**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul>|**prebuilt-layout**|
+
 ### Try Form Recognizer
 
 See how data, including tables, check boxes, and text, is extracted from forms and documents using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/concept-receipt.md b/articles/applied-ai-services/form-recognizer/concept-receipt.md
@@ -21,6 +21,20 @@ The receipt model combines powerful Optical Character Recognition (OCR) capabili
 
 :::image type="content" source="media/studio/overview-receipt.png" alt-text="sample receipt" lightbox="./media/overview-receipt.jpg":::
 
+## Development options
+
+The following resources are supported by Form Recognizer v2.1:
+
+| Feature | Resources |
+|----------|-------------------------|
+|**Receipt model**| <ul><li>[**Form Recognizer labeling tool**](https://fott-2-1.azurewebsites.net/prebuilts-analyze)</li><li>[**REST API**](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-receipts)</li><li>[**Client-library SDK**](quickstarts/try-sdk-rest-api.md)</li><li>[**Form Recognizer Docker container**](containers/form-recognizer-container-install-run.md?tabs=receipt#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+
+The following resources are supported by Form Recognizer v3.0:
+
+| Feature | Resources | Model ID |
+|----------|-------------|-----------|
+|**Receipt model**| <ul><li>[**Form Recognizer Studio**](https://formrecognizer.appliedai.azure.com)</li><li>[**REST API**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-1/operations/AnalyzeDocument)</li><li>[**C# SDK**](quickstarts/try-v3-csharp-sdk.md)</li><li>[**Python SDK**](quickstarts/try-v3-python-sdk.md)</li></ul>|**prebuilt-receipt**|
+
 ### Try Form Recognizer
 
 See how data, including time and date of transactions, merchant information, and amount totals, is extracted from receipts using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following:
diff --git a/articles/applied-ai-services/form-recognizer/overview.md b/articles/applied-ai-services/form-recognizer/overview.md
