Added tip for AI Studio options

Author: jboback

articles/ai-services/language-service/personally-identifiable-information/overview.md

@@ -19,6 +19,9 @@ Customers can now redact transcripts, chats, and other text written in a convers
 
 PII detection is one of the features offered by [Azure AI Language](../overview.md), a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The PII detection feature can **identify, categorize, and redact** sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Azure AI Language supports general text PII redaction, as well as [Conversational PII](how-to-call-for-conversations.md), a specialized model for handling speech transcriptions and the more informal, conversational tone of meeting and call transcripts. The service also supports [Native Document PII redaction](#native-document-support), where the input and output are structured document files.
 
+> [!TIP]
+> PII detection is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service. 
+
 * [**Quickstarts**](quickstart.md) are getting-started instructions to guide you through making requests to the service.
 * [**How-to guides**](how-to-call.md) contain instructions for using the service in more specific or customized ways.
 * The [**conceptual articles**](concepts/entity-categories.md) provide in-depth explanations of the service's functionality and features.

articles/ai-services/language-service/summarization/overview.md

@@ -21,6 +21,9 @@ Use this article to learn more about this feature, and how to use it in your app
 
 Out of the box, the service provides summarization solutions for three types of genre, plain texts, conversations, and native documents. Text summarization only accepts plain text blocks, and conversation summarization accept conversational input, including various speech audio signals in order for the model to effectively segment and summarize, and native document can directly summarize for documents in their native formats, such as Words, PDF, etc. 
 
+> [!TIP]
+> Summarization is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service. 
+
 # [Text summarization](#tab/text-summarization)
 
 This documentation contains the following article types:

articles/ai-services/language-service/text-analytics-for-health/overview.md

@@ -18,6 +18,9 @@ ms.custom: language-service-health
 
 Text Analytics for health is one of the prebuilt features offered by [Azure AI Language](../overview.md). It is a cloud-based API service that applies machine-learning intelligence to extract and label relevant medical information from a variety of unstructured texts such as doctor's notes, discharge summaries, clinical documents, and electronic health records. 
 
+> [!TIP]
+> Text Analytics for health is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service. 
+
 This documentation contains the following types of articles:
 * The [**quickstart article**](quickstart.md) provides a short tutorial that guides you with making your first request to the service.
 * The [**how-to guides**](how-to/call-api.md) contain detailed instructions on how to make calls to the service using the hosted API or using the on-premises Docker container.