name changes

Author: ssalgadodev

articles/ai-foundry/concepts/content-filtering.md

@@ -26,7 +26,7 @@ author: PatrickFarley
 
 The content filtering system is powered by [Azure AI Content Safety](../../ai-services/content-safety/overview.md), and it works by running both the prompt input and completion output through a set of classification models designed to detect and prevent the output of harmful content. Variations in API configurations and application design might affect completions and thus filtering behavior.
 
-With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later on). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Azure Direct Models](model-catalog-content-safety.md).
+With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later on). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Models Sold Directly by Azure ](model-catalog-content-safety.md).
 
 ## Language support
 

articles/ai-foundry/concepts/foundry-models-overview.md

@@ -30,30 +30,30 @@ Azure AI Foundry offers a comprehensive catalog of AI models. There are over 190
 
 Our catalog is organized into two main categories: 
 
-* [Azure Direct Models](#azure-direct-models)
-* [Azure Ecosystem Models](#azure-ecosystem-models)
+* [Models sold directly by Azure](#models-sold-directly-by-azure)
+* [Models from Partners and Community](#models-from-partners-and-community)
 
 Understanding the distinction between these categories helps you choose the right models based on your specific requirements and strategic goals. 
 
-## Azure Direct Models  
+## Models Sold Directly by Azure 
 
-Azure Direct Models are models that are hosted and sold by Microsoft under Microsoft Product Terms. These models have undergone rigorous evaluation and are deeply integrated into Azure's AI ecosystem. They offer enhanced integration, optimized performance, and direct Microsoft support, including enterprise-grade Service Level Agreements (SLAs). 
+These are models that are hosted and sold by Microsoft under Microsoft Product Terms. These models have undergone rigorous evaluation and are deeply integrated into Azure’s AI ecosystem. The models come from a variety of top providers and they offer enhanced integration, optimized performance, and direct Microsoft support, including enterprise-grade Service Level Agreements (SLAs).
 
-Characteristics of Azure Direct Models: 
+Characteristics of models sold directly by Azure: 
 
 - Official first-party support from Microsoft 
 - High level of integration with Azure services and infrastructure 
 - Extensive performance benchmarking and validation 
 - Adherence to Microsoft's Responsible AI standards 
 - Enterprise-grade scalability, reliability, and security
 
-Azure Direct Models also have the benefit of flexible Provisioned Throughput, meaning you can use your quota and reservations across any of these models.
+These Models also have the benefit of fungible Provisioned Throughput, meaning you can flexibly use your quota and reservations across any of these models.
 
-## Azure Ecosystem Models
+## Models from Partners and Community
 
-Models constitute the vast majority of the Azure AI Foundry Models. These models are provided by trusted third-party organizations, partners, research labs, and community contributors. These models offer specialized and diverse AI capabilities, covering a wide array of scenarios, industries, and innovations.
+ These models constitute the vast majority of the Azure AI Foundry Models. These models are provided by trusted third-party organizations, partners, research labs, and community contributors. These models offer specialized and diverse AI capabilities, covering a wide array of scenarios, industries, and innovations.
 
-Characteristics of Azure Ecosystem Models: 
+Characteristics of Models from Partners and Community: 
 * Developed and supported by external partners and community contributors 
 * Diverse range of specialized models catering to niche or broad use cases 
 * Typically validated by providers themselves, with integration guidelines provided by Azure 
@@ -62,28 +62,18 @@ Characteristics of Azure Ecosystem Models:
 
 Models are deployable as Managed Compute or Standard (pay-go) deployment options. The model provider selects how the models are deployable.   
 
-## Choosing between Azure Direct and Azure Ecosystem Models 
+## Choosing Between direct models and partner & community models 
 
 
 When selecting models from Azure AI Foundry Models, consider the following: 
-* **Use Case and Requirements**: Azure Direct Models are ideal for scenarios requiring deep Azure integration, guaranteed support, and enterprise SLAs. Azure Ecosystem Models excel in specialized use cases and innovation-led scenarios. 
-* **Support Expectations**: Azure Direct Models come with robust Microsoft-provided support and maintenance. Azure Ecosystem Models are supported by their providers, with varying levels of SLA and support structures. 
-* **Innovation and Specialization**: Azure Ecosystem Models offer rapid access to specialized innovations and niche capabilities often developed by leading research labs and emerging AI providers.
+* **Use Case and Requirements**: Models sold directly by Azure are ideal for scenarios requiring deep Azure integration, guaranteed support, and enterprise SLAs. Models from Partners and Community excel in specialized use cases and innovation-led scenarios. 
+* **Support Expectations**: Models sold directly by Azure come with robust Microsoft-provided support and maintenance. These models are supported by their providers, with varying levels of SLA and support structures. 
+* **Innovation and Specialization**: Models from Partners and Community offer rapid access to specialized innovations and niche capabilities often developed by leading research labs and emerging AI providers.
 
-## Accessing Azure Ecosystem Models
-
-Azure Ecosystem Models are accessible through Azure AI Foundry, providing: 
-* Comprehensive details about the model's capabilities and integration requirements.
-* Community ratings, usage data, and qualitative feedback to guide your decisions.
-* Clear integration guidelines to help incorporate these models seamlessly into your Azure workflows.
-
-For more detailed guidance and exploration of available models, visit the [Azure AI Foundry documentation](/azure/ai-foundry/). 
- 
-Azure AI Foundry remains committed to providing a robust ecosystem, enabling customers to easily access the best AI innovations from Microsoft and our trusted partners. 
 
 ## Model collections
 
-The model catalog organizes models into different collections:
+The model catalog organizes models into different collections, including:
 
 * **Azure OpenAI models exclusively available on Azure**: Flagship Azure OpenAI models available through an integration with Azure OpenAI in Foundry Models. Microsoft supports these models and their use according to the product terms and [SLA for Azure OpenAI](https://www.microsoft.com/licensing/docs/view/Service-Level-Agreements-SLA-for-Online-Services).
 

articles/ai-foundry/concepts/model-catalog-content-safety.md

@@ -1,5 +1,5 @@
 ---
-title: Guardrails & controls for Azure Direct Models
+title: Guardrails & controls for Models Sold Directly by Azure 
 titleSuffix: Azure AI Foundry
 description: Learn about content safety for models deployed using standard deployments, using Azure AI Foundry.
 manager: scottpolly
@@ -13,7 +13,7 @@ reviewer: ositanachi
 ms.custom: 
 ---
 
-# Guardrails & controls for Azure Direct Models
+# Guardrails & controls for Models Sold Directly by Azure 
 
 [!INCLUDE [feature-preview](../includes/feature-preview.md)]
 

articles/ai-foundry/concepts/model-lifecycle-retirement.md

@@ -19,7 +19,7 @@ reviewer: fkriti
 Azure AI Foundry Models in the model catalog are continually refreshed with newer and more capable models. As part of this process, model providers might deprecate and retire their older models, and you might need to update your applications to use a newer model. This document communicates information about the model lifecycle and deprecation timelines and explains how you're informed of model lifecycle stages.
 
 > [!IMPORTANT]
-> This article describes deprecation and retirement only for Azure Direct models and Azure Ecosystem models models in Foundry Models. For information about deprecation and retirement for Azure OpenAI in Foundry Models, see the [Azure OpenAI models lifecycle](../../ai-services/openai/concepts/model-retirements.md?context=/azure/ai-foundry/context/context) documentation.
+> This article describes deprecation and retirement only for AModels Sold Directly by Azure and Models from Partners and Community in Foundry Models. For information about deprecation and retirement for Azure OpenAI in Foundry Models, see the [Azure OpenAI models lifecycle](../../ai-services/openai/concepts/model-retirements.md?context=/azure/ai-foundry/context/context) documentation.
 
 ## Model lifecycle stages
 

articles/ai-foundry/concepts/models-featured.md

@@ -364,5 +364,5 @@ For examples of how to use Stability AI models, see the following examples:
 - [Deploy models as standard deployments](../how-to/deploy-models-serverless.md)
 - [Model catalog and collections in Azure AI Foundry portal](../how-to/model-catalog-overview.md)
 - [Region availability for models in standard deployments](../how-to/deploy-models-serverless-availability.md)
-- [Content safety for  Azure Direct Models](model-catalog-content-safety.md)
+- [Content safety for  Models Sold Directly by Azure ](model-catalog-content-safety.md)
 

articles/ai-foundry/how-to/concept-data-privacy.md

@@ -35,7 +35,7 @@ Deploying models to managed compute deploys model weights to dedicated virtual m
 
 You manage the infrastructure for these managed compute resources. Azure data, privacy, and security commitments apply. To learn more about Azure compliance offerings applicable to Azure AI Foundry, see the [Azure Compliance Offerings page](https://servicetrust.microsoft.com/DocumentPage/7adf2d9e-d7b5-4e71-bad8-713e6a183cf3).
 
-Although containers for **Azure Direct Models** are scanned for vulnerabilities that could exfiltrate data, not all models available through the model catalog are scanned. To reduce the risk of data exfiltration, you can [help protect your deployment by using virtual networks](configure-managed-network.md). You can also use [Azure Policy](../../ai-services/policy-reference.md) to regulate the models that your users can deploy.
+Although containers for **Models Sold Directly by Azure** are scanned for vulnerabilities that could exfiltrate data, not all models available through the model catalog are scanned. To reduce the risk of data exfiltration, you can [help protect your deployment by using virtual networks](configure-managed-network.md). You can also use [Azure Policy](../../ai-services/policy-reference.md) to regulate the models that your users can deploy.
 
 :::image type="content" source="../media/explore/subscription-service-cycle.png" alt-text="Diagram that shows the platform service life cycle." lightbox="../media/explore/subscription-service-cycle.png":::
 

articles/ai-foundry/how-to/configure-managed-network.md

@@ -29,7 +29,7 @@ You need to configure following network isolation configurations.
 - Choose network isolation mode. You have two options: allow internet outbound mode or allow only approved outbound mode.
 - If you use Visual Studio Code integration with allow only approved outbound mode, create FQDN outbound rules described in the [use Visual Studio Code](#scenario-use-visual-studio-code) section.
 - If you use HuggingFace models in Models with allow only approved outbound mode, create FQDN outbound rules described in the [use HuggingFace models](#scenario-use-huggingface-models) section.
-- If you use one of the open-source models with allow only approved outbound mode, create FQDN outbound rules described in the [Azure Direct Models](#scenario-azure-direct-models) section.
+- If you use one of the open-source models with allow only approved outbound mode, create FQDN outbound rules described in the [Models Sold Directly by Azure ](#scenario-azure-direct-models) section.
 
 ## Network isolation architecture and isolation modes
 
@@ -812,7 +812,7 @@ If you plan to use __HuggingFace models__ with the hub, add outbound _FQDN_ rule
 * cnd.auth0.com
 * cdn-lfs.huggingface.co
 
-### Scenario: Azure Direct Models
+### Scenario: Models Sold Directly by Azure 
 
 These models involve dynamic installation of dependencies at runtime, and require outbound _FQDN_ rules to allow traffic to the following hosts:
 

articles/ai-foundry/includes/content-safety-serverless-apis-note.md

@@ -13,4 +13,4 @@ ms.custom: include file
 ---
 
 > [!NOTE]
-> Azure AI Content Safety is currently available for models deployed as standard deployment, but not to models deployed via managed compute. To learn more about Azure AI Content Safety for models deployed as standard deployment, see [Guardrails & controls for Azure Direct Models](../concepts/model-catalog-content-safety.md).
+> Azure AI Content Safety is currently available for models deployed as standard deployment, but not to models deployed via managed compute. To learn more about Azure AI Content Safety for models deployed as standard deployment, see [Guardrails & controls for Models Sold Directly by Azure ](../concepts/model-catalog-content-safety.md).

articles/ai-foundry/includes/content-safety-serverless-models.md

@@ -13,7 +13,7 @@ ms.custom: include file
 # Also used in Azure Machine Learning documentation
 ---
 
-For language models deployed via standard deployment, Azure AI implements a default configuration of [Azure AI Content Safety](../../ai-services/content-safety/overview.md) text moderation filters that detect harmful content such as hate, self-harm, sexual, and violent content. To learn more about content filtering, see [Guardrails & controls for Azure Direct Models](../concepts/model-catalog-content-safety.md). 
+For language models deployed via standard deployment, Azure AI implements a default configuration of [Azure AI Content Safety](../../ai-services/content-safety/overview.md) text moderation filters that detect harmful content such as hate, self-harm, sexual, and violent content. To learn more about content filtering, see [Guardrails & controls for Models Sold Directly by Azure](../concepts/model-catalog-content-safety.md). 
 
 > [!TIP]
 > Content filtering is not available for certain model types that are deployed via standard deployments. These model types include embedding models and time series models.

articles/ai-foundry/model-inference/concepts/models.md

@@ -17,15 +17,15 @@ ms.custom: references_regions, tool_generated
 
 Azure AI Foundry Models gives you access to flagship models in Azure AI Foundry to consume them as APIs without hosting them on your infrastructure.
 
-A selection of models is offered directly by Microsoft under [Azure Direct Models](#azure-direct-models) which brings the most powerful options to developers to build AI applications. We also enable the breath of models by partnering with key players in the industry and bringing [Azure Ecosystem Models](#azure-ecosystem-models).
+A selection of models is offered directly by Microsoft under [Models Sold Directly by Azure](#azure-direct-models) which brings the most powerful options to developers to build AI applications. We also enable the breath of models by partnering with key players in the industry and bringing [Models from Partners and Community](#models-from-partners-and-community).
 
 
 :::image type="content" source="../media/models/models-catalog.gif" alt-text="An animation showing Azure AI Foundry portal model catalog section and the models available." lightbox="../media/models/models-catalog.gif":::
 
 
-## Azure Direct Models
+## Models Sold Directly by Azure 
 
-Azure Direct Models is a selection of flagship models offered directly by Microsoft. These models don't require integration with Azure Marketplace. 
+Models Sold Directly by Azure  is a selection of flagship models offered directly by Microsoft. These models don't require integration with Azure Marketplace. 
 
 ### Azure OpenAI
 
@@ -65,7 +65,7 @@ See [this model collection in Azure AI Foundry portal](https://ai.azure.com/expl
 
 ### Microsoft
 
-Microsoft models include various model groups such as MAI models, Phi models, healthcare AI models, and more. Some Microsoft models are offered as [Azure Ecosystem Models](#azure-ecosystem-models). To see all the available Microsoft models, view [the Microsoft model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=phi).
+Microsoft models include various model groups such as MAI models, Phi models, healthcare AI models, and more. Some Microsoft models are offered as [Models from Partners and Community](#models-from-partners-and-community). To see all the available Microsoft models, view [the Microsoft model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=phi).
 
 
 | Model  | Type | Tier | Capabilities |
@@ -74,7 +74,7 @@ Microsoft models include various model groups such as MAI models, Phi models, he
 
 ### Mistral AI
 
-Mistral AI offers two categories of models: premium models including Mistral Large and Mistral Small and open models including Mistral Nemo. Some Mistral models are offered as [Azure Ecosystem Models](#azure-ecosystem-models).
+Mistral AI offers two categories of models: premium models including Mistral Large and Mistral Small and open models including Mistral Nemo. Some Mistral models are offered as [Models from Partners and Community](#models-from-partners-and-community).
 
 | Model  | Type | Tier | Capabilities |
 | ------ | ---- | --- | ------------ |
@@ -84,7 +84,7 @@ See [this model collection in Azure AI Foundry portal](https://ai.azure.com/expl
 
 ### Meta
 
-Meta Llama models and tools are a collection of pretrained and fine-tuned generative AI text and image reasoning models. Meta Llama 4 is part of Azure Direct Models, while the rest of the Llama family is offered as [Azure Ecosystem Models](#azure-ecosystem-models).
+Meta Llama models and tools are a collection of pretrained and fine-tuned generative AI text and image reasoning models. Meta Llama 4 is part of Models Sold Directly by Azure, while the rest of the Llama family is offered as [Models from Partners and Community](#models-from-partners-and-community).
 
 | Model  | Type | Tier | Capabilities |
 | ------ | ---- | --- | ------------ |
@@ -93,11 +93,11 @@ Meta Llama models and tools are a collection of pretrained and fine-tuned genera
 
 See [this model collection in Azure AI Foundry portal](https://ai.azure.com/explore/models?&selectedCollection=meta).
 
-## Azure Ecosystem Models
+## Models from Partners and Community
 
-Azure Ecosystem Models available for deployment with pay-as-you-go billing (for example, Cohere models) are offered by the model provider but hosted in Microsoft-managed Azure infrastructure and accessed via API in the Azure AI Foundry. Model providers define the license terms and set the price for use of their models, while Azure AI Foundry manages the hosting infrastructure.
+Models from Partners and Community available for deployment with pay-as-you-go billing (for example, Cohere models) are offered by the model provider but hosted in Microsoft-managed Azure infrastructure and accessed via API in the Azure AI Foundry. Model providers define the license terms and set the price for use of their models, while Azure AI Foundry manages the hosting infrastructure.
 
-Azure Ecosystem Models are offered through Azure Marketplace and [requires additional configuration for enabling](../how-to/configure-marketplace.md). 
+Models from Partners and Community are offered through Azure Marketplace and [requires additional configuration for enabling](../how-to/configure-marketplace.md). 
 
 ### AI21 Labs