Updating links and improving score

Author: mathapli

articles/confidential-computing/confidential-clean-rooms.md

@@ -20,52 +20,52 @@ Organizations can safely collaborate and analyze sensitive data, within the sand
 ## Who should use Azure Confidential Clean Rooms?
 Azure Confidential Clean Rooms could be a great choice for you if you have these scenarios: 
 
-- Data analytics and inferencing: Organizations looking to build insights on second-party data while ensuring data privacy can leverage ACCR. ACCR is useful when data providers are concerned about data exfiltration. ACCR ensures that data is only used for agreed purposes and safeguards against unauthorized access or egress (as it is a sandboxed environment). 
+- Data analytics and inferencing: Organizations looking to build insights on second-party data while ensuring data privacy can use ACCR. ACCR is useful when data providers are concerned about data exfiltration. ACCR ensures that data is only used for agreed purposes and safeguards against unauthorized access or egress (as it's a sandboxed environment). 
 - Data privacy ISVs: Independent Software Vendors (ISVs) who provide secure multiparty data collaboration services can use ACCR as an extensible platform. It allows them to add enforceable tamperproof contracts with governance and audit capabilities, and uses [Confidential containers or C-ACI](../confidential-computing/confidential-containers.md) underneath to ensure data is encrypted during processing so that their customers' data remains secure.
 - ML fine tuning: ACCR provides a solution to organizations that require data from various sources to train or fine-tune machine learning models but face data sharing regulations. It allows any party to audit and confirm that data is being used only for the agreed purpose, such as ML modeling.
-- ML inferencing: Organizations can leverage ACCR in machine learning (ML) inferencing to enable secure, collaborative data analysis without compromising privacy or data ownership. ACCR acts as secure environment where multiple parties can combine sensitive data and apply ML models for inferencing while keeping raw data inaccessible to others.
+- ML inferencing: Organizations can use ACCR in machine learning (ML) inferencing to enable secure, collaborative data analysis without compromising privacy or data ownership. ACCR acts as secure environment where multiple parties can combine sensitive data and apply ML models for inferencing while keeping raw data inaccessible to others.
 
 ### Industries which can successfully utilize ACCR
-1. Healthcare- In the healthcare industry, Azure Confidential Clean Rooms enable secure collaboration on sensitive patient data. For example, healthcare providers can use clean rooms to train and fine-tune AI/ML models for predictive diagnostics, personalized medicine, and clinical decision support. By leveraging confidential computing, healthcare organizations can protect patient privacy while collaborating with other institutions to improve healthcare outcomes.
-Subsequently, ACCR can also be used for ML inferencing where partner hospitals can utilize power of these models for early detection.
+1. Healthcare- In the healthcare industry, Azure Confidential Clean Rooms enable secure collaboration on sensitive patient data. For example, healthcare providers can use clean rooms to train and fine-tune AI/ML models for predictive diagnostics, personalized medicine, and clinical decision support. By using confidential computing, healthcare organizations can protect patient privacy while collaborating with other institutions to improve healthcare outcomes.
+ACCR can also be used for ML inferencing where partner hospitals can utilize power of these models for early detection.
 2. Advertising- In the advertising industry, Azure Confidential Clean Rooms facilitates secure data sharing between advertisers and publishers. ACCR enables targeted advertising and campaign effectiveness measurement without exposing sensitive user data.
 3. Banking, Financial Services and Insurance (BFSI) - The BFSI sector can use Azure Confidential Clean Rooms to securely collaborate on financial data, ensuring compliance with regulatory requirements. This enables financial institutions to perform joint data analysis and develop risk models, fraud detection models, lending scenarios among others without exposing sensitive customer information.
 4. Retail- In the retail industry, Azure Confidential Clean Rooms enables secure collaboration on customer data to enhance personalized marketing and inventory management. Retailers can use clean rooms to analyze customer behavior and preferences to create personalized marketing campaigns without compromising data privacy.
 
 ## Benefits
 
-:::image type="content" source="./media/confidential-clean-rooms/accr-benefits.png" alt-text="Graphic of Azure Confidential Clean Rooms benefits, showing zero trust, no data duplicationm container workloads, and managed governance.":::
+:::image type="content" source="./media/confidential-clean-rooms/accr-benefits.png" alt-text="Graphic of Azure Confidential Clean Rooms benefits, showing zero trust, no data duplication of container workloads, and managed governance.":::
 
 Azure Confidential Clean Rooms (ACCR) provides a secure and compliant environment for multi-party data collaboration. Built on [Confidential containers or C-ACI](../confidential-computing/confidential-containers.md), ACCR ensures that sensitive data remains protected throughout the collaboration process. Here are some key benefits of using Azure Confidential Clean Rooms:
 
 - Secure collaboration and governance:
-ACCR allows collaborators to create tamper-proof contracts. ACCR also enforces all the constraints which are part of the contract. Governance ensures validity of constraints before allowing data to be released into clean rooms and drives transparency amongst collaborators by generating tamper-proof audit trails. ACCR uses the open-sourced [confidential consortium framework](https://microsoft.github.io/CCF/main/overview/what_is_ccf.html) to enable these capabilities.
+ACCR allows collaborators to create tamper-proof contracts. ACCR also enforces all the constraints which are part of the contract. Governance ensures validity of constraints before allowing data to be released into clean rooms and drives transparency among collaborators by generating tamper-proof audit trails. ACCR uses the open-sourced [confidential consortium framework](https://microsoft.github.io/CCF/main/overview/what_is_ccf.html) to enable these capabilities.
 - Compliance:
 Confidential computing can address some of the regulatory and privacy concerns by providing a secure environment for data collaboration. This capability is beneficial for industries such as financial services, healthcare, and telecom, which deal with highly sensitive data and personally identifiable information (PII).
 - Enhanced data security:
 ACCR is built using confidential computing to provide a hardware-based, trusted execution environment (TEE). This environment is sandboxed and allows only authorized workloads to execute and prevents unauthorized access to data or code during processing, ensuring that sensitive information remains secure.
 - Verifiable trust at each step with the help of cryptographic remote attestation forms the cornerstone of Azure Confidential Clean Rooms.
 
 - Cost-effective: 
-By providing a secure and compliant environment for data collaboration, ACCR reduces the need for costly and complex data protection measures. This makes it a cost-effective solution for organizations looking to leverage sensitive data for analysis and insights.
+By providing a secure and compliant environment for data collaboration, ACCR reduces the need for costly and complex data protection measures. This makes it a cost-effective solution for organizations looking to use sensitive data for analysis and insights.
 
 :::image type="content" source="./media/confidential-clean-rooms/accr-illustration.png" alt-text="Graphic of Azure Confidential Clean Rooms benefits, showing all steps of clean room creation.":::
 
 
 ## Onboarding to Azure Confidential Clean Rooms
-ACCR is currently in Gated Preview. To express your interest in joining the gated preview, please follow these steps:
+ACCR is currently in Gated Preview. To express your interest in joining the gated preview, follow these steps:
 - Fill and submit the form at https://aka.ms/ACCR-Preview-Onboarding.
 - Once you submit, further steps will be shared with you on onboarding. 
 - For further questions on onboarding reach out to  [email protected].
-- After reviewing details, we will reach out to you with detailed steps for onboarding.
+- After reviewing details, we'll reach out to you with detailed steps for onboarding.
 
 ## Frequently asked questions
 
 - Question: Where is the location Microsoft published side cars?
-  Answer: The Microsoft published side cars are available at: mcr.microsoft.com/cleanroom. The code repository for the sidecars is present [here](https://github.com/Azure/azure-cleanroom).
+  Answer: The Microsoft published side cars are available at: mcr.microsoft.com/cleanroom. The code repository for the sidecars is present [here](https://github.com/Azure/azure-cleanroom/).
 
 - Question: Is there a sampleclean room application to try out?
-  Answer: You can find the clean room sample application [here](https://github.com/Azure/azure-cleanroom-samples/). Please feel free to try out the sample after signing up for the Preview and receiving our response. 
+  Answer: You can find the clean room sample application [here](https://github.com/Azure-Samples/azure-cleanroom-samples). Please feel free to try out the sample after signing up for the Preview and receiving our response. 
 
 - Question: Can more than two collaborators participate in a collaboration?
   Answer: Yes, more than two collaborators can become part of collaboration. This allows multiple data providers to share data in the clean room.