Fixed Feedback

Emphasize cost savings by highlighting the reduction in monthly search spend from $1,250 to $250 due to shared Azure AI Search instance.

Author: Susmitha221

learn-pr/wwl-azure/configure-ai-ready-infrastructure-microsoft-foundry/includes/2-understand-microsoft-foundry-architecture-components.md

@@ -10,7 +10,7 @@ Projects sit at the bottom tier as isolated workspaces where teams build AI solu
 
 ## Connected resources and the sharing model
 
-Now that you understand the three-tier hierarchy, consider how Azure services integrate with this architecture. Connected resources—like Azure AI Search, Azure OpenAI Service, Azure Storage, and Application Insights—attach at either the hub or project level depending on whether they're shared or dedicated. Hub-level connections make the most impact: when you connect Azure AI Search at the hub level, all projects within that hub can query the same search service without duplicating configuration or incurring separate costs. Your five AI projects share one Standard-tier search instance instead of each provisioning its own Basic tier, cutting your monthly search spend from $1,250 to $250.
+Now that you understand the three-tier hierarchy, consider how Azure services integrate with this architecture. Connected resources—like Azure AI Search, Azure OpenAI Service, Azure Storage, and Application Insights—attach at either the hub or project level depending on whether they're shared or dedicated. Hub-level connections make the most impact: when you connect Azure AI Search at the hub level, all projects within that hub can query the same search service without duplicating configuration or incurring separate costs. Your five AI projects share one Standard-tier search instance instead of each provisioning its own Basic tier, cutting your monthly search spend from **$1,250** to **$250**.
 
 With this shared connection in place, project teams maintain logical isolation through separate search indexes. The E-commerce Bot Project queries the Product Catalog index containing 2 million product documents, while the Support Agent Project queries the Knowledge Base index with 500,000 troubleshooting articles. Both indexes live in the same hub-connected search service, yet each project only accesses its authorized data. At the same time, your centralized operations team monitors performance, manages capacity, and reviews audit logs from a single Azure AI Search resource instead of tracking metrics across multiple isolated instances.