Update cache-overview-vector-similarity.md

Author: MSFTeegarden

articles/azure-cache-for-redis/cache-overview-vector-similarity.md

@@ -1,5 +1,5 @@
 ---
-title: What is Vector Similarity in Azure Cache for Redis?
+title: About Vector Embeddings and Vector Search in Azure Cache for Redis
 description: Learn about Azure Cache for Redis to store vector embeddings and provide similarity search.
 author: flang-msft
 ms.author: franlanglois
@@ -8,14 +8,19 @@ ms.topic: overview
 ms.date: 09/18/2023
 ---
 
-# What is Vector Similarity in Azure Cache for Redis?
+# About Vector Embeddings and Vector Search in Azure Cache for Redis
 
-You could rename this "about". Overview documents contain "nice-to-know" information,
-like background information, that is not strictly required to complete a task, but
-builds the readers confidence in the technology, when to use it, etc.
+Vector similarity search (VSS) has become a very popular use-case for AI-driven applications. Azure Cache for Redis can be used to store vector embeddings and compare them through vector similarity search. This article is a high-level introduction to the concept of vector embeddings, vector comparison, and how Redis can be used as a seamless part of a vector similarity workflow. 
 
-I stole this from your tutorial ... we can break this up and expand on it throughout
-this document:
+For a tutorial on how to use Azure Cache for Redis and Azure OpenAI to perform vector similarity search, see [Tutorial: Conduct  vector similarity search on Azure OpenAI embeddings using Azure Cache for Redis](cache-tutorial-vector-similarity.md)
+
+## Scope of Availability
+
+|Tier      | Basic, Standard  | Premium  |Enterprise | Enterprise Flash  |
+|--------- |:------------------:|:----------:|:---------:|:---------:|
+|Available | No          | No       |  Yes  | Yes (preview) |
+
+Vector search capabilities in Redis require [Redis Stack](https://redis.io/docs/about/about-stack/), specifically the [RediSearch](https://redis.io/docs/interact/search-and-query/) module. This capability is only available in the [Enterprise tiers of Azure Cache for Redis](cache-redis-modules.md).
 
 ```markdown
 Azure Cache for Redis can be used to store the embeddings vectors and to perform the vector similarity search. Redis is extremely fast because it runs in-memory. This can be very useful when processing large datasets!
@@ -26,6 +31,7 @@ Redis has access to a wide range of search capabilities through the [RediSearch
 - `FLAT` and `Hierarchical Navigable Small World (HNSW)`  indexing methods
 - Hybrid filtering with [powerful query features](https://redis.io/docs/interact/search-and-query/)
 ```
+## What are embeddings?
 
 ## What is a vector database?
 
@@ -73,4 +79,4 @@ help the reader find other solutions, you've done them a great service.
 
 You may want to just point out the top one or two scenarios you've come across
 in testing that trip up users. Point them to most extensive documentation on Redis'
-site.
+site.