Update content/develop/ai/genai-apps.md

Co-authored-by: andy-stark-redis <164213578+andy-stark-redis@users.noreply.github.com>

Author: mich-elle-luna

content/develop/ai/genai-apps.md

@@ -17,7 +17,7 @@ Redis excels in storing and indexing vector embeddings that semantically represe
 ## Key Benefits of Redis in GenAI Apps
 
 - **Performance**: low-latency data access enables real-time interactions critical for AI-driven applications.
-- **Scalability**: designed to handle numerous concurrent connections, Redis is perfect for high-demand GenAI apps.
+- **Scalability**: Redis is designed to handle numerous concurrent connections, so it is perfect for high-demand GenAI apps.
 - **Caching**: efficiently stores frequently accessed data and responses, reducing primary database load and accelerating response times.
 - **Session Management**: in-memory data structures simplify managing session states in conversational AI scenarios.
 - **Flexibility**: Redis supports diverse data structures (for example, strings, hashes, lists, sets), allowing tailored solutions for GenAI apps.