add images

qdrant-landing/content/documentation/agentic-rag-crewai-zoom.md

@@ -2,9 +2,11 @@
 title: Simple Agentic RAG System
 weight: 12
 partition: build
+social_preview_image: /documentation/examples/agentic-rag-crewai-zoom/social_preview.png
 ---
+![agentic-rag-crewai-zoom](/documentation/examples/agentic-rag-crewai-zoom/agentic-rag-1.png)
 
-# Agentic RAG With Claude, CrewAI & Qdrant 
+# Agentic RAG With CrewAI & Qdrant Vector Database
 
 | Time: 45 min | Level: Beginner | Output: [GitHub](https://github.com/qdrant/examples/tree/master/agentic_rag_zoom_crewai) |
 | --- | ----------- | ----------- |----------- |
@@ -80,6 +82,8 @@ The system is built on three main components:
 
 ## Getting Started
 
+![agentic-rag-crewai-zoom](/documentation/examples/agentic-rag-crewai-zoom/agentic-rag-2.png)
+
 1. **Get API Credentials for Qdrant**:
    - Sign up for an account at [Qdrant Cloud](https://cloud.qdrant.io/).
    - Create a new cluster and copy the **Cluster URL** (format: https://xxx.gcp.cloud.qdrant.io).
@@ -344,6 +348,8 @@ This combination of features creates an interface that's both powerful and appro
 ---
 ## Conclusion
 
+![agentic-rag-crewai-zoom](/documentation/examples/agentic-rag-crewai-zoom/agentic-rag-3.png)
+
 This tutorial has demonstrated how to build a sophisticated meeting analysis system that combines vector search with AI agents. Let's recap the key components we've covered:
 
 1. **Vector Search Integration**