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                 <li><strong>Vector Storage (Embeddings)</strong>: Preprocessed data is embedded and stored in a vector database (e.g., Pinecone) for semantic search and RAG operations.</li>
                 <li><strong>Real-time Updates (MCP Stream)</strong>: MCPs continuously stream real-time events and updates (e.g., user actions, market changes, regulatory alerts) to the Knowledge Integration layer.</li>
                 <li><strong>Knowledge Integration (Context)</strong>: This layer combines retrieved information from the Vector Storage with real-time updates to build a comprehensive context for the RAG Engine and specialized agents.</li>
-                <li><strong>Response Generation (Agent Output)</strong>: The RAG Engine and specialized agents process queries and context to generate intelligent responses, proactive interventions, or actionable insights.</li>
+                <li><strong>Response Generation (Agent Output/Export to csv)</strong>: The RAG Engine and specialized agents process queries and context to generate intelligent responses, proactive interventions, or actionable insights.</li>
             </ul>
             
         </section>