The Vector Storage Process

1. Text Conversion: Documents and text chunks are processed through embedding models that convert words and sentences into numerical vectors

2. In-Memory Storage: These vectors are stored in RAM, enabling ultra-fast access without database setup

3. Similarity Operations: When queries are made, the system finds information by calculating vector distances - matching concepts, not just keywords

4. Integration Power: Seamlessly connects with other n8n nodes for document processing, AI model interaction, and workflow automation