A discussion about RAG, Vector Database , and Their Monetization Potential, as well as an Analysis of Elastic as a Company-Part-3

In this department, we also interviewed some relevant experts who provided additional insights into RAG and VectorDB.

1. Cost Differences Between CSPs and Independent Database Projects

Regarding cost differences, only deep users will pay particular attention to this aspect. For instance, many large vendors develop conversational capabilities that allow clients to interact with their systems. In these interactions, the system can understand prior information exchanges based on context rather than starting anew with each question. A typical example is Notion.AI. Their models are not only applicable to Q&A but also relevant to business contexts, especially in CRM systems designed for maintaining customer relationships. These systems typically need to retain contextual information, but the context for each client is not necessarily extensive. The challenge arises from having numerous user tenants; for example, OpenAI or Notion AI might have millions of users, each with low engagement. This contrasts sharply in the application of RAG for startup companies focused on single enterprises.