RAG (Retrieval Augmented Generation) allows AI to access internal knowledge bases before providing answers, unlike general AI models like GPT and Claude.
Traditional keyword-based search is complemented by vector search, enabling semantic search powered by vector databases.
AI like RAG ensures that specific business-related questions are answered accurately by leveraging internal company knowledge.
Memory modules can be implemented to enhance AI's ability to remember and provide continuous learning beyond one-off queries.