Datacloud: RAG Retrievers Helps Business to Unlock Unstructured Data

This post educates on two advanced search techniques that leverage artificial intelligence for enhanced search capabilities. Semantic Search/Vector Search is an AI-driven method that goes beyond traditional keyword matching. It focuses on comprehending the context and purpose behind a user's search query, leading to more precise and relevant results. Retrieval Augmented Generation (RAG) in Data Cloud introduces a framework designed to enhance large language model (LLM) prompts. By enriching prompts with up-to-date and relevant data, RAG elevates the accuracy and usefulness of LLM responses, providing users with more valuable information. When you submit an LLM prompt, RAG in Data Cloud: Retrieves relevant information from structured and unstructured data indexed in Data Cloud’s vector database Augments the prompt by combining this information with the original prompt Generates a prompt response #rag #retriever #llm #ai #salesforceai #agentforce #RetrievalAugmentedGeneration #datacloud #salesforce @salesforce