Retrieval Augmented Generation

Use Retrieval Augmented Generation (RAG) in Data 360 to improve large language model (LLM) responses for agents and users. RAG is a framework for grounding prompts with relevant, accurate knowledge from unstructured data sources.

• About Retrieval Augmented Generation
  Learn how Retrieval Augmented Generation (RAG) in Data 360 enhances your Agentforce and Einstein generative AI solutions with knowledge.
• Example: Agentic RAG with Advanced Data 360 Setup
  This example walks you through the end-to-end steps to implement an agent that's grounded with knowledge using Retrieval Augmented Generation (RAG) in Data 360.
• Troubleshooting Knowledge Retrieval for Agents
  Solve common retrieval augmented generation (RAG) issues for agents.