To set up a Retrieval-Augmented Generation (RAG) system, you will need the following:

• Knowledge Base: Built on an AI search instance, the knowledge base holds indexed content that the bot queries to provide relevant information.

• Azure OpenAI Instance: Access to an Azure OpenAI instance is required to power the large language model (LLM). The large language model enriches user queries, generates optimized search terms, and synthesizes results into coherent, context-aware responses.

RAG Project Management in Zammo

Zammo provides a dedicated RAG Projects page to streamline the management and configuration of RAG systems. This centralized interface allows you to:

• Configure pre-search optimizations, bot personas, and query types to enhance bot performance.

• Make adjustments easily using natural language inputs.

• Test and fine-tune settings to ensure optimal results for your use case.

Key Features of RAG Projects:

• Customizable Projects: Create multiple RAG projects to support different use cases, such as department-specific bots or task-oriented assistants.