RAG Custom Databases

What is RAG?

RAG (Retrieval-Augmented Generation) allows your AI to search through custom databases of information at runtime. Instead of cramming everything into the prompt, the AI retrieves relevant content when it needs it.

Creating a RAG Database

RAG databases work across all assistant types: Voice AI, Chat AI, and Web Orbs.

Navigate to Knowledge

Go to the Knowledge section in your dashboard.

Create Database

Create a new knowledge base and select the RAG database option.

Add Content

Upload your data — documents, text entries, FAQs, or website content. The system indexes this for semantic search.

Connect to Assistant

Link the RAG database to your assistant. The AI will automatically search it when relevant questions arise.

When to Use RAG vs. Standard Knowledge Base

Feature	Standard KB	RAG Database
Best for	Small, focused datasets	Large, diverse content
Retrieval	Full context in prompt	Semantic search at runtime
Token usage	Higher (always loaded)	Lower (retrieved on demand)
Accuracy	Very high for exact matches	High for broad topics

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What is RAG?

Creating a RAG Database

When to Use RAG vs. Standard Knowledge Base

​What is RAG?

​Creating a RAG Database

​When to Use RAG vs. Standard Knowledge Base

What is RAG?

Creating a RAG Database

When to Use RAG vs. Standard Knowledge Base