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RAG (Retrieval-Augmented Generation) lets you give your assistant custom knowledge by uploading documents, FAQs, and other content. Your AI can then reference this information to give accurate, specific answers.

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What is RAG?

RAG combines your custom knowledge with the AI’s general intelligence:
  1. Upload documents (PDFs, text files, web pages, etc.)
  2. AI processes and indexes the content
  3. During calls, the AI searches your knowledge base
  4. Combines retrieved information with its response
Think of RAG as giving your AI a “company handbook” it can instantly reference during conversations.

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How to Set Up RAG

Supported Formats:
  • PDF documents
  • Text files (.txt, .md)
  • Web pages (URLs)
  • Structured data (JSON, CSV)
Content Tips:
  • Keep documents focused and well-organized
  • Use clear headings and sections
  • Include FAQs, product info, policies, etc.
  • Remove outdated or irrelevant information
  1. Go to your assistant’s RAG Configuration section
  2. Click “Upload Documents” or “Add Knowledge”
  3. Upload files or paste URLs
  4. Wait for processing (may take a few minutes)
  5. Test with sample questions
Start with your most important documents—you can always add more later!
  • Similarity Threshold: How closely questions must match content
  • Max Results: Number of knowledge pieces to retrieve
  • Context Window: How much text to include in responses
Higher similarity thresholds are more selective but may miss relevant content. Start with default settings and adjust based on testing.

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Use Cases

  • Product manuals and troubleshooting guides
  • Company policies and procedures
  • FAQ documents
  • Return/refund policies
Example: “How do I return a product?” → AI finds your return policy and gives specific instructions.
  • Product catalogs and specifications
  • Pricing information
  • Company background and history
  • Service descriptions
Example: “What services do you offer?” → AI references your service catalog for accurate details.
  • Employee handbooks
  • Internal procedures
  • Technical documentation
  • Training materials
Example: “What’s our vacation policy?” → AI finds the relevant HR policy section.

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Best Practices

  • Quality over quantity: Better to have fewer, high-quality documents than many poor ones
  • Keep content updated: Regularly review and update your knowledge base
  • Test thoroughly: Ask questions you expect callers to ask and verify accuracy
  • Use clear language: Write content in plain language, avoiding jargon when possible
  • Organize logically: Group related information together

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Troubleshooting

  • AI doesn’t find relevant info: Check similarity threshold, add more specific keywords
  • Outdated information: Remove or update old documents
  • Conflicting answers: Ensure documents don’t contradict each other
  • Too much irrelevant content: Use more focused, specific documents
RAG works best when combined with a well-written system prompt that tells the AI how to use the knowledge base effectively.