How do I implement RAG with multiple data sources?

Direct Answer

RAG (Retrieval-Augmented Generation) combines search and generation to provide accurate, grounded answers. It retrieves relevant information from your knowledge base, then uses that context to generate responses. This approach reduces hallucinations and keeps answers current without retraining models.

Key Considerations

• Start with clear objectives and success metrics
• Iterate based on data and feedback
• Focus on user needs and business outcomes
• Maintain quality while moving quickly

Takeaway & Related Resources

• What is RAG?
• AI Workflow Automation Guide