How do you implement RAG for customer support knowledge bases?

RAG for customer support indexes product documentation, troubleshooting guides, FAQ databases, known issues, and resolution procedures. Key considerations include priority-based retrieval weighting recent known issues higher than general documentation, customer context integration pulling relevant account details and product configuration, multi-language support for international customer bases, and confidence-based routing escalating to human agents when retrieval confidence is low. The chunking strategy should preserve complete troubleshooting steps rather than splitting them across chunks. Include metadata about product versions, issue severity, and resolution success rates. Implement intent classification to route queries to the appropriate knowledge domain before retrieval. Track which knowledge base articles resolve issues to improve ranking. Integrate with ticketing systems to automatically log the AI response and retrieved sources for agent review when escalation occurs.