Customer Support Triage Agent
customer-support
The Problem
Support teams waste hours manually reading and routing tickets. Customers wait longer, agents burn out on repetitive sorting, and urgent issues get buried in the queue.
The Solution
An AI agent that instantly reads incoming tickets, determines urgency and category, and routes them to the right team—before a human even sees the queue.
How It Works
- Intake: New ticket arrives via email, chat, or form
- Analysis: Agent reads the message, detects sentiment and intent
- Classification: Assigns category (billing, technical, general) and priority (urgent, normal, low)
- Routing: Sends to appropriate team or triggers auto-response for common questions
- Handoff: Agent provides context summary for the human agent
Tool Stack
- n8n: Workflow orchestration and integrations
- OpenAI/Claude: Natural language understanding
- Zendesk/Freshdesk: Ticket management (or any helpdesk with API)
- Slack: Team notifications for urgent issues
Example Prompt
You are a customer support triage specialist. Analyze the following support ticket and respond with JSON:
{
"category": "billing|technical|account|general|urgent",
"priority": "high|medium|low",
"sentiment": "frustrated|neutral|positive",
"summary": "One sentence summary",
"suggested_response": "Draft response if straightforward",
"needs_human": true/false
}
Ticket:
{{ticket_content}}
Implementation Tips
- Start with just 3-4 categories to keep accuracy high
- Set confidence thresholds—if unsure, escalate to human
- Log all decisions for review and improvement
- Build a feedback loop: agents mark "correct/incorrect" routing
When to Use This
- Support volume exceeds 50 tickets/day
- Response time SLAs are suffering
- Agents spend more time routing than solving
- You have clear category definitions
Limitations
- Won't replace human judgment for complex issues
- Needs training data from your actual tickets
- Sentiment detection isn't perfect—always have escalation paths