{"workflow":{"id":14826,"name":"Route and triage support tickets with Claude Sonnet and your CRM","views":57,"recentViews":11,"totalViews":57,"createdAt":"2026-04-06T16:18:43.019Z","description":"\n\n## Overview\nThis workflow automates customer support ticket processing using AI-powered analysis, classification, and intelligent routing.\n\nIt processes incoming tickets from email or webhook, translates messages when needed, analyzes sentiment and urgency, and routes tickets to auto-reply or escalation flows. The system also updates CRM platforms and logs observability metrics for monitoring.\n\nThis enables faster response times, improved customer experience, and scalable support operations.\n\n---\n\n## How It Works\n\n1. **Input Sources**\n   - Receives tickets via:\n     - IMAP Email Trigger\n     - Webhook endpoint\n\n2. **Workflow Configuration**\n   - Defines:\n     - CRM/Helpdesk API endpoint\n     - Escalation webhook URL\n     - Observability logging endpoint\n\n3. **Data Cleaning & Normalization**\n   - Extracts and cleans HTML content\n   - Normalizes ticket data:\n     - Ticket ID\n     - User email\n     - Message content\n     - Timestamp\n     - Source channel\n\n4. **Language Detection & Translation**\n   - Detects the original language\n   - Translates message into English if needed\n   - Returns confidence score\n\n5. **AI Support Intelligence**\n   - Classifies ticket into:\n     - Sentiment (positive/neutral/negative)\n     - Urgency (low → critical)\n     - Category (billing, bug, technical, etc.)\n   - Generates:\n     - Short summary\n     - Churn risk score (0–1)\n     - Recommended action path\n\n6. **Decision Routing**\n   - Routes tickets based on AI output:\n     - **Auto Reply** → Generate response\n     - **Escalate / Critical** → Send to team\n\n---\n\n### Auto Reply Flow\n\n7. **AI Reply Generation**\n   - Drafts professional response using ticket context\n   - Keeps tone empathetic and actionable\n\n8. **CRM/Helpdesk Update**\n   - Sends structured ticket data to CRM:\n     - Priority\n     - Category\n     - Sentiment\n     - Churn risk\n     - Draft reply\n\n---\n\n###  Escalation Flow\n\n9. **Escalation Handling**\n   - Sends high-priority tickets to support team\n   - Includes full ticket context and analysis\n\n---\n\n###  Observability & Monitoring\n\n10. **Metrics Logging**\n   - Tracks:\n     - Response time\n     - Escalation status\n     - Category & urgency\n     - Sentiment & churn risk\n   - Sends data to observability endpoint (optional)\n\n---\n\n## Setup Instructions\n\n1. **Email / Webhook Setup**\n   - Configure IMAP credentials OR webhook endpoint (`support-ticket`)\n\n2. **AI Model Setup**\n   - Add Anthropic or OpenAI credentials\n   - Connect models to:\n     - Translation agent\n     - Intelligence agent\n     - Reply generator\n\n3. **CRM / Helpdesk Integration**\n   - Set API endpoint URL\n   - Configure headers and authentication\n\n4. **Escalation Setup**\n   - Add webhook URL for team notifications (Slack, internal API, etc.)\n\n5. **Observability (Optional)**\n   - Configure logging endpoint for metrics tracking\n\n6. **Customize Prompts**\n   - Adjust system messages for:\n     - Translation\n     - Classification\n     - Reply generation\n\n---\n\n## Use Cases\n\n- AI-powered customer support automation  \n- SaaS support ticket triaging  \n- Multi-language support systems  \n- Helpdesk automation with CRM integration  \n- Customer churn risk detection workflows  \n\n---\n\n## Requirements\n\n- Anthropic or OpenAI API key  \n- Email (IMAP) or webhook source  \n- CRM/helpdesk system API  \n- Optional observability/logging service  \n- n8n instance  \n\n---\n\n## Key Features\n\n- Multi-channel ticket ingestion (email + webhook)  \n- Automatic language detection and translation  \n- AI-based sentiment, urgency, and category classification  \n- Intelligent routing (auto-reply vs escalation)  \n- AI-generated support replies  \n- CRM integration for structured ticket updates  \n- Observability and performance tracking  \n\n---\n\n## Summary\n\nA powerful AI-driven support automation workflow that processes, analyzes, and routes customer tickets intelligently. It reduces manual workload, improves response speed, and enables scalable, data-driven support operations.","workflow":{"meta":{"instanceId":"48aac30adfc5487a33ef16e0e958096f27cef40df3ed0febcbe1ca199e789786","templateCredsSetupCompleted":true},"nodes":[{"id":"94cd9674-983f-47f4-ae32-df54556141e3","name":"Email Trigger (IMAP)","type":"n8n-nodes-base.emailReadImap","position":[-1328,416],"parameters":{"options":{}},"typeVersion":2.1},{"id":"f531a644-2fbd-4509-ac1d-f7c4a0229b76","name":"Webhook Trigger","type":"n8n-nodes-base.webhook","position":[-1184,544],"webhookId":"59430543-8000-45f2-a606-806eeb30c586","parameters":{"path":"support-ticket","options":{},"httpMethod":"POST","responseMode":"lastNode"},"typeVersion":2.1},{"id":"9f2d29fe-938c-4a07-a5ab-e45e46040367","name":"Workflow Configuration","type":"n8n-nodes-base.set","position":[-864,432],"parameters":{"options":{},"assignments":{"assignments":[{"id":"id-1","name":"crmApiUrl","type":"string","value":"<__PLACEHOLDER_VALUE__CRM/Helpdesk API URL__>"},{"id":"id-2","name":"escalationWebhookUrl","type":"string","value":"<__PLACEHOLDER_VALUE__Escalation Webhook URL__>"},{"id":"id-3","name":"observabilityEndpoint","type":"string","value":"<__PLACEHOLDER_VALUE__Observability Logging Endpoint__>"}]},"includeOtherFields":true},"typeVersion":3.4},{"id":"5807dd75-bd42-488f-8b38-33e7c9090dc0","name":"Clean HTML","type":"n8n-nodes-base.html","position":[-640,432],"parameters":{"options":{},"operation":"extractHtmlContent","dataPropertyName":"={{ $json.html || $json.body || $json.text }}","extractionValues":{"values":[{}]}},"typeVersion":1.2},{"id":"b5d78aa5-8191-44c9-953a-eb9e70b29ca2","name":"Normalize Ticket Data","type":"n8n-nodes-base.set","position":[-448,432],"parameters":{"options":{},"assignments":{"assignments":[{"id":"id-1","name":"ticket_id","type":"string","value":"={{ $json.id || $json.messageId || $now }}"},{"id":"id-2","name":"user_email","type":"string","value":"={{ $json.from || $json.email }}"},{"id":"id-3","name":"original_message","type":"string","value":"={{ $json.text }}"},{"id":"id-4","name":"timestamp","type":"string","value":"={{ $now }}"},{"id":"id-5","name":"source_channel","type":"string","value":"={{ $json.source || \"email\" }}"}]},"includeOtherFields":true},"typeVersion":3.4},{"id":"fbf994d0-0641-48ad-94c3-30e97cbebe8a","name":"Language Detection & Translation Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[-224,432],"parameters":{"text":"={{ $json.original_message }}","options":{"systemMessage":"You are a language detection and translation specialist.\n\nYour task is to:\n1. 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new Date(startTime);\n\n// Determine escalation status based on which path was taken\nconst escalationStatus = $input.item.json.escalated || false;\n\n// Get intelligence data from Support Intelligence Agent\nconst intelligenceData = $('Support Intelligence Agent').item.json;\n\nconst metrics = {\n  response_time: responseTime,\n  escalation_status: escalationStatus,\n  model_used: 'anthropic',\n  category: intelligenceData.category || 'unknown',\n  urgency: intelligenceData.urgency || 'unknown',\n  sentiment: intelligenceData.sentiment || 'unknown',\n  churn_risk: intelligenceData.churn_risk || 'unknown',\n  timestamp: currentTime\n};\n\n// Get observability endpoint from Workflow Configuration\nconst observabilityEndpoint = $('Workflow Configuration').item.json.observability_endpoint;\n\nif (observabilityEndpoint) {\n  try {\n    // Send metrics to observability endpoint\n    await $http.post(observabilityEndpoint, {\n      body: metrics,\n      headers: {\n        'Content-Type': 'application/json'\n      }\n    });\n    \n    return {\n      json: {\n        success: true,\n        metrics: metrics,\n        message: 'Metrics logged successfully'\n      }\n    };\n  } catch (error) {\n    return {\n      json: {\n        success: false,\n        metrics: metrics,\n        error: error.message,\n        message: 'Failed to send metrics to observability endpoint'\n      }\n    };\n  }\n} else {\n  // If no endpoint configured, just return the metrics\n  return {\n    json: {\n      success: true,\n      metrics: metrics,\n      message: 'No observability endpoint configured, metrics collected only'\n    }\n  };\n}"},"typeVersion":2},{"id":"65d76d99-fcf7-4da3-8e5d-e2815d00b652","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-1408,304],"parameters":{"color":7,"width":448,"height":432,"content":"## Input Layer\nReceive tickets via email or webhook"},"typeVersion":1},{"id":"e56fb971-f92b-4b6e-869e-fe479514d1e0","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-944,304],"parameters":{"color":7,"height":432,"content":"## Configuration\nSet CRM, escalation, and logging endpoints"},"typeVersion":1},{"id":"3e2f398e-508a-4208-b20d-fe4c24c20665","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-672,320],"parameters":{"color":7,"width":384,"height":304,"content":"## Data Processing\nClean HTML and normalize ticket data"},"typeVersion":1},{"id":"afc4ca83-0c95-4b24-8b29-4205eca6439f","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-256,304],"parameters":{"color":7,"width":320,"height":352,"content":"## Translation Layer\nDetect language and translate to English"},"typeVersion":1},{"id":"d27cfcf4-56df-4461-a040-54cdb8022c02","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[96,304],"parameters":{"color":7,"width":352,"height":352,"content":"## AI Classification\nAnalyze sentiment, urgency, and category"},"typeVersion":1},{"id":"65165788-adeb-415a-abb2-e41d5b3877b3","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[480,304],"parameters":{"color":7,"width":304,"height":352,"content":"## Decision Routing\nRoute tickets based on AI recommendation"},"typeVersion":1},{"id":"e3c19d7e-a721-4600-95d0-9af278402289","name":"Sticky Note6","type":"n8n-nodes-base.stickyNote","position":[800,-64],"parameters":{"color":7,"width":624,"height":368,"content":"## Auto Reply Flow\nGenerate AI reply and update CRM"},"typeVersion":1},{"id":"93d853a9-960c-41c8-9150-781e0e91b9f9","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[1456,400],"parameters":{"color":7,"width":304,"height":240,"content":"## Observability\nLog metrics for monitoring and insights"},"typeVersion":1},{"id":"aa5dadcc-1f48-4255-b19a-c58fe5494634","name":"Sticky Note8","type":"n8n-nodes-base.stickyNote","position":[992,528],"parameters":{"color":7,"width":352,"height":336,"content":"## Escalation Flow\nSend high-risk tickets to support team"},"typeVersion":1},{"id":"142cd556-55ec-49b1-aed6-55d71edb5e2b","name":"Sticky Note9","type":"n8n-nodes-base.stickyNote","position":[-2336,288],"parameters":{"width":384,"height":592,"content":"## How it works\nThis workflow automates customer support ticket processing using AI-powered analysis and intelligent routing.\n\nIncoming messages from email or webhook are cleaned, normalized, and translated into English if needed. An AI agent then analyzes each ticket to determine sentiment, urgency, category, and churn risk.\n\nAll actions are logged with observability metrics for monitoring performance and response quality.\n\n## Setup steps\n- Configure IMAP or webhook for incoming tickets\n- Add AI model credentials (Anthropic/OpenAI)\n- Set CRM or helpdesk API endpoint\n- Configure escalation webhook for alerts\n- Set observability/logging endpoint (optional)"},"typeVersion":1}],"pinData":{},"connections":{"Clean HTML":{"main":[[{"node":"Normalize Ticket Data","type":"main","index":0}]]},"Decision Router":{"main":[[{"node":"Draft Reply Generator","type":"main","index":0}],[{"node":"Escalate to Team","type":"main","index":0}]]},"Webhook Trigger":{"main":[[{"node":"Workflow Configuration","type":"main","index":0}]]},"Escalate to Team":{"main":[[{"node":"Log Observability Metrics","type":"main","index":0}]]},"Update CRM/Helpdesk":{"main":[[{"node":"Log Observability Metrics","type":"main","index":0}]]},"Email 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