n8n Support SLA Monitoring with AI Classification

n8n Support SLA Monitoring with AI Classification & Alerts

Problem Support tickets arrived from chat and email in different formats. The team needed a reliable way to track response deadlines, detect VIP breaches, and understand ticket volume by category.

Solution / Workflow I built an n8n workflow that normalizes both sources, classifies ticket category and priority, calculates SLA status, and separates on-time, pending, and breached requests. VIP breaches trigger individual Telegram alerts, while category statistics are stored separately.

What I built • Multi-source ticket normalization • Priority-based SLA calculation • Optional AI classification with explicit parsing and validation • VIP breach alerts and category summaries • Seven-ticket QA set and error review

Tech n8n, JavaScript, Groq API, Telegram, Data Tables

Result The workflow processed all seven test tickets, identified two VIP breaches, classified category correctly in 7/7 cases, and matched priority in 5/7. The two mismatches revealed a real AI tendency to overrate emotionally worded requests, so AI output remains reviewable instead of blindly trusted.

Portfolio demo built with anonymized test data.