Engineering
Intelligent
Systems
dancodea.tech
Real-time ticket intelligence with zero human bottlenecks
Customer support teams face overwhelming ticket volumes, repetitive inquiries, lost context across multiple customer messages, and slow escalation to engineering or billing departments.
We developed an ultra-fast, intelligent ticket processing engine built with n8n and powered by Groq LLMs. The system automatically inspects incoming support tickets, checks for duplicates, retrieves historical customer interactions, performs sentiment and urgency analysis, drafts personalized replies for human review, and routes notifications to specialized team channels in Slack.
Catches inbound tickets via webhooks and cross-references active records. If a customer follows up on an open issue, it appends a note to the existing ticket, notifies the team, and auto-sends an acknowledgment email via Gmail without creating duplicate clutter.
Fetches prior ticket records and resolution history for the user, combining historical context with the active ticket payload before feeding into the AI model.
High-speed Groq LLMs analyze the ticket for category (Technical, Billing, Account, Bug, Feature Request, Complaint), sentiment (Neutral to Angry), urgency, and priority (Low to Critical) using structured JSON output parsers.
Generates a tailored, policy-grounded draft reply matched to customer sentiment and pre-fills structured internal alerts ready for 1-click human review and dispatch.
A custom router dispatches tickets directly to dedicated department
channels (e.g. #eng-support, #finance-tickets,
#customer-success, #product-ideas), with urgent priority flags for
critical disruptions.
System Architecture & Workflow Execution
End-to-End Automation Pipeline
Complete n8n orchestration connecting webhooks, Google Sheets, Groq AI agents, Slack channels, and Gmail auto-responders.
Stage 1: Intake & Deduplication
Webhook ingests ticket, searches active sheets, appends follow-up notes or logs new records, and retrieves ticket history.
Stage 2: Groq AI Classification
Evaluates context, assigns category & priority tags, and drafts empathetic customer responses in structured JSON format.
Stage 3: Multi-Channel Dispatch
Updates the central database and dispatches actionable alerts directly to specialized team channels in Discord and Slack.
Workflow Testing & Live QA Verification
Live production scenarios were executed to validate duplicate inquiry resolution, customer history linking, sentiment grading, Google Sheets sync, and automated Discord triage dispatches. Below are the verified database records and live channel alerts.
1. Google Sheets Central Ticket Database
Live production spreadsheet capturing incoming ticket IDs, customer accounts, timestamps, subject summaries, and full customer messages.
2. New Ticket Triage & Routing Alert (Slack)
High-priority bug report alert instantly routed to the Engineering team with structured customer profile, priority tags, and issue summary.
3. Duplicate Follow-Up Detection Alert (Slack)
Intelligent change detection identifies follow-up on existing ticket
#TKT-10293, appends a note to the sheet without clutter, and alerts the
channel.
We build custom autonomous AI support agents.