An autonomous multi-agent system that classifies, resolves, and escalates support tickets in under 30 seconds. Built for enterprise teams handling 1,000+ tickets per month.
Based on an enterprise team handling 10,000 support tickets per month.
| Metric | Before | After | Change |
|---|---|---|---|
| Monthly support cost | $12,000 | $2,800 | -77% |
| Average response time | 4-8 hours | Under 30 seconds | -99% |
| Tickets requiring human agents | 100% | 30-40% | -65% |
| Agent hours consumed per week | 250+ hours | 60-80 hours | -70% |
| Cost per ticket | $1.20 | $0.08-$0.36 | -80% |
Each agent handles one job. LangGraph orchestrates the flow with conditional routing between auto-resolution and human escalation.
Reads every incoming ticket and outputs category, urgency score (1-5), complexity label, and a confidence score. Powered by GPT-4o-mini.
Generates a personalized, context-aware reply for every auto-resolvable ticket. Pulls customer history from Supabase to avoid generic responses.
Routes low-confidence or high-complexity tickets to human agents with a full structured context summary so they never start from scratch.
Tracks auto-resolution rate, average response time, escalation rate per category, and cost per ticket in real time.
Every component is containerized, monitored, and deployable with zero-downtime redeploys via Railway.
Each project targets a specific enterprise workflow with measurable ROI and a production deployment.
Autonomous outreach, qualification, and response agent for WhatsApp at enterprise scale.
View Case Study →Multi-source lead enrichment, scoring, and outreach automation for B2B sales pipelines.
View Case Study →Autonomous ticket classification, resolution, and escalation system for high-volume support teams.
Request Details →This system is available as a fully managed, custom deployment for your business. Built, documented, and handed over production-ready.