CASE STUDY: RETAIL & ECOMMERCE

Recovering 40% of OpEx via Autonomous Support Agents

How a specialized AI Agent architecture handled 15,200 support tickets in November, reducing human workload by 70%.

40%
OpEx Savings
24/7
Coverage
<30s
Response
5
Languages

The Problem

During Black Friday preparation, support volume spiked 10x. The existing team of 4 agents could not maintain 24/7 coverage, leading to 48-hour response delays and lost sales.

  • Overflow of repetitive "Where is my order?" (WISMO) tickets.
  • Lost revenue from after-hours international traffic.
  • High cost of hiring temporary holiday staff.

The Architecture

We deployed a 3-Agent Cluster orchestrated on n8n (Self-Hosted).

Architecture Highlights:

  • Triage Node Analyzing intent & sentiment via GPT-4o-mini before routing.
  • Action Node Safe-querying Shopify API to check order status.
  • Response Node Drafting on-brand replies in native language.

The Results

In the first 30 days, the system auto-resolved 72% of L1 inquiries. Key Result: The support team DID NOT hire temp staff for Q4, saving $12k/month immediately.