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AI Support AgentE-commerce
E-commerce · Micromobility

AI Support Agent for an E-commerce Platform

A micromobility rental platform was drowning in thousands of repetitive tickets. We deployed an AI agent that processes tickets, resolves standard questions, and escalates complex cases to operators.

11 644
tickets processed
26.5 min
avg response time
41.5%
closed by bot
4 689
escalated / week (down)
GPT-4on8nZendeskPostgreSQLPython
The challenge

The support team received thousands of tickets a month — mostly repetitive: order status, breakdowns, returns, payments. Operators spent most of their time copy-pasting answers, response time spiked at peak hours, and complex cases got lost in the shared queue.

Our approach
  1. 01

    Ticket audit

    We analyzed ticket history and isolated the top intents that cover most of the queue.

  2. 02

    Knowledge base + classification

    We assembled answers into a structured knowledge base and taught the agent to detect ticket intent.

  3. 03

    Routing & escalation

    We defined rules: standard cases are closed by the bot, complex ones go to an operator with full context.

  4. 04

    Launch & tuning

    We launched on part of the traffic, collected errors, and iteratively raised accuracy.

The solution

A GPT-4o agent inside an n8n pipeline is connected to Zendesk. Each new ticket is classified by intent, the agent searches a PostgreSQL knowledge base and drafts a reply; complex or emotional cases are auto-escalated to an operator with a summary and references.

Results
11 644
tickets processed
26.5 min
avg response time
41.5%
closed by bot
4 689
escalated / week (down)

First working result in 2 weeks; full rollout within a month.

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