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Automation Case StudyTheoraux Lab · Production tested prototype

AI Customer Support & Escalation System

Build Status

Built and live tested

A message triage system for an e commerce brand that answers only what it can prove from a live spreadsheet, everything else, and anything from a distressed customer, goes straight to a human with the order already looked up.

Results

34

Scripted Messages Run Against the Real System, Real Gemini, Real Spreadsheet, Zero Misfires

3

Channels Unified into One Pipeline

0

Tolerance for a Wrong Automated Answer, by Design

Inside the Build

The Complete Workflow Canvas.

n8n workflow for AI customer support, safety checks, and human escalation
100%
Scroll to zoom · Drag to move · Double click to zoom
Overviewn8n · Redacted workflow view

Scenario Replay

See How the Logic Responds.

Choose a real world situation to follow the path from trigger to outcome.

Trigger

“Where is order #1048?”

01

Capture message

02

Load order data

03

Run safety gates

04

Send verified reply

Outcome

The customer gets a fast answer backed by a live spreadsheet row.

Operational Change

What Changes After Automation.

Routine replies

Before

Repeated manually in a shared inbox

Automated

Answered in seconds from verified data

Urgent messages

Before

Wait behind routine questions

Automated

Escalated before intent handling

Agent context

Before

Order details searched by hand

Automated

Customer and order context preloaded

The Challenge

A growing online seller had one shared inbox for Messenger, Instagram, and web form messages, and staff were answering the same routine questions dozens of times a day while urgent complaints sometimes waited behind them in the queue.

The System

We built an n8n decision engine with six ordered gates that only answers when it can point to a live spreadsheet row. Anything urgent or unproven goes to a human inbox with the order already pulled up.

Guardrails

Distress and urgency are checked first.

Replies need a matching source record.

Unsupported requests fall back to a human.