AI-powered customer support automation that classifies incoming requests, assigns priorities, routes tickets, and monitors response deadlines.

Industry: EdTech / Online Exam Preparation

1. Context

ScoreUp is an EdTech business scenario with a two-person support team handling approximately 700 requests per month, rising to 1,500 during peak periods.

Around 55% of requests concern lesson access, broken recording links, and homework navigation. This represents approximately 385 routine access-related requests per month at average volume.

The project explores how AI automation can help a small support team manage this workload more efficiently.

2. Problem

When urgent student requests get buried in a crowded inbox, delayed support can disrupt their learning experience.

A small support team handling hundreds of monthly requests faces three key challenges:

• Repetitive manual work: Employees must review, categorize, prioritize, and assign incoming emails.
• Missed priorities: Critical access problems can be mixed with routine questions or spam.
• Poor deadline visibility: Without systematic SLA monitoring, overdue tickets may remain unresolved without escalation.

The goal: Automate ticket classification and routing while giving the support team greater visibility into urgent and overdue requests.

3. Solution

I built an AI-powered customer support system using two connected n8n workflow branches.

1. AI Ticket Classification & Routing

When a new email arrives, the system:

1. Analyzes the request using OpenAI.
2. Assigns a ticket category, priority, responsible agent, and customer sentiment.
3. Filters out spam.