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AI-Assisted Support Chatbot Prototype

A first-line AI responder trained on real ticket history, built to catch the questions that shouldn't need a human.

AIAutomationServiceNow
Private — built in an employer environment, details on request24/7 Coverage

The problem

A 3-person Service Desk supporting ~1,500 users was drowning in repetitive, common-pattern tickets — password resets, access requests, known-issue troubleshooting — while running at roughly 75% of designed headcount. Every hour spent on a question that had already been answered a hundred times was an hour not spent on the tickets that actually needed a human.

The solution

I built a chatbot prototype trained on historical ticket data, existing knowledge base articles, and recurring-issue patterns mined from the ITSM system. It handles common requests automatically and around the clock, and surfaces emerging issue clusters back to the team before they escalate.

Impact

  • 24/7 automated coverage for the most common request types
  • Meaningfully reduced administrative load on a 3-person team
  • Faster identification of recurring incidents before they became trends

How it works

Architecture / Flow
01Historical tickets + KB articles ingested and categorized
02Pattern analysis surfaces the highest-frequency, lowest-complexity request types
03Chatbot handles matched requests directly; ambiguous requests route to a live technician
04Unresolved or novel patterns feed back into trend analysis for proactive fixes

Lessons learned

  • The highest-leverage automation isn't the flashiest ticket — it's the one that repeats the most.
  • A chatbot is only as good as the knowledge base underneath it; cleaning up KB content was half the project.
  • Transparency with the team mattered — this was framed as taking work off their plate, not replacing them, which is exactly what happened.
Technologies
Ticket data analysisKnowledge base integrationPattern/trend detectionLLM prompting