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Case Study

Dartmouth College : 24/7 AI Helpdesk Assistant for Campus-Wide IT Support


Education / EdTech

Dartmouth College – AI-Powered IT Helpdesk Assistant for Education

Dartmouth College deployed our AI chatbot to automate IT support for students, faculty, and administrative staff. Built using advanced NLP models, the assistant handles everything from password resets and Wi-Fi issues to software installation queries. It integrates seamlessly with the college’s ticketing system and learns from historical tickets to offer faster resolutions. The bot is active 24/7, ensuring zero downtime in service availability. With our AI solution, Dartmouth reduced wait times, improved ticket deflection, and empowered its helpdesk to focus on complex tech needs.

Project Overview

  • Client: Dartmouth College (Ivy League institution with 6,600+ students and 900+ faculty)
  • Challenge: High IT ticket volume + long resolution times for common tech issues
  • Goal: Build an AI chatbot to:
    • Resolve basic IT issues autonomously (e.g., Wi-Fi, login, software setup)
    • Deflect repetitive support tickets from helpdesk staff
    • Ensure uninterrupted support across time zones and schedules
  • Team: 7 (2 NLP Engineers, 2 Integration Devs, 1 ITSM Consultant, 1 QA Analyst, 1 PM)
  • Timeline: 4 months (Build → Campus Beta → Full Deployment)

“With GenX, we’ve moved beyond basic chatbots to create an intelligent support system that scales with our growing student population.”

Director of Campus IT Services, Dartmouth College

The Challenge

Critical Pain Points:
  • IT teams were overwhelmed by repetitive, low-complexity queries
  • Delayed response times during peak academic periods frustrated users
  • Ticketing system lacked AI capabilities to auto-resolve or triage tickets
Technical Hurdles:
  • Training the NLP engine on domain-specific campus terminology and tech stack
  • Connecting to Dartmouth's specialized ITSM platform and knowledge repository
  • Maintaining data privacy and FERPA compliance for sensitive queries

Tech Stack

Component Technologies
NLP & Chatbot Framework Dialogflow CX, BERT, spaCy, GPT-4 fallback
Backend & Integration Node.js, Firebase, Google Cloud Functions
Ticketing System Integration ServiceNow APIs, REST/GraphQL
Frontend Channels React, Slack SDK, Teams SDK, Intranet Widgets
Security & Monitoring Google IAM, Datadog, FERPA Compliance Logging

Key Innovations

The assistant resolved routine IT queries like Wi-Fi and password resets 24/7. It learned from past tickets to suggest instant solutions. Staff could focus on complex issues as ticket volume dropped.

24/7 Self-Service IT Resolution

  • Resolved most queries without human intervention, anytime

Result: 62% of IT tickets fully deflected within the first month

Smart Learning from Ticket Histories

  • Identified trending tech issues and adapted responses accordingly

Result: 29% faster response accuracy over the first 10K interactions

Cross-Channel Campus Integration

  • Available through web, mobile, Slack, Teams, and kiosks

Result: 48% increase in student engagement with IT support

Our AI/ML Architecture

Core Models

  • Campus NLP Engine:
    • Fine-tuned BERT-based model trained on Dartmouth-specific queries
    • Handles over 120 classified IT intents (from “forgot password” to “install MATLAB”)
  • Auto-Triage + Ticket Escalation System:
    • Deflects tickets by resolving directly or routing to appropriate support tiers
    • Learns from closed ticket patterns for improved intent detection
  • Knowledge Feedback Loop:
    • Uses unresolved queries to update and expand the knowledge base
    • Human-in-the-loop approval before publishing AI-suggested content

Data Pipeline

  • Sources
    • Historical helpdesk tickets, knowledge base articles, FAQ repositories
    • Real-time user queries and bot feedback sessions
  • Processing: GCP Functions + Dialogflow CX + Firestore + Elastic KB sync

Integration Layer

  • Integrated with ServiceNow ITSM and campus SSO
  • Real-time Slack and Microsoft Teams chatbot support
  • Browser, mobile & kiosk integration

Quantified Impact

Avg. First Response Time (IT support)
Before AI

11.3 min

After AI

1.4 min

Ticket Deflection Rate
Before AI

0%

After AI

62%

Avg. Resolution Time (Tier-1 issues)
Before AI

4.7 hours

After AI

26 minutes

Ticket Volume per Helpdesk Agent
Before AI

180/month

After AI

75/month

User Satisfaction Score (IT feedback)
Before AI

76/100

After AI

91/100

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