IT Service Desk

Lean, Scalable, Always-On IT Support

AI service desk software that detects urgency, resolves L1 and L2 tickets, and integrates fully with the ServiceNow and Ivanti consoles agents already work in.

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Summarise this with

Industry
Legal / Estate Planning
Region
California, USA
Company size
500+ employees
Engagement
12 months

01 Drag to explore

Inside the Platform

  • Seed image culture-5
    Escalation handoff
  • Two of the team on a boat at the harbour
    Role controls
  • Seed image story-2
    Sentiment monitor
  • A developer at their desk, two screens of code
    Admin analytics
  • Three of the team on a rooftop, mid-Jenga
    Chat copilot
  • Seed image story-3
    Intent routing
  • The whole company on the office steps
    Knowledge lookup
  • The karting team lined up in race suits
    Ticket automation

02 Project outcome

Tangible Wins Across Every Metric

Speed. Accuracy. Deflection. Delivered.

50%
Time saved Routine queries resolved without an agent
95%
Answer accuracy GPT-4o over vectorised knowledge retrieval
40%
Interaction cut Helpdesk effort reduced across the board
60%
Ticket automation Auto-generated and routed with SLA labels

03 The brief

Client & Industry Overview

The client needed a chatbot to handle growing ticket volumes, reduce L1/L2 load, and improve SLA compliance. Their IT helpdesk was overburdened by routine queries like access issues, software installation, or system errors, all of which delayed actual incident handling.

We built an AI copilot powered by GPT-4o, vectorized knowledge retrieval, and ELSER for ElasticSearch accuracy. It resolved most issues instantly, auto-generated L3 tickets via ServiceNow/Ivanti, and reduced helpdesk effort by 40%.

04 What made this complex

Not Every AI is IT-Aware

Five places where a general-purpose assistant would have quietly got it wrong.

  1. Ambiguous Query Intents

    Phrases like 'system error' needed downstream filters to sort between device issues, VPN errors, or Outlook crashes.

  2. Ticket Routing Loops

    Improper retry logic in ServiceNow API led to duplicate or recursive ticket entries under high request loads.

  3. Delayed Sentiment Triggers

    User frustration detection often missed the escalation window due to NLP lag in emotion scoring mid-conversation.

  4. Vector Index Drift

    Knowledge base updates weren't reflected live, outdated embeddings caused poor context recall from document vectors.

  5. Role-Based Prompt Conflicts

    Custom prompts didn't respect all SSO permissions, unauthorized responses occasionally bypassed expected scope controls.

05 What we did to fix it

Engineering Through the Complexity

Five decisions that turned a promising demo into something a 500-person helpdesk could stand behind.

Talk Through Your Build

  1. Intent Mapping Optimization

    We retrained embeddings with scenario-specific data and added decision tree logic to route ambiguous phrases like "system down" or "email blocked" to precise intent categories.

  2. Structured Knowledge Training

    We built a standard content template for KB ingestion, enabling clean vectorization and predictable embedding generation across Elastic + GPT-4o pipeline for consistent document understanding.

  3. Reliable Agent Escalation Sync

    We implemented a transcript buffer and pre-handoff state validation to ensure full user context transferred properly to Amazon Connect, preventing dropped session issues.

  4. Role-Based Prompt Enforcement

    Prompt templates dynamically changed based on SSO role payloads. Access-controlled KB filters were enforced through backend logic before response generation even triggered.

  5. Noise Reduction in Elastic

    ELSER model was fine-tuned with domain-specific token weights to suppress keyword pollution and improve high-confidence clause retrieval within mixed-topic documents.

06 Features that cut workload

Built for Real ITSM Challenges

Nine capabilities the copilot shipped with.

  • Intent-Based Query Detection

  • Vector-Based Knowledge Lookup

  • L1 and L2 Issue Resolution

  • ELSER-Powered Search Precision

  • ServiceNow & Ivanti Sync

  • Amazon Connect Handoff Integration

  • SSO with Role Control

  • Sentiment-Based Escalation Logic

  • Analytics Dashboard for Admins

07 backbone of the IT copilot

Fast, Contextual, & Always On

  1. Interface

    • React UI framework
    • Tailwind CSS Styling

  2. Services & APIs

    • Nest.js API framework
    • Python Services and ML

  3. Data & Retrieval

    • PostgreSQL Primary database
    • Elasticsearch Vector + ELSER search
    • OpenAI GPT-4o reasoning

  4. Cloud & Ops

    • Azure Cloud hosting
    • HighLevel Marketing ops

08 What that felt like

Speed. Accuracy. Deflection. Delivered.

The five things users noticed once the copilot was in front of them.

  1. Instant Knowledge Retrieval

    Sub-3 second replies with GPT + vector search provided users with accurate solutions.

  2. High-Level Deflection Rate

    Over 70% of interactions ended without agent support.

  3. SLA-Ready Ticket Automation

    Auto-generated tickets respected issue urgency and routed with accurate SLA labels.

  4. Semantic Consistency Maintained

    Structured multi-turn prompts avoided off-topic replies.

  5. Role-Tailored Chat Responses

    RBAC logic kept responses scoped to user role.

09 Client testimonial

I'm impressed by KoderTal's responsiveness and clean codebase.

KoderTal's efforts have yielded a production-ready SaaS platform for custom content generation. The team does excellent work and saves the client six months of development work. Moreover, KoderTal has delivered on time and suggested ideas beyond the scope to enhance UX and save time on development.

Chris Marin Business Owner

Clutch 5.0

10 Why choose us

Why Teams Trust KoderTal

We build systems that stay simple on the surface and strong underneath, so adoption is easy and operations stay reliable.

Our team possesses deep expertise in AI and LLM technologies, delivering robust, scalable solutions tailored to meet diverse industry needs.

We offer AI and LLM solutions customized for various industries, addressing specific challenges and driving measurable outcomes for each sector.

Our AI development process is built on a proven methodology, ensuring consistent, high-quality results delivered on time and within budget.

With teams across multiple regions, we ensure global delivery of AI solutions, providing reliable, scalable results tailored to your business's unique requirements.

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12 Get started

Ready to Build with KoderTal's AI Experts?

Connect with our experts today to discuss your development goals, requirements, and the best approach for your AI project.

  • 2451 West Grapevine Mills Circle, Grapevine, TX 76051 · USA
  • hello@kodertal.com
  • Reply within 1 business day, 24/7 support once live

Covered by an NDA on request. We never share project details.

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