LLM fine-tuning support automation hero

NDA project

Custom LLM Fine-Tuning for Support Automation

Fine-tuned language model trained on company data to automate first-line customer support responses.

Industry

SaaS / Customer Support

Country

USA

Platform

Web / API

Partnership model

Turnkey Product Development

Client Context

The client handled a high volume of support requests across multiple channels — email, chat, and in-app tickets. A large portion of these requests were repetitive: account setup, pricing questions, feature explanations, basic troubleshooting. The team had already experimented with generic AI tools to speed things up. In practice:

  • answers were often technically correct, but not relevant to the user’s situation
  • tone didn’t match the brand — too generic or too "robotic"
  • responses sometimes included incorrect or made-up details (hallucinations)

Challenge

  • Operational Pain: Support teams overloaded with repetitive questions

  • Technical Limitation: Out-of-the-box models didn’t understand product context

  • Business Risk: Poor responses → customer frustration

LLM fine-tuning support demo

Solution

We fine-tuned a language model on:

  • support tickets
  • internal documentation
  • product knowledge base

Added guardrails and structured prompts to control output quality.
The model was integrated into the support workflow as a response assistant.

Team

  • 2x

    AI
    Engineer

  • 1x

    QA
    Engineer

  • 1x

    Backend Developer

  • 1x

    Project Manager

  • 2x

    AI
    Engineer

  • 1x

    QA
    Engineer

  • 1x

    Backend Developer

  • 1x

    Project Manager

What We Delivered

  • Fine-tuned LLM on domain-specific data

  • Prompt and response control system

  • Integration with support tools

  • Evaluation and feedback loop

Timeline & Cost

Full breakdown is available under NDA

Discovery & Planning: 3–4 weeks

Architecture & Design: 4–6 weeks

Development: 4–6 months

Total Timeline: ~6–8 months

Discovery Phase: $25K–$40K

Design & Architecture: $40K–$70K

Development: $180K–$320K

Total Investment: $300K–$450K

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Impact & Results

Operational:

Reduced load on support teams

Technical:

More accurate and context-aware responses

Business:

Faster response times and improved customer experience

Technology Stack

  • Python
  • OpenAI
  • HuggingFace
  • LangChain
  • FastAPI
  • and more...

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