A major call center application has replaced its automatic ticket routing service with a new system using a locally-hosted, fine-tuned Large Language Model (LLM). This LLM, Llama 3.2 1B, was fine-tuned in less than 20 minutes using the Unsloth framework, reducing its size to under 1GB. The model now efficiently classifies support tickets into categories like packaging and shipping, product defects, or general dissatisfaction. The service, built with Rust and Axum, processes tickets in about 2 seconds on CPU hardware, demonstrating that even small, fine-tuned models can perform complex tasks with minimal resources. This approach highlights the potential of using lean AI agents to enhance specific functions within larger systems, offering a cost-effective and scalable solution for AI integration.
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