Large Language Models (LLMs) are increasingly used to ensure compliance with regulatory standards, legal contracts, product and service standards, and internal guidelines. These models analyze vast…

hantian pang

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Large Language Models (LLMs) have shown significant improvements in ensuring compliance in medical marketing and sales calls. Salus AI improved LLM accuracy from 80% to 95-100% using five key techniques: prompt engineering and design, pre-processing input text for speaker separation, implementing Retrieval-Augmented Generation (RAG), and fine-tuning models. These optimizations demonstrated that LLMs can outperform traditional rule-based compliance solutions in monitoring regulatory adherence during calls.

Best practices for LLM optimization for call and message compliance: prompt engineering, RAG, and fine-tuning

Overall Findings: Our use of Retrieval-Augmented Generation (RAG) had for the most part a small effect on prompt performance, likely due to diminishing returns after significant model improvements prior to its use. However, we did reduce LLM compute costs by up to 80%.

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