Introducing Axlerod: An LLM-based Chatbot for Assisting Independent Insurance Agents

• URL: http://arxiv.org/abs/2601.09715v1
• Date: Wed, 24 Dec 2025 15:31:59 GMT
• Title: Introducing Axlerod: An LLM-based Chatbot for Assisting Independent Insurance Agents
• Authors: Adam Bradley, John Hastings, Khandaker Mamun Ahmed,
• Abstract summary: The insurance industry is undergoing a paradigm shift through the adoption of artificial intelligence (AI) technologies.<n>This paper presents the design, implementation, and empirical evaluation of Axlerod, an AI-powered conversational interface designed to improve the operational efficiency of independent insurance agents.
• Score: 0.20999222360659608
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The insurance industry is undergoing a paradigm shift through the adoption of artificial intelligence (AI) technologies, particularly in the realm of intelligent conversational agents. Chatbots have evolved into sophisticated AI-driven systems capable of automating complex workflows, including policy recommendation and claims triage, while simultaneously enabling dynamic, context-aware user engagement. This paper presents the design, implementation, and empirical evaluation of Axlerod, an AI-powered conversational interface designed to improve the operational efficiency of independent insurance agents. Leveraging natural language processing (NLP), retrieval-augmented generation (RAG), and domain-specific knowledge integration, Axlerod demonstrates robust capabilities in parsing user intent, accessing structured policy databases, and delivering real-time, contextually relevant responses. Experimental results underscore Axlerod's effectiveness, achieving an overall accuracy of 93.18% in policy retrieval tasks while reducing the average search time by 2.42 seconds. This work contributes to the growing body of research on enterprise-grade AI applications in insurtech, with a particular focus on agent-assistive rather than consumer-facing architectures.

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