Chatting with your ERP: A Recipe

This paper presents the design, implementation, and evaluation behind a Large Language Model (LLM) agent that chats with an industrial production-grade ERP system. The agent is capable of interpreting natural language queries and translating them into executable SQL statements, leveraging open-weight LLMs. A novel dual-agent architecture combining reasoning and critique stages was proposed to improve query generation reliability. Keywords: LLMs, Text to SQL, AI Agents 1. Introduction Enterprise Resource Planning (ERP) systems are complex software platforms that integrate and manage core business processes across departments such as manufacturing, logistics, finance, and human resources. These systems are essential for coordinating operations, ensuring data consistency, and enabling data-driven decision-making in industrial environments.