This paper reveals the design of a dual-agent LLM that translates natural language into SQL for ERP queries, suggesting improvements in reliability.
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.
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Gómez et al. (2025) studied this question.
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