A new pattern for integrating Large Language Models (LLMs) with Enterprise Resource Planning (ERP) systems focuses on safety by separating read and write operations. The proposed method allows LLMs to read data directly from the ERP but requires all proposed changes to be submitted as structured proposals to an approval queue. A human approver, using existing authorization rules, then reviews, edits, or rejects these proposals before a separate, non-LLM service executes approved changes. This approach ensures the ERP remains the system of record, maintains auditability, and allows for continuous improvement by feeding rejection reasons back into the LLM's context. AI
IMPACT Provides a secure framework for LLMs to interact with critical business data, enabling broader adoption in enterprise resource planning.
RANK_REASON Describes a specific technical pattern for integrating an existing technology (LLM) with another (ERP), focusing on practical implementation and safety.
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