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This study introduces Enterprise Brain (EB), a general decision support system framework designed to address the interpretation bottleneck in enterprise data analytics. The EB system provides a scalable approach, integrating deep reinforcement learning (DRL) and large language models (LLMs) to provide contextualized insights from complex business data. The system interprets user queries, leverages relevant DRL models to analyze data, and explains the responses using the LLM. A continuous learning mechanism updates DRL models on new data from user interactions and inputs. In a case study of merger evaluation, EB demonstrates a significant reduction in time-to-decision by providing specific, data-driven answers.
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