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The presented Natural Language User Interface (NLUI) enables users with limited expertise in machine learning and data science to harness prescriptive analytics in their decision-making processes without requiring intensive compute. We present an agent capable of function calling, maintaining faithful, interactive, and dynamic conversations, and supporting new domains.","abstract_html":"Despite advancements in causal inference and prescriptive AI, its adoption in enterprise settings remains hindered primarily due to its complexity and lack of interpretability. This work at the MIT-IBM Watson AI Lab focuses on extending upon the proof-of-concept agent, PrecAIse, by designing a domain-adaptable conversational agent equipped with a suite of causal and prescriptive tools. The objective is to make advanced, novel causal inference and prescriptive tools widely accessible through natural language interactions. 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