Domain Adaptable Prescriptive AI Agent for Enterprise

Abstract

Despite advancements in causal inference and prescriptive analytics, its adoption in enterprise settings remains hindered due to its technical complexity. Many users lack the necessary knowledge and appropriate tools to effectively leverage these technologies. This work focuses on developing a proof-of-concept, PrecAIse, a domain-adaptable conversational agent equipped with a suite of causal and prescriptive tools to help enterprise users make better business decisions. The objective is to make advanced, novel causal inference and prescriptive tools widely accessible through natural language interactions. The presented Natural Language User Interface (NLUI) enables users with limited expertise in causal ML and optimization to harness prescriptive analytics in their decision-making processes without requiring intensive computing resources. We present an agent capable of function calling, maintaining faithful, interactive, and dynamic conversations, and supporting new domains.