Building Decision Agents with LLMs and Machine Learning Models

Explore how to design and implement decision agents that effectively combine Large Language Models (LLMs) with machine learning models for automated decision-making systems. Learn from Blue Polaris Executive Partner James Taylor as he demonstrates the integration of Decision Model and Notation (DMN) with LLMs and ML models to create transparent, scalable, and efficient decision-making frameworks. Discover the complementary roles that decision agents play alongside LLMs in automation workflows, understanding how these technologies work together to enable robust AI systems. Gain insights into building decision agents that maintain transparency while delivering efficient automated solutions, and understand the architectural considerations for implementing these hybrid approaches in real-world applications.