Beyond Prompt-Heavy LLMs: How Small Language Models and Statistical Models Enable Reliable Decision-Making

In high-stakes domains like finance, bigger models and longer prompts are not always the path to better decisions. While large language models are powerful for language understanding, enterprise decision-making often requires precision, interpretability, calibration, and risk controls that prompt-heavy approaches alone cannot provide. This session explores how small language models can be combined with statistical and financial models to create more reliable, modular, and production-ready AI systems. Attendees will learn how to separate language understanding from decision logic, route tasks across specialized models, and design workflows that support human oversight and model governance. Join this talk to understand how organizations can move beyond generic LLM prototypes toward controlled AI systems that make decision support safer, faster, and more trustworthy.