Table of Contents

For enterprise applications, "boring" AI is the ideal, meaning a system that is predictable, reliable, accurate, and auditable. This is difficult to achieve because the probabilistic nature of LLMs causes errors to compound in complex, multi-step workflows, reducing overall accuracy. The proposed solution is a full-stack approach that includes foundation models optimized for instruction-following, structured Retrieval-Augmented Generation (RAG), and an orchestration framework like AI21 Maestro to enforce rules. By deliberately engineering for reliability over unpredictable creativity, these systems build trust and become suitable for critical business processes.