In the initial phases of large language models (LLMs), users witnessed significant advancements—often tenfold—in reasoning and coding abilities with each model update. However, the pace of these improvements has slowed, leading to more modest enhancements over time. A notable exception remains in the realm of domain-specific intelligence, where substantial advancements continue to emerge. By integrating a model with an organization’s unique data and requirements, companies can achieve these significant leaps in performance. This shift towards AI model customization is becoming essential for organizations aiming to harness the full potential of AI technologies in their respective fields.