In a previous article, we focused on the capability that turns large language models (LLMs) from general-purpose tools into instruments of research through domain-specific customization. Fine-tuned models are how research teams encode domain expertise, institutional research, and reasoning patterns into systems that can help accelerate discovery rather than simply assist it.But customized models are only one half of the equation. For those models to become useful at institutional scale, they need a platform that can be used to train, serve, govern access to, and integrate them into the broader