Semiconducting nanocrystals, recognized by the 2023 Nobel Prize in Chemistry, are versatile materials created solely through chemical synthesis, now integral to functional nanotechnologies. Recent research integrates AI technologies into nanocrystal development using robotic tools to enhance data size and accelerate innovation. Addressing challenges like generating white light from a single material, recent studies focus on two-dimensional structures that spontaneously intercalate organic and inorganic components. While prior investigations mainly used random selection, our experimental approach is based on molecular descriptors of organic cations to study their role in emission characteristics. To this aim, we collected experimental data in real time and uploaded it to a digital platform for data interaction, analysis, and preservation. We first carefully selected primary and secondary amines and established a robust synthetic protocol that is performed at relatively low temperatures and through simple steps. To date, we have prepared more than 50 different layered structures and established seven digital protocols, enabling direct linkage between structural and optical features. Initial correlations indicate that using short organic cations with heteroatoms promotes the synthesis of broadband-emitting layered structures, and changes in the heteroatom position might lead to tunable emission color from blue to white. Such real-time data integration and analysis, which includes sorting, interactive exploration, and data graphical representation, offer new pathways for developing efficient white-emitting structures from a single material, with a broad perspective for other functionalities.