The demand for computational accelerators (GPUs, FPGAs, ASICs, etc.) is growing due to the widening variety of datacenter applications fueled by recent scientific breakthroughs that leverage artificial intelligence (AI). As much as these applications (e.g., cosmology, physics, etc.) have continued to witness record-breaking accuracy in predictive capabilities due to AI widespread influence, the infrastructure and workflow to take these applications out of research labs into production and business use-cases continues to lag. To address these important infrastructural challenges, we present SCAIGATE, a prototype science gateway with a simplified workflow aimed at facilitating model building/validation workflows in large-scale scientific applications.