Abstract Background: Spatial transcriptomics (ST) technology maps gene expression within tissue structures, offering unprecedented insights into tissue organization and cellular interactions. Analyzing these complex datasets, however, remains a significant bottleneck. Current workflows demand specialized, multi-domain expertise and rely on heavy manual intervention, an expertise barrier that hinders the rapid translation of data into biological insights. Method: To address this challenge, we dev