-Integrate transcriptomics, proteomics, metabolomics, and histology layers
-Offer custom annotation, segmentation, and quantification of TME components
-Provide insights into immune cell localization, phenotype, and functional states
-Characterize DC (Dendritic Cell), TAM (Tumor Associated Macrophage), CAF( Cancer Associated Fibroblast), and macrophage crosstalk using spatial data
-Identify immunosuppressive niches and therapeutic resistance zones
-Generate actionable maps for drug targeting or combination therapy design
-Simulate therapeutic interventions (e.g., checkpoint inhibitors, STING agonists) in silico
-Predict response based on TME composition and spatial dynamics
-Offer preclinical validation support for biotech or pharma partners
-Use AI-enhanced spatial omics to identify predictive biomarkers
-Focus on agnostic patient stratification across PD1/L1 and combination regimens
-Provide companion diagnostic development support
-Collaborate with academic labs or startups needing spatial omics expertise
-Offer tailored project design, data generation, and interpretation