Immunai - Decoding immunity

Immunai is an AI-powered immunology platform that decodes complex immune data to accelerate drug discovery and biomarker identification. By integrating single-cell sequencing, mass cytometry, and other high-throughput technologies, it provides researchers free access to curated datasets, interactive visualizations, and pre-trained machine learning models for systematic analysis of immune cell populations and signaling pathways. Unlike traditional bioinformatics tools, Immunai’s end-to-end AI pipeline builds high-resolution immune cell atlases from multi-omics data, revealing dynamic immune microenvironments across diseases. Key differentiators include deep data integration from public and proprietary sources covering oncology, autoimmunity, and infectious diseases, plus model interpretability that explains why specific targets or biomarkers hold potential. Users can also upload their own data for joint analysis. Typical users are drug discovery scientists, clinical researchers, and immunology labs. Use cases range from predicting immune checkpoint inhibitor responses and identifying neoantigens in cancer, to characterizing pathogenic T cell clones in autoimmune diseases and analyzing vaccine-induced immune memory. Pharmaceutical companies employ Immunai for early target validation and safety assessment, while academics leverage its free resources to validate findings or generate new hypotheses. Backed by peer-reviewed deep learning algorithms and a large immune repertoire database, Immunai has earned collaborations with leading pharma firms like Novartis and Regeneron. Maintained by a multidisciplinary team of immunologists, computational biologists, and clinicians, it continues to advance precision immunology from concept to practice, earning strong trust in the global biomedical research community.