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Research and discovery teams still sift through genomic data, literature, and knowledge graphs largely by hand, searching for the signal that points to a new target or a mutation worth pursuing. A researcher can spend more time reading than discovering.
AI reads at a scale no team can match. Predictive models flag gene mutations and drug discovery signals from genomic and clinical data. Generative AI surfaces the relevant finding from literature and knowledge graphs instead of a manual search. Agents keep signal detection running as new data and papers arrive. Your researchers spend their time on the finding, not the search, running in your own environment.