Oracle is expanding its life sciences AI data platform with domain-trained AI agents, enhanced analytics and natural-language data exploration. The platform, now called Life Sciences Data Intelligence, builds on the Oracle Life Sciences AI Data Platform launched earlier this year. It combines a customer’s own data with Oracle’s repository of real-world data, which includes more than 122 million longitudinal health records, under strong oversight controls. Researchers can use natural-language queries to analyse data, build and refine patient cohorts and automate complex research workflows without extensive coding. Features guide common activities such as cohort discovery, clinical trial recruitment, site optimisation, health economics and outcomes research, market access research and evidence generation. The tools provide traceable reasoning and transparent audit trails so users can validate underlying evidence.
Oracle is expanding its life sciences AI data platform with domain-trained AI agents, enhanced analytics and natural-language data exploration. The platform, now called Life Sciences Data Intelligence, builds on the Oracle Life Sciences AI Data Platform launched earlier this year. It combines a customer’s own data with Oracle’s repository of real-world data, which includes more than 122 million longitudinal health records, under strong oversight controls. Researchers can use natural-language queries to analyse data, build and refine patient cohorts and automate complex research workflows without extensive coding. Features guide common activities such as cohort discovery, clinical trial recruitment, site optimisation, health economics and outcomes research, market access research and evidence generation. The tools provide traceable reasoning and transparent audit trails so users can validate underlying evidence.