ORLANDO, Fla.—Oracle is expanding the capabilities of its life sciences AI data platform with domain-trained AI agents, enhanced analytics tools and natural-language data exploration aimed at accelerating clinical research.
The company launched its Oracle Life Sciences AI Data Platform in January, positioned as a foundational data platform for life sciences. The company said the platform uses generative AI, agentic reasoning and customizable AI agents to help pharmaceutical, medical device and research organizations accelerate drug development, clinical trials, safety monitoring and commercialization efforts.
Building on that effort, the company has expanded the platform, now rebranded as Life Sciences Data Intelligence, with AI and real-world-data capabilities built for life sciences workflows. Research teams can use these capabilities to generate evidence, identify patients earlier in disease progression and support clinical research efforts, the company said.
Announced at the Oracle Health and Life Sciences Summit 2026 this week, the platform enhancements mark the next phase of the software giant's broader life sciences strategy.
Oracle says the Life Sciences Data Intelligence platform combines a customer’s own data with the company's repository of real-world data, which includes over 122 million longitudinal health records. The solution brings these data sources together in one secure platform and uses strong oversight controls to turn de-identified patient data into insights organizations can act on, Oracle executives said. The platform is also built to incorporate additional third-party datasets over time.
The cloud native platform also gives organizations flexibility to scale as data volumes, research needs and AI use cases evolve, the company said.
"Fragmented data and disconnected workflows continue to slow the path to discovery," Seema Verma, executive vice president and general manager, Oracle Health and Life Sciences, said in a statement. "Oracle's unique ability to offer real-world data, along with domain-specific AI tools helps enable researchers to conduct studies and explore data in natural language accelerating research from discovery to commercialization."
Advanced analytics help researchers perform analyses and interpret results with contextual guidance, expanding beyond basic analytics tools, executives said. Connected intelligence workflows also link models, cohorts and insights to help reinforce consistency and repeatable results across the enterprise.
Nimita Limaye, Ph.D., research vice president, life sciences R&D strategy and technology at IDC, said Oracle is bridging the "trust gap" for researchers by "combining governed real-world data, domain-trained AI capabilities and advanced analytics in a single connected environment that turns complex research questions into credible evidence, faster."
"These capabilities reflect exactly the kind of purposeful innovation that the industry needs to make smarter decisions across the therapeutic lifecycle," Limaye said.
The company's life sciences data intelligence platform is designed to work across Oracle’s broader technology ecosystem, including OCI, Oracle Life Sciences, Oracle Fusion Cloud applications and Oracle Health solutions, according to the company.
Oracle is rapidly building out its AI capabilities in healthcare and life sciences with a focus on enterprise-scale, embedded intelligence across clinical, operational and research workflows. It's expected that the company will unveil its latest healthcare AI technology at its Oracle Health and Life Sciences Summit in Orlando this week. A year ago, Oracle Health launched its next-gen EHR, equipped with the latest AI and voice capabilities, designed to be easier for clinicians to navigate. It also recently upgraded its AI-powered clinical agent to help clinicians document faster, streamline professional fee coding and surface relevant patient context. And, the company built out its generative AI capabilities for inpatient nursing workflows.