Oracle has introduced the Oracle Life Sciences AI Data Platform, a cloud-native data and analytics platform designed to consolidate clinical, research and commercial datasets. With this, the company aims to accelerate the delivery of medical treatments by providing an interoperable ecosystem that connects research workflows with real-world medical data.
The platform uses generative and agentic artificial intelligence (AI) to support research and evidence generation for life sciences companies.
Seema Verma, executive vice president and general manager, Oracle Health and Life Sciences, said, “Fragmented, inconsistent data is a major barrier to progress, holding back life sciences organizations from delivering the medical breakthroughs that could transform and even save lives.”
The Oracle Life Sciences AI Data Platform is intended to unify these datasets within a single cloud-based environment. It combines first- and third-party data sources with analytics and AI-driven capabilities, the company said.
Using Data at Scale Across the Research Lifecycle
By integrating massive datasets, including over 129 million de-identified patient records, the system is designed to reduce data fragmentation that often hinders drug development and clinical trials.
“Oracle Life Sciences AI Data Platform unifies and intelligently organizes data and employs AI and advanced analytics to reveal deep insights that are often not possible with humans alone,” Verma explained.
The platform utilizes generative AI and autonomous agents to automate complex data analysis, allowing researchers to uncover deep insights and generate evidence faster. These intelligent agents can perform specialized tasks such as monitoring drug safety, identifying new therapeutic uses for existing labels, and supporting regulatory filings.
Delivered as a managed cloud service on Oracle Cloud Infrastructure (OCI), the platform supports automated data ingestion, normalization and governance, and provides a unified data layer for analytics and AI services. On top of this data foundation, researchers can ask questions in natural language, while AI agents interpret requests, suggest analyses and operate within defined controls.
Oracle said the platform can enable life sciences organizations to scale their research capabilities while maintaining full transparency and data integrity.
The Oracle Life Sciences AI Data Platform also integrates with Oracle’s broader cloud application portfolio, including Oracle Fusion Cloud Supply Chain Management and Oracle Fusion Cloud Sales, enabling shared data and operational alignment across research and downstream business functions.
What This Means for ERP Insiders
ERP platforms are increasingly connected to industry-specific data environments. The integration of Oracle’s life sciences data platform with Fusion Cloud applications reflects how ERP systems are becoming part of broader, vertical-focused operational architectures.
Unified cloud data layers are becoming core enterprise assets. The platform reflects a broader shift toward bringing enterprise data into a single, governed environment so it can support analytics and AI beyond traditional transaction reporting.
AI capabilities are moving closer to the data layer. Oracle’s approach illustrates how AI is being positioned as an embedded platform capability, built into data and workflow environments rather than being delivered as standalone tools.
