Elsevier, a global provider of advanced information and decision-support solutions in science and healthcare, has introduced LeapSpace, a next-generation AI-supported workspace developed to improve the speed, rigor, and collaboration of academic and corporate research. The platform is built to help researchers uncover deeper insights, strengthen analysis, and work securely within one integrated environment.
Industry data indicates that 84% of researchers have used AI tools in their work, while only 22% express trust in existing tools. LeapSpace has been developed with the involvement of thousands of researchers and extends the capabilities of ScienceDirect AI and Scopus AI. Its foundation combines a broad collection of peer-reviewed scientific content with responsible AI practices. A core feature, Trust Cards, provides context, evidence transparency, rationales for cited sources, and indications of conflicting findings to support critical thinking and evidence evaluation.
LeapSpace™ is intended to help researchers progress from early inquiry to validated discovery while maintaining a reliance on trusted, peer-reviewed knowledge. The platform draws from verified scientific sources rather than unvetted web data and currently incorporates the world’s largest collection of research abstracts alongside millions of peer-reviewed full-text articles and books from Elsevier and additional scientific publishers and societies. Content volume will continue to expand as part of the long-term vision to support research grounded in reliable evidence.
The growing content set includes the world’s largest repository of research abstracts, data, and analytics from Scopus, Elsevier’s publisher-neutral index of more than 100 million records from over 7,000 global publishers, as well as more than 15 million peer-reviewed full-text articles and book chapters from Elsevier and other scientific organizations. LeapSpace’s transparency will be overseen by an independent advisory board responsible for ensuring that its algorithms remain explainable and publisher-neutral.
LeapSpace has been purpose-built for researchers seeking to manage multiple stages of their workflow in a single secure environment. Features include an integrated assistant capable of generating ideas, structuring project plans, analyzing literature, identifying collaborators, and locating funding opportunities. The system draws on abstracts and full text to produce referenced, structured responses.
The platform provides access to certified and curated scientific datasets, Trust Cards accompanying every AI-generated insight, and Deep Research capabilities that surface emerging patterns, assumptions, limitations, and evidence gaps. Users can upload their own materials for analysis. Integrated funding discovery enables access to 45,000 active and recurring grants totaling more than $100 billion from Elsevier’s Funding Institutional database. Additional tools such as Reading Assistant, Compare, and Author Search streamline evidence review and collaborator identification.
Elsevier has built LeapSpace with enterprise-grade security and has stated that the platform aligns with the company’s Privacy Principles to ensure responsible AI use and data protection. The underlying technology integrates agentic AI, generative AI, reasoning engines, and retrieval-augmented generation to support literature analysis, hypothesis development, and data exploration. All features reflect Elsevier’s Responsible AI Principles, prioritizing transparency, explainability, and human oversight, with full visibility into how results are generated.
The platform has been developed in collaboration with thousands of researchers from more than 300 institutions across 64 countries. Early users have reported that the system reduces time spent on key tasks, strengthens research design, uncovers overlooked insights, and enhances the depth of analysis, making it a frequent starting point for their workflows. Industry specialists in rare disease research have noted that LeapSpace can help synthesize widely dispersed information and address evidence gaps by enabling the review of large, multidisciplinary bodies of literature with improved rigor and clarity.
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