Iris.ai secured €7.64M to optimize its AI engine for scientific text understanding
Iris.ai, the startup behind an AI engine that can provide high-quality insights from scientific research publications, raised €7.64 million to enhance its flagship RSpace platform's factual accuracy capabilities.
Copenhagen-based Iris.ai recently raised €7.64 million in funding to continue developing its AI engine for scientific research acceleration. The round was led by Silverline Capital, with a matching investment from the European Innovation Council (EIC) Accelerator Fund.
Iris.ai aims at helping researchers across disciplines tackle the overwhelming volumes of research being published by providing an AI-powered solution that can accurately process (understand, categorize, summarize and systematize) data and facts from several sources, including academic papers, patents, and other technical or research documentation. RSpace, Iris.ai's platform, combines proprietary scientific language models with other machine learning models and generative AI capabilities to deliver high-quality insights into research data while reducing hallucinations.
Iris.ai will direct the funding towards enhancing the RSpace platform, its flagship offering. Particularly, the startup wants to boost the technology's factual accuracy capabilities to further streamline the research workflows of its client base across a diversity of disciplines and industries.
Ellie Ramirez-Camara is the News Editor at Data Phoenix, where she writes the daily AI newsdesk — covering model releases, research, funding rounds, and policy across the AI and machine-learning industry. She tracks announcements from labs and startups alike and distills them into clear, source-linked reporting for practitioners.
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