- Iris.ai secures €7.64 million in its latest funding round to enhance its AI engine for scientific text comprehension.
- The company addresses the challenge of information overload in research and development departments.
- Integration of proprietary scientific language and generative AI module enables accurate categorization, navigation, and summarization of data from academic papers and technical documents.
- Silverline Capital leads the funding initiative, with the European Innovation Council (EIC) Accelerator Fund matching its contribution.
- CEO Anita Schjøll Abildgaard highlights the company’s momentum and adoption of generative AI combined with domain expertise.
- Funding will further develop Iris.ai’s flagship offering, RSpace, to improve factual verification capabilities for researchers.
- Investment signifies continued growth and innovation in AI-assisted scientific research, contributing to the European AI ecosystem.
Main AI News:
Iris.ai, a leading provider of an AI engine tailored for scientific text comprehension, has disclosed its recent funding round, amassing €7.64 million. The company addresses a critical challenge encountered by research and development divisions across various entities: the inundation of research publications. Leveraging its proprietary scientific language alongside other internally crafted machine learning models refined over eight years, Iris.ai integrates a generative AI module that produces top-tier text outputs. This integration not only mitigates the risk of misinterpretation but also proficiently categorizes, navigates, condenses, and organizes data and insights extracted from academic papers, patents, and diverse technical documents. Organizations reliant on cutting-edge scientific insights can seamlessly access actionable intelligence at scale.
The funding initiative was spearheaded by Silverline Capital, with the European Innovation Council (EIC) Accelerator Fund, the primary startup grant under EIC’s purview, matching its investment, consistent with the Fund’s prior endorsement in January 2023. Anita Schjøll Abildgaard, CEO and co-founder of Iris.ai, expressed, “This investment underscores the momentum we’ve amassed in the past year. Since January of last year, we’ve revolutionized our methodology by amalgamating the finest generative AI practices with the precision and expertise embedded in our proprietary scientific language models. Our adoption of the RSpace tool suite has facilitated successful onboarding of diverse clientele spanning material science, food science, medical, biotech, agriculture, chemistry, automotive, and cosmetics sectors.”
According to Evgeny Angelov of Silverline Capital, “The team has demonstrated exceptional proficiency in navigating a swiftly evolving landscape, capitalizing on their profound technical acumen and scalable market approach, all while prioritizing data privacy and evidence-driven AI insights. We take pride in supporting a European enterprise with global aspirations.”
The fresh influx of capital is earmarked for further enhancing Iris.ai’s flagship offering, RSpace. Building on the foundation laid in 2023, when Iris.ai introduced a solution to assess the factual accuracy of RSpace outputs, this investment will bolster the platform’s factual verification capabilities, streamlining research workflows for both corporate and academic researchers.
This strategic investment not only fuels Iris.ai’s ongoing expansion and innovation within AI-assisted scientific research but also contributes to the flourishing European AI landscape, fostering a vibrant ecosystem of technological advancement and knowledge dissemination.
Conclusion:
The substantial funding secured by Iris.ai reflects a growing recognition of the critical role AI plays in scientific research. With advancements in text comprehension and factual verification, Iris.ai is poised to address the escalating challenge of information overload, thereby enhancing research efficiency and driving innovation across various sectors. This investment signals confidence in the company’s capabilities and underscores the significance of AI-driven solutions in advancing scientific knowledge.
