Iris.ai Unveils AI-Powered Tools to Unlock Deep Knowledge in R&D Data
OSLO, Norway, Nov. 12, 2024 – Following a successful €7.64 million Series A funding round, Iris.ai, a global leader in AI-driven scientific research, has unveiled new advancements that mark the culmination of nine years of innovation. The company's latest development addresses one of the most pressing challenges in research and development: unlocking the vast reservoirs of deep knowledge embedded within decades of R&D work.
Deep Knowledge refers to the complex, interconnected insights buried within an organization's historical R&D work. This encompasses not just surface-level information but the intricate relationships between concepts, methodologies, and findings that have evolved over time. By unlocking Deep Knowledge, researchers can build upon previous work, identify patterns across disparate sources, and accelerate innovation by avoiding redundant efforts.
For commercial entities, Deep Knowledge represents an untapped competitive advantage. Companies sitting on decades of research data, lab notebooks, technical documentation, and internal reports possess a wealth of potentially valuable insights. The effective mining of Deep Knowledge enables organizations to identify new applications for existing technologies while simultaneously uncovering overlooked commercial opportunities in previous research. By leveraging this historical knowledge base, organizations can avoid costly redundancies and prevent teams from unknowingly reinvesting resources into problems that have already been solved or paths that have proven unfruitful in the past.
At the core of Iris.ai's offering is a suite of AI-powered tools designed to unlock and process deep knowledge, representing the fruition of nine years of intensive research and development. This suite, including the newly introduced RSpace platform, leverages Iris.ai's extensive expertise in natural language processing (NLP) and machine vision to extract and organize knowledge from vast internal repositories. As a result of nearly a decade of innovation, these AI tools enable researchers to easily access relevant information, transforming vast unstructured datasets into actionable insights.
"This journey of innovation hasn't been overnight – it's taken years of dedicated research to reach this point," said Anita Schjøll Abildgaard, CEO of Iris.ai. "We've seen R&D teams repeatedly struggle with the same issue: they have all the knowledge they need, but it's locked away in disparate, unstructured formats. We always expected the AI technology landscape to develop in the way it has, so we’ve built the perfect foundation to leverage all the most recent breakthroughs."
R&D teams across industries are increasingly overwhelmed by the sheer volume of unstructured data within their organizations. A study by Iris.ai of 500 research professionals revealed that 66% feel overwhelmed by the volume of published research they must review. Scientific papers, patents, internal reports, and regulatory specifications are dispersed across various formats, making it difficult for researchers to access the insights needed to drive innovation. With Iris.ai's AI solutions, R&D professionals can now manage and transform this data more effectively, allowing them to focus on generating new insights and accelerating their projects.
"With the support of our investors and the dedication of our team, we've created AI tools that make it faster and easier for research teams to access the knowledge buried in their data and apply it innovatively," Abildgaard added. "By putting deep knowledge at researchers' fingertips, we're enabling them to drive breakthroughs that can have real-world impact."
About Iris.ai
Iris.ai is a world-leading and award-winning AI engine for deep knowledge textual understanding, co-founded and run by serial founders Anita Schjøll Abildgaard and Jacobo Elosua alongside AI researcher Victor Botev, with a cross-European team around them. The founders and the team have placed themselves at the very forefront of the field of AI for complex unstructured documentation, with solid in-house research efforts on NLP and applications of LLMs. Iris.ai has developed world leading infrastructure and tools, based on both LLM and multiple other AI/ML approaches, for transforming unstructured information into actionable Deep Knowledge. The RSpace Core application, the configurable Enterprise offerings, and the Infrastructure API are based on a combination of in-house, and modified and fine-tuned open source models. The system is architected for the deepest and most complex forms of knowledge - and is scalable across all industries.
Source: Iris.ai
