At Iris.ai we envisioned that if one person could absorb all scientific knowledge, they could solve many of humanity’s greatest challenges. Recognizing human limitations, we founded Iris.ai to build an AI that makes sense of and connects the dots across the vast and growing body of scientific knowledge. We are not just another AI company—we are mission-driven, aiming to transform how science is accessed, understood, and applied.
Our clients—primarily in chemical, pharmaceutical, MedTech, biotech, and materials science—face a critical challenge: the exponential growth of scientific content, increasing pressure to innovate, and a lack of digital transformation in R&D. These organizations rely on scientific papers, patents, and proprietary research. Their highly educated teams often spend up to 40% of their time on manual tasks like searching, aggregating, and cleaning data. With over 6,000 papers and 8,000 patents published daily, growing at 5% annually, accessing the right knowledge at the right time is becoming unmanageable.
These companies face two types of burdens: time-consuming tasks they must do (e.g. literature reviews) and high-value tasks they cannot scale (e.g. extracting insights from competitor patents). Their core need is to unlock insights from documented research—quickly, accurately, and securely.
Through this project, we transitioned from fragmented TRL6 tools to a coherent TRL8 platform—the Researcher Workspace—now deployed in four pilot organizations. It automates document comprehension, contextual interrogation, and knowledge extraction, reducing data-gathering time by up to 40%. The platform is content-agnostic, privacy-first, and adaptable to internal and external sources. It supports on-premise deployment and uses explainable, non-hallucinatory AI to ensure scientific rigor.
The project’s impact has been validated through pilot deployments, technical milestones, and market feedback. Dissemination reached thousands across academia, industry, and media. We secured €7.64 million in investment, submitted 18 approved deliverables, and launched a revised Go-To-Market strategy. With over 2,000 professionals engaged through events and media, we are well-positioned for growth.
Looking ahead, our vision is to build a fully-fledged scientific assistant—an AI that not only answers questions but guides users through research, asks the right questions, and brings interdisciplinary insights. This is our roadmap, and the project confirms Iris.ai’s readiness to scale and contribute to Europe’s digital and innovation agenda.
