Living Models Raises $7 Million for AI Biological Models
Living Models, a Paris-based company specializing in the development of AI foundation models for biology, has raised $7 million in a recent funding round. The funding, announced on March 12, 2026, will support the company's efforts to enhance its AI models trained on DNA, RNA, and multi-omics data, improving the understanding of biological systems.
Company Background
Founded by Bertrand Gakière (Co-Founder & CSO), Cyril Véran (Co-Founder & CEO), and Léonard Strouk (Co-Founder & CTO), Living Models is focused on creating large-scale transformer models that analyze genomic, transcriptomic, and other biological datasets. Their work aims to reveal patterns in living organisms, which can have significant implications for biological research and agricultural innovation.
Use of Funds
The $7 million raised will be used to further develop Living Models' AI capabilities. A key component of this expansion is the acquisition of access to a 120-GPU NVIDIA B200 computing cluster. This powerful infrastructure will facilitate the training of next-generation biological AI models, allowing the company to push the boundaries of current biological research.
Expanding AI in Agriculture and Biology
While AI has made significant strides in sectors such as finance and software, its application in agriculture and food production is still emerging. Living Models is targeting this niche by applying its AI models to plant biology. This approach aims to enhance crop resilience and productivity, which is increasingly important in the face of climate change challenges.
A Global Team
The company operates with teams located in both Paris and Berkeley, uniting expertise in artificial intelligence and plant science. This international collaboration is crucial for leveraging machine learning techniques to advance biological research and drive innovation in agriculture.
Living Models' recent funding marks a significant step in its mission to transform how AI is used in biological sciences, potentially leading to breakthroughs in how we understand and interact with living systems.