Waiv spins out of Owkin with $33M for AI-driven cancer testing
AI-powered oncology startup Waiv, a spinout from French healthtech company Owkin, has raised $33 million to transform routine pathology slides into rapid, precision cancer tests. The funding will accelerate the global rollout of its AI pathology platform, designed to give oncologists and laboratories faster access to critical biomarkers and risk scores.
Turning routine slides into precision oncology insights
Waiv uses advanced AI algorithms to analyze standard hematoxylin and eosin (H&E) pathology slides and deliver clinically relevant outputs in minutes. Its flagship tools — RlapsRisk BC, MSIntuit, and BRCAura — aim to predict patient outcomes, identify candidates for targeted therapies, and detect genetic risk signatures without the need for additional complex or costly tests.
RlapsRisk BC is focused on breast cancer risk stratification, helping clinicians better understand prognosis and tailor treatment intensity. MSIntuit targets microsatellite instability (MSI) status, a key biomarker for immunotherapy eligibility in several tumor types. BRCAura is designed to infer BRCA-related signatures from pathology images, potentially guiding decisions around PARP inhibitors and hereditary cancer assessment.
Global ambitions for AI pathology in everyday labs
The fresh capital will support regulatory validation, clinical partnerships, and commercial expansion, with a focus on making AI pathology accessible to routine hospital and reference labs worldwide. By working directly on existing pathology workflows and infrastructure, Waiv aims to reduce dependence on slow, expensive molecular testing and broaden access to precision oncology in both high-resource and underserved settings.
Backed by its heritage from Owkin, a pioneer in federated learning and medical machine learning, Waiv is positioning itself at the intersection of digital pathology, biomarker discovery, and clinical decision support. Investors are betting that AI-powered slide analysis will become a standard layer in cancer diagnosis, enabling faster, more personalized treatment decisions for patients worldwide.