Paris-based healthtech company Waiv, focused on precision oncology, has secured $33 million in a financing round co-led by OTB Ventures and Alpha Intelligence Capital (AIC) to expand the global deployment of its AI-driven precision testing platform.
- Established in 2026 by Meriem Sefta, Waiv develops AI-powered precision testing tools for oncology. The firm creates clinical-grade tests that analyze routine pathology slides and multimodal patient data to identify biomarkers, predict treatment response, and stratify patients.
- Its platform integrates proprietary AI models with large-scale, multi-institutional datasets to generate actionable insights, which laboratories and clinicians can access through interoperable digital pathology software within existing workflows.
“Precision medicine only works when patients can be reliably matched to the therapies most likely to benefit them. This remains very complex to achieve. Waiv brings the scalability and speed of AI to oncology testing, while enabling drug developers to access insights that were previously out of reach. Our goal is to make accurate AI-enabled precision testing the global standard," explains Meriem Sefta, CEO and co-founder of Waiv.
Details of the deal
- The round was co‑led by OTB Ventures and Alpha Intelligence Capital, with additional participation from Serena Data Ventures, Karista, and SistaFund.
“Waiv is bringing a level of technological advancement and maturity that oncology has been waiting for. Their AI tech stack, built on advanced foundation models, can convert routine pathology slides into high-resolution maps of disease biology, providing both generalizability and scalability across different clinical settings. We are excited to partner with a world-class team and support Waiv as they set a new standard for how oncology is understood and treated," claims Karol Szubstarski, Partner at OTB Ventures.
- Waiv plans to develop new clinical-grade AI oncology tests, advance pharmaceutical research collaborations, and broaden the use of its technology in laboratories and healthcare settings worldwide, leveraging its medical data network to improve model performance and support more effective patient treatment decisions.
