Aignostics, Berlin AI pathology firm, raises $34m

Berlin-based Aignostics, an artificial intelligence (AI) company that “turns complex multi-modal pathology data into transformative insights” announced it has raised $34 million in Series B financing.

This additional funding will be used to build new product offerings for biopharmaceutical clients, fuel growth within the United States (US), and develop leading foundation models for pathology in collaboration with Mayo Clinic.

The oversubscribed funding round was led by single-family office investor Athos, with investments from Mayo Clinic and growth financing from early-stage investor HTGF, alongside support from existing investors Wellington Partners, Boehringer Ingelheim Venture Fund, Carma Fund, and VC Fonds Technologie managed by IBB Ventures.

In total, Aignostics has now raised over $55 million.

“At its core, Aignostics is a world-class machine learning company,” said Julian Zachmann from Athos. “The field is advancing so quickly that, in order to succeed, AI companies need to avoid flashy distractions, stay laser focused on the highest-quality science, and relentlessly innovate. Aignostics is doing just that and bringing a level of transparency and rigor to its biopharmaceutical clients that we think is truly unique.”

Jim Rogers, CEO of Mayo Clinic Digital Pathology, said: “We know that digital pathology, paired with the vast capabilities of AI, has immense potential to impact diagnosis and treatment for patients. Mayo Clinic is actively charting the new frontier of predictive and personalized care.”

Viktor Matyas, CEO and Co-Founder of Aignostics, said: “2024 has been a pivotal year for us that has included a major strategic collaboration with Bayer and the launch of our first foundation model, RudolfV.

“With RudolfV, we’ve gained the ability to quickly develop cost-efficient algorithms that generalize to the real-world. Now with this new round of funding, we’re turning our most popular algorithms into products that will help usher in an era of truly generalizable AI for computational pathology.”