Craif, a Japan-founded bio-AI company developing urine-based disease detection technology, has closed an approximately $34 million Series D financing round. The funding comprises about $30.7 million in equity and $3.3 million in debt.
The latest financing brings Craif’s total funding since its 2018 founding to approximately $88 million, including equity investment, debt financing and grants.
A spinout from Nagoya University, Craif develops technology that combines urinary microRNA analysis with artificial intelligence for cancer detection and personalized medicine. Its main commercial product, miSignal, measures microRNAs found in urine and uses AI to estimate an individual’s risk of several cancers.
The test covers pancreatic, lung, colorectal, breast, ovarian and prostate cancers. It is currently commercially available in Japan, where Craif says more than 2,500 medical institutions have adopted the technology.
Craif is separately developing a software-based medical device intended to support pancreatic cancer diagnosis. The product combines urinary microRNA profiling with AI to generate an assessment of an individual’s pancreatic cancer risk.
The company recently opened a laboratory in San Diego and plans to use the new capital to strengthen its U.S. research and development operations. Funding will also support the regulatory pathway in Japan for its pancreatic cancer medical device program and preparations to introduce its cancer testing technology in the U.S.
"I moved to San Diego to build our U.S. business myself, because the United States is the hardest and most important market to prove this technology," Ryuichi Onose, CEO and cofounder of Craif, said in a statement. "What we are building goes beyond a single cancer test. The earliest signals of many diseases show up in urine, and reading them is what Craif is really about. Cancer is the first step.”
Craif previously raised $22 million through a Series C financing round in April 2025. Its expansion comes as other companies are also developing urine-based diagnostic technologies, including tests that combine urinary biomarkers with AI and machine learning to identify disease-associated molecular patterns.
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