Ubenwa Secures $2.5 Million in Pre-Seed Funding Round Led by Radical Ventures

Ubenwa, a pioneering developer of diagnostic software for the rapid detection of medical anomalies in infant cry sounds has secured $2.5 million in pre-seed financing led by AI-focused Radical Ventures and AI pioneer Yoshua Bengio, with participation from returning investor AIX ventures, entrepreneurs Pieter Abbeel and Richard Socher, Canadian politician Marc Bellemare, and Google Brain’s Hugo Larochelle.

Found in 2017 by Charles Onu, Ubenwa is a spinout from Mila – the Quebec Artificial Intelligence Institute and is working with Montreal Children’s Hospital and pediatric hospital networks around the world, to build a platform for sound-based diagnostic tools, combining groundbreaking AI research and clinical insights.

Ubenwa’s technology is based on a foundation of scientific research developed in close collaboration with Mila, and six hospitals in three countries including Montréal Children’s Hospital, Enugu State University Teaching Hospital in Nigeria, Rivers State Teaching Hospital in Nigeria and Santa Casa de Misericordia in Brazil. The company has the largest and most diverse clinically-annotated database of infant cry sounds, an essential asset for the development of audio-based biomarkers.

“AI is well-suited to deriving insights from the sound signature of an infant cry,” said Yoshua Bengio, the AI pioneer who heads Mila. “Charles Onu’s leading research into identifying biomarkers in baby cry sounds offers the promise of unlocking our understanding of what’s behind a baby’s cry.”

For both clinicians and parents, an infant’s cry is difficult to diagnose. Babies cry for several reasons such as when they are hungry, exhausted or have colic. But a baby’s cry can also be a signal that more urgent care is required. Delayed diagnosis may lead to severe, long-lasting effects or fatality. Ubenwa has developed accurate algorithms for cry activity tracking, acoustic biomarker detection and anomaly prediction, turning infant cries into clinically-relevant insights and potential diagnoses. The company’s first pilot on detecting neurological injury due to birth asphyxia demonstrated about 40% improvement over APGAR scoring, the most common physical exam at birth.

“Ubenwa is building a diagnostic tool that understands when a baby’s cry is actually a cry for medical attention,” said Charles Onu, CEO and Co-founder of Ubenwa who has pioneered the use of audio signal processing and machine learning to better understand infant cry sounds. “Ultimately, our goal is to be a translator for baby cry sounds, providing a non-invasive way to monitor for medical conditions everywhere you find a baby: delivery rooms, neonatal and pediatric intensive care units, nurseries, and in the home.”

“Cry analysis has the potential to provide critical information for identifying babies with evolving brain problems,” said Dr. Guilherme Sant’Anna, Neonatologist at Montreal Children’s Hospital and Professor at McGill University. “A non-invasive diagnostic tool of this nature would be a powerful clinical resource for pediatric medicine. We are very happy to be collaborating with Ubenwa to realize this through well-controlled clinical studies.”

“Supported by a strong clinical foundation, Ubenwa has developed a proprietary innovation for an underserved and important market,” said Sanjana Basu, an Investor with Radical Ventures who joins the Ubenwa board. “Deciphering a baby’s cry using machine learning can open up a range of possibilities in the consumer and clinical pediatrics market where demand for better digital products is only growing.”