Wavelet Medical, a startup spun out of Yale University, has secured $7 million in seed funding and entered a co-creation partnership with Aegis Ventures to advance its AI-powered fetal brain monitoring platform. The company is focused on scaling its non-invasive fetal electroencephalography (EEG) technology for broader clinical adoption.
Founded by Liz Golden, Dr. Emily Lee, and Dr. Jose Cortes-Briones, Wavelet has developed a system designed to capture fetal brain activity through sensors placed on the mother’s abdomen. The platform applies proprietary AI algorithms to reconstruct fetal EEG signals and identify auditory-evoked brain responses, which can indicate neurological distress in real time.
“Until recently, noninvasive fetal EEG from the maternal abdomen was not feasible,” says Dr. Cortes-Briones. “We are now harnessing AI to reconstruct fetal EEG and translate it into quantitative markers of fetal distress.”
The company’s approach represents a shift from traditional fetal monitoring methods, which primarily assess heart rate, toward direct measurement of neurological activity. This may enable earlier detection of conditions such as hypoxia and provide more precise clinical insights during pregnancy.
Wavelet’s platform is currently being piloted at multiple clinical sites, including Yale University, LA General Hospital/USC, and Yonsei University Health System in South Korea. These deployments are intended to support validation efforts ahead of broader clinical trials and commercialization.
The partnership with Aegis Ventures is expected to accelerate Wavelet’s transition from academic research to a global commercial entity. Aegis, a venture studio focused on healthcare innovation, identified maternal-fetal medicine as an area with significant opportunity for predictive AI applications. The collaboration has also been supported by Yale Ventures and the Aegis Digital Consortium, which includes health systems such as Yale New Haven Health.
Clinical stakeholders have suggested that the technology could represent a meaningful development in fetal monitoring, with potential implications for improving diagnostic precision and reducing unnecessary interventions. By identifying early signs of distress, the platform may help lower rates of avoidable cesarean sections while supporting better neonatal outcomes.
“This isn’t about building a device,” says CEO Liz Golden. “It’s about building a new category in maternal health—one grounded in data, precision, and prevention.”
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