Burlington, Massachusetts–based Butterfly develops a single-probe, whole-body ultrasound system with seamless AI integration. Now, it can accurately assess GA to improve pregnancy care. This can address significant gaps in populations that lack hospital obstetric services and face socioeconomic barriers.
The company said it marks the first FDA-cleared blind-sweep ultrasound AI tool for estimating GA. It provides earlier identification in key prenatal screenings. This detects complications sooner, guides intervention and can improve outcomes for mothers and babies.
Butterfly said its GA tool builds on deep learning models developed by Dr. Jeffrey Stringer and his team at the University of North Carolina at Chapel Hill. It uses an AI-powered, blind-sweep method to deliver reliable GA estimates in under two minutes.
The feature uses a simple three-step process. First, users enter fundal height, then they apply gel, then perform sweeps.
Butterfly trained its GA tool on more than 21 million images across diverse patient demographics and care settings. It integrated its solution directly into the Butterfly app for availability across the globe.
Already deployed in Malawi and Uganda, Butterfly received support for the GA tool through a Gates Foundation grant. It said FDA clearance enables expedited pathways to expand across additional regions in Sub-Saharan Africa and across the U.S.
Commentary from Butterfly Network officials
Dr. Sachita Shah, VP, Global Health, Butterfly Network, said:
“Improving maternal health outcomes and expanding access to prenatal imaging has become an urgent priority, and Butterfly is proud to be the first to bring this type of technology to mothers globally. With FDA clearance, we now have an AI-powered tool that can help transform maternal health, both worldwide and here in the U.S., by addressing longstanding gaps in access to timely, reliable imaging and enabling earlier, more informed care.”
Butterfly Chief Business Officer Steve Cashman said:
“The GA Tool is built to address three critical use cases: enabling faster decisions in emergency settings when gestational age is unknown; expanding access in countries where maternal and neonatal mortality remains high; and improving prenatal ultrasound access in rural U.S. communities, where patients may otherwise travel hours for imaging. Ultimately, it’s about helping clinicians act faster, earlier, and with greater confidence, at critical moments and in any setting.”
