The world’s only handheld, single-probe, whole-body ultrasound system powered by AI and Ultrasound-on-a-Chip™ technology.
Butterfly Network represents a paradigm shift in medical imaging by replacing traditional piezoelectric crystals with a single silicon chip (CMOS). As of 2026, their latest flagship, the Butterfly iQ3, utilizes advanced AI-driven 'Butterfly Compass' technology to provide real-time guidance for non-expert users, significantly lowering the barrier to entry for Point-of-Care Ultrasound (POCUS). The technical architecture is built on a massive dataset of ultrasound images used to train their 'Auto' suite—including Auto B-line, Auto Bladder, and Auto Ejection Fraction (EF) models. These models operate at the edge on mobile devices, providing low-latency diagnostic support. The system integrates with the Butterfly Cloud, a HIPAA-compliant SaaS platform that leverages machine learning to streamline billings, quality assurance, and fleet management. Positioning itself as the 'stethoscope of the future,' Butterfly has expanded its ecosystem through the 'Butterfly Garden,' allowing third-party AI developers to deploy specialized diagnostic algorithms directly onto the Butterfly hardware, effectively creating an 'App Store' for medical imaging.
Replaces traditional piezo-crystals with 9,000+ micro-machined sensors on a single semiconductor wafer.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
AI-driven visual navigation tool that provides real-time feedback on probe positioning for specific clinical views.
Uses deep learning to automatically calculate the percentage of blood leaving the heart with each contraction.
A developer platform for third-party medical AI companies to build and sell diagnostic apps on Butterfly's hardware.
Enhanced CMOS signal processing allowing for quantitative blood flow velocity measurements.
Integrated video conferencing with remote probe control and AR overlays for virtual supervision.
AI algorithm that identifies and counts B-lines in lung scans to assess pulmonary congestion.
Rapidly identifying internal bleeding in trauma patients without waiting for a radiology cart.
Registry Updated:2/7/2026
Lack of onsite radiologists to perform obstetric scans.
Immediate need to check heart function (EF) in the ICU.