TL;DR
Dopl raised $6.3M for a telerobotic ultrasound platform letting sonographers work remotely. Founded by ex-Nvidia AI engineer and practising cardiologists. FDA 510(k) pathway established. Targeting rural care gaps.
Dopl raised $6.3M to pursue FDA clearance for a robotic ultrasound platform. It uses off-the-shelf robots, haptic controllers, and cameras. Rural hospitals see 90% shorter wait times.
Dopl raised $6.3M for a telerobotic ultrasound platform letting sonographers work remotely. Founded by ex-Nvidia AI engineer and practising cardiologists. FDA 510(k) pathway established. Targeting rural care gaps.
Dopl Technologies raised $6.3 million in seed funding led by SpringTide Ventures to advance a telerobotic ultrasound platform toward FDA clearance. The system, called Traverse, lets sonographers remotely operate a robotic arm via haptic controllers and cameras to perform diagnostic ultrasound exams on patients at distant sites. The platform is hardware-agnostic, integrating off-the-shelf robots and ultrasound systems into existing hospital infrastructure. Total funding is now over $8 million.
The company was founded in 2022 by a former Nvidia medical AI engineer alongside practising cardiologists and radiologists. The broader team includes alumni from Butterfly Network, Philips, Microsoft, and Amazon. Dopl has completed FDA pre-submission engagement and established a 510(k) regulatory pathway. The funding will support verification, validation, FDA submission, and initial pilot deployments at rural hospitals in Washington State.
While pursuing FDA clearance, Dopl launched CareBridge, an interim service that sends travelling sonographers to underserved hospitals in person. Patients in communities where Dopl operates see up to a 90% reduction in wait times. The plan is to transition these partner hospitals to the telerobotic system once it clears regulatory review. The company estimates a $40 billion annual reimbursement opportunity for US hospitals as telerobotic imaging scales nationally. Corti took a similar approach to medical coding, treating a broken clinical workflow as a reasoning problem and building AI around it rather than replacing clinicians. More than 50 million Americans live in areas with limited access to diagnostic imaging. The sonographer shortage is structural: training takes years, the workforce is aging, and rural hospitals cannot recruit specialists to live in remote communities. AI has shown it can outperform biopsies in rare cancer assessment, but most imaging AI requires a human to acquire the scan in the first place. Dopl’s bet is that the acquisition step can also be done remotely, turning a sonographer shortage into a distribution problem that robotics and connectivity can solve.
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