InVision delivers clinically-validated AI for the most common cardiac imaging exam in the world — streamlining interpretation, standardizing measurements, and surfacing disease that today goes undiagnosed.
CPT Category III code 0932T (effective January 1, 2025) supports AI-assisted echocardiographic evaluation for patients with heart failure symptoms — providing a direct reimbursement path for Precision Cardiac Amyloid, not a budget ask that lives on indefinitely.
Echo interpretation consumes over an hour of physician and technician time per exam. Precision LVEF has been shown in a blinded, randomized trial to reduce sonographer and cardiologist effort while improving measurement consistency.
FDA 510(k) clearance for both Precision LVEF and Precision Cardiac Amyloid. Cardiac Amyloid was previously granted Breakthrough Device Designation and enrolled in the FDA's Total Product Lifecycle Advisory Program (TAP).
Post-processing analysis of standard DICOM echo studies. No new hardware, no new scanners, no disruption to the cardiology workflow — deploys alongside your existing PACS, Epic EHR, and structured reporting platforms.
Cardiac amyloidosis is rare, under-diagnosed, and now treatable. Our algorithms screen every routine echo at zero marginal clinician burden — turning your existing imaging volume into a population-health instrument.
LVEF and Cardiac Amyloid are live. Precision Cirrhosis holds Breakthrough Device designation, and Precision Reporting — powered by our Nature-published foundation model — is in active development. A single deployment path that grows across your cardiovascular service line.
Automated evaluation of left ventricular ejection fraction from standard echocardiographic DICOM images. The only AI-Echo product to undergo a blinded, randomized prospective clinical trial — published in Nature, demonstrating time savings and improved clinical precision.
Learn more about Precision LVEFAI screening for cardiac amyloidosis from apical-4-chamber and parasternal-long-axis echocardiographic views. Developed in collaboration with Alexion, AstraZeneca Rare Disease, to accelerate early detection of a life-threatening and routinely missed condition.
Learn more about Precision Cardiac AmyloidOpportunistic screening for cirrhosis and steatotic liver disease directly from the subcostal view already captured during routine echocardiography. Built on EchoNet-Liver — a deep learning pipeline developed from over 1.5 million echocardiogram videos and validated against paired abdominal ultrasound and MRI across two large academic medical centers.
Learn more about Precision CirrhosisAutomated, structured echocardiographic reports built on two complementary open-source foundation models. EchoPrime (Nature, 2025) — a multi-view vision-language model trained on over 12 million video-report pairs — delivers holistic clinical interpretation across 23 diverse benchmarks of cardiac form and function, validated in five international health systems. EchoNet-Measurements (JACC, 2025) — trained on 877,983 sonographer annotations from 155,000+ studies — automates 18 standard B-mode and Doppler parameters with accuracy comparable to expert sonographers (R² 0.97 — 0.99).
Learn more about Precision ReportingThe same research foundation extends to multi-valve screening. Mitral regurgitation detection was published in Circulation (2024), and automated deep learning phenotyping of tricuspid regurgitation — led by Vrudhula et al. — was published in JAMA Cardiology (2025). Aortic valve work is in active development, with clearance pathways to follow.
See the full pipelineOur foundation is a decade of academic work at Stanford and Cedars-Sinai — culminating in the first and only prospective, blinded, randomized clinical trial of AI in cardiology. Here's the evidence trail, in the words of the journals that published it.
InVision is founded and led by the people who authored the foundational literature on AI in echocardiography — not by acquirers of someone else's research. That difference shows up in how our models are built, how they're tested, and how they behave at the bedside.
Dr. Ouyang is an attending cardiologist who reads echoes every week — currently at Kaiser Permanente Northern California and previously at Cedars-Sinai. Our models are designed against real workflow, not inferred from one.
Backed by Y Combinator and strategic partners including Alexion (AstraZeneca Rare Disease), with live deployments through partners like HeartLab.
Precision LVEF is trained on more echocardiographic videos than any other FDA-cleared echo AI model, giving it unmatched generalizability across scanners and populations.
Schedule a 30-minute briefing with our clinical and commercial teams. We'll walk through deployment, reimbursement, and the evidence base — tailored to your cardiovascular service line.