Diagnostics & imaging AI · Echocardiography AI
Ultromics
Ultromics makes EchoGo, FDA-cleared AI that analyzes routine echocardiograms and flags patients likely to have heart failure with preserved ejection fraction or cardiac amyloidosis.
Strong fit
- Hospital echo labs and cardiology groups that see many patients with shortness of breath
- Heart failure and amyloidosis programs that want missed cases found on routine scans
- Health systems that want an AI tool Medicare pays for
Weak fit
- Groups that want AI across X-ray, CT, and MRI
- Practices with low echo volumes
- Buyers who need a published price list
Bottom line
Ultromics is worth using for echo labs and heart failure programs that want to find hidden heart failure and cardiac amyloidosis earlier without new hardware. Its FDA-cleared EchoGo AI reads standard echocardiograms, and Medicare pays for its use. Hospitals building bedside cardiac ultrasound programs may prefer AISAP.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Ultromics, a University of Oxford spinout based in Oxford, England, makes EchoGo, AI that reads a standard echocardiogram. Ross Upton built its first algorithm during his PhD at Oxford with his supervisor, cardiologist Paul Leeson, and the company spun out in 2017.
EchoGo Heart Failure, cleared by the FDA in 2022, analyzes the routine views of an echocardiogram. It flags patients likely to have heart failure with preserved ejection fraction, a form of heart failure that standard measurements often miss.
EchoGo Amyloidosis, which received FDA breakthrough device clearance in late 2024, looks for cardiac amyloidosis, another condition that is often missed.
Results go to the cardiologist with the echo, and EchoGo Score adds a probability for each patient. No new scanner or hardware is needed.
Ultromics raised a $55 million Series C in July 2025, co-led by L&G, Allegis Capital, and Lightrock. The American Heart Association's Go Red for Women Venture Fund invested later that year.
It has analyzed more than 430,000 echocardiograms. In clinical studies EchoGo improved detection of heart failure with preserved ejection fraction by 73.6% compared with standard clinical risk scores.
Medicare pays for its use in both outpatient and inpatient care, and City of Hope is among its U.S. users.
Compare AISAP when a hospital is building AI-guided bedside cardiac ultrasound, and Studycast when the need is echo and imaging reporting and workflow.
Aidoc fits a health system that wants AI across many imaging types.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Us2.ai | 7.7 | 7.5 |
| Ultromics | 7.4 | 7.1 |
| Studycast | 7.2 | 6.9 |
| AISAP | 7.0 | 6.6 |
Pricing
| Item | Detail |
|---|---|
| Model | Custom contract quoted by Ultromics. |
| What usually drives cost | Echo volume, which EchoGo products are used, the number of sites, and integration with the echo reporting system. |
| What to ask before you buy | The price per study, how Medicare and other payer reimbursement offset the cost, and who runs the integration with your echo system. |
| Published pricing | Ultromics does not publish a price list. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Ultromics to function | |
| Echo lab director as clinical lead | Sets how results are used. |
| Echo reporting system access | Studies route to the AI. |
| Heart failure program for follow-up | Flagged patients need a path. |
| Baseline diagnosis rates | You need them to show the change later. |
| Billing setup for reimbursement | Offsets the cost. |
| What will maximize your value | |
| Run it on patients with shortness of breath | Highest yield. |
| Send flagged patients to a heart failure clinic | Turns findings into treatment. |
| Review cases flagged but not treated | Shows gaps in follow-up. |
| Deal-breakers | |
| Low echo volume | |
| No follow-up pathway | |
| Wants AI for other imaging | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract and integration | 1-3 months |
| 2 | First echo lab live | 2-4 months |
| 3 | More sites and amyloidosis | 4-9 months |
Leadership
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.