Diagnostics & imaging AI · POCUS AI
AISAP
AISAP is an AI platform for point-of-care ultrasound, with FDA-cleared cardiac algorithms and reporting workflows tied to POCUS devices. Hospitals use it to support bedside cardiac assessment. It is not enterprise CT/MR radiology triage AI.
Strong fit
- Hospitals and clinics expanding cardiac point-of-care ultrasound with AI assistance
- Programs whose scans match the heart uses AISAP's algorithms are FDA-cleared for
- Teams that can connect bedside ultrasound devices and reporting to the EMR and PACS
Weak fit
- Radiology groups looking for CT and MRI triage AI like Aidoc
- Buyers without bedside ultrasound devices or a training program
- Organizations that need imaging AI across many specialties from the start
Bottom line
AISAP is worth using for hospitals building a point-of-care ultrasound program with AI help for heart scans. It suits teams with the devices, training, and clinical uses in place. Buyers who want AI across all of radiology should look at Aidoc or Rad AI.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
AISAP builds AI for point-of-care ultrasound, the scans clinicians take at the bedside. Its FDA-cleared cardiac algorithms sit at the center of the product, along with software that runs on the devices, handles reporting, and connects to PACS or EMR workflows.
Results depend on how widely the devices are rolled out, how well clinicians are trained, and whether bedside readings change decisions about where patients go next. Implementing it means running an ultrasound program, which is a smaller job than deploying AI across a whole PACS. Pricing is best worked out for each site based on the number of devices.
That focus puts AISAP on a different shopping list from enterprise radiology triage tools such as Aidoc or reporting AI such as Rad AI. It is earlier and narrower than those companies, and among the imaging tools we review it scores below the radiology AI leaders and alongside other narrower tools. The score reflects a promising product in a niche, held back by its smaller scale and coverage, and the Recommend rating holds only for hospitals whose ultrasound program, training, and clinical uses are real.
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 | Software licenses for AISAP's ultrasound AI and operating software, priced by site and volume. |
| What usually drives cost | The number of sites and devices, the clinical modules you choose, and whether it runs in the cloud or on your own servers. |
| What to ask before you buy | The cost per site for your number of ultrasound devices, whether the FDA clearance covers the scans you plan to use it for, and how much work connecting to the EMR and PACS involves. |
| Published pricing | AISAP does not publish prices. Expect a quote based on your ultrasound program. |
Confirm FDA-cleared indications match the exams you will run before you budget a system-wide rollout.
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get AISAP to function | |
| Bedside ultrasound devices in use or being bought | The AI is no help at the bedside without ultrasound probes. |
| FDA clearance that covers the scans you plan to do | Using it outside its cleared uses will not pass internal review. |
| A clinical champion in emergency medicine, critical care, or cardiology | Ultrasound programs with no owner stall. |
| A way to document and bill these scans when appropriate | Scans that never reach a report lose much of their value. |
| An IT plan for devices, cloud or local hosting, and connections to the EMR and PACS | AI at the bedside still has to connect to your systems. |
| What will maximize your value | |
| Train novices and experts on when to trust AI measurements | Trusting it blindly is unsafe, and ignoring it wastes the tool. |
| Start with the heart scans that help most | Trying every kind of scan at once lowers quality. |
| Measure time from arrival to decision, or transfers avoided, where relevant | Pick outcomes that matter clinically. |
| Keep a clear path to a radiologist or a formal echo when needed | Bedside AI does not replace formal imaging when it is needed. |
| Check image quality regularly | Poor images produce poor AI results. |
| Deal-breakers | |
| You need CT and MRI triage across the organization, like Aidoc. | |
| You have no bedside ultrasound devices or training program. | |
| Compliance will not allow the cleared indications you want to use. | |
| No clinical champion exists. | |
| IT cannot connect devices or reporting for a year. | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | From signing to kickoff | 2-6 weeks for clinical approvals and listing ultrasound devices |
| 2 | From kickoff to first use | 6-14 weeks for the first units to start using it with reports |
| 3 | From first use to steady results | 3-6 months of training and quality checks before expanding further |
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.