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 that have FDA-cleared use cases matching AISAP's cardio algorithms
- Teams that can integrate POCUS devices, reporting, and EMR/PACS paths
Weak fit
- Radiology groups shopping enterprise CT/MR triage AI like Aidoc
- Buyers without POCUS devices or training pathways
- Organizations that need broad multi-ology imaging AI on day one
Bottom line
AISAP earns a Conditional for buyers specifically standing up AI-assisted cardiac POCUS programs. FDA-cleared cardio algorithms and a POCUS operating-system story sit at the center of the product. Outcomes depend on device rollout, clinician training, and whether bedside reads change disposition decisions. It is earlier and narrower than Aidoc or Rad AI on our imaging board. Implementation is a POCUS program, not a PACS-wide AI platform. Pricing should be modeled per site and device footprint. Score reflects promising niche product marks with Conditional scale and coverage limits.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
AISAP builds AI for point-of-care ultrasound, with FDA-cleared cardiac algorithms and an operating-system layer for devices, reporting, and connection to PACS or EMR workflows.
That is a different shopping list than enterprise radiology triage (Aidoc) or reporting AI (Rad AI). Conditional is the right label until your POCUS program, training, and indications are real.
On our diagnostics board AISAP scores below the radiology AI leaders and with other narrower imaging tools.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| AISAP | 7.0 | 6.6 |
| Aidoc | 7.9 | 7.5 |
| Rad AI | 7.7 | 7.2 |
| Viz.ai | 7.7 | 7.3 |
| Subtle Medical | 7.2 | 6.8 |
Pricing
| Item | Detail |
|---|---|
| Model | Software licensing for POCUS AI / OS deployments; site and volume based. |
| What usually drives cost | Sites, devices, clinical modules, and whether cloud or on-prem packaging is required. |
| What to ask in diligence | Cost per site at your POCUS fleet, FDA indication coverage for your use cases, and EMR/PACS integration scope. |
| Published pricing | Public list price: not published. Expect a clinical-program quote. |
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 | |
| POCUS devices in clinical use or procurement | AI without ultrasound probes does not help bedside care. |
| FDA indication match for your intended exams | Off-label enthusiasm fails governance. |
| Clinical champion in EM, critical care, or cardiology | Unowned POCUS programs stall. |
| Path to document and bill encounters when appropriate | Workflow without reporting loses value. |
| IT plan for device, cloud/on-prem, and EMR/PACS connections | Bedside AI still needs integration. |
| What will maximize your value | |
| Train novices and experts on when to trust AI measurements | Blind trust is unsafe; blind distrust wastes the tool. |
| Start on high-yield cardiac use cases | Trying every POCUS exam at once dilutes quality. |
| Measure door-to-decision or transfer avoidance where relevant | Pick outcomes that matter clinically. |
| Keep radiologist or echo backup paths clear | POCUS AI does not replace formal imaging when needed. |
| Review image quality QA regularly | Garbage acquisitions create garbage AI. |
| Deal-breakers | |
| You need enterprise CT/MR triage like Aidoc. | |
| You have no POCUS devices or training pathway. | |
| 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 | Contract signed → kickoff | 2-6 weeks (clinical governance, device inventory) |
| 2 | Kickoff → first live workflow | 6-14 weeks for first units with reporting live |
| 3 | First live workflow → steady value | 3-6 months of training and QA before broader expansion |
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 actually 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.