Diagnostics & imaging AI · Ultrasound AI CDS
Koios Medical
Koios Medical provides FDA-cleared AI clinical decision support for breast and thyroid ultrasound (Smart Ultrasound / Koios DS). It is not a CT triage platform, MRI acceleration tool, or ambient documentation product.
Strong fit
- Breast and thyroid ultrasound programs that want FDA-cleared AI to act as a second reader
- Sites that will measure how many biopsies find disease and how often readers agree after Koios DS goes live
- Buyers comparing ultrasound AI decision support, not CT triage or faster MRI
Weak fit
- Radiology groups whose main purchase is CT and MRI triage across the whole system
- Programs without enough ultrasound exams in the uses it is cleared for
- Buyers who need an AI scribe or a new image system
Bottom line
Koios Medical is worth considering for ultrasound programs that specifically need FDA-cleared AI decision support for breast and thyroid imaging. It suits readers who want a consistent second opinion in their workflow. Programs that need chest imaging detection or CT triage should look at Riverain or Aidoc.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Koios Medical provides FDA-cleared Smart Ultrasound AI that supports decisions on breast and thyroid ultrasound. The goal is more consistent and efficient diagnosis.
The clinical niche is real, but little is public about how widely it is sold.
Results depend on how well it fits the way readers work and whether its second opinion changes biopsy decisions.
Setup is a project in ultrasound and reporting work, and pricing is custom.
Its focus on ultrasound decision support sets it apart from Riverain's chest CT and X-ray detection, Subtle's faster imaging, and Aidoc's triage.
AISAP suits heart ultrasound at the bedside. Riverain suits chest CT and X-ray detection, and Aidoc suits buyers whose main need is CT triage across a health system.
Among the diagnostics tools we review, Koios scores at the low end. Its niche is real, but there is limited proof that it works at large scale.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Aidoc | 7.9 | 7.5 |
| ScreenPoint Medical | 7.9 | 7.6 |
| Harrison.ai | 7.7 | 7.5 |
| Qure.ai | 7.4 | 7.1 |
| Riverain Technologies | 7.3 | 6.9 |
| Subtle Medical | 7.2 | 6.8 |
| DeepTek | 7.1 | 6.8 |
| AZmed | 6.9 | 6.7 |
| Enlitic | 6.9 | 6.5 |
| Avicenna.AI | 6.9 | 6.6 |
| Ferrum Health | 6.8 | 6.5 |
| Koios Medical | 6.7 | 6.3 |
Pricing
| Item | Detail |
|---|---|
| Model | A software license for FDA-cleared ultrasound AI, priced by site and volume. |
| What usually drives cost | The number of sites, exam volume, breast or thyroid modules, and how it connects to your systems. |
| What to ask before you buy | The cost per site at your ultrasound volume, which uses are covered, and how much work it takes to connect to your reporting system. |
| Published pricing | Koios does not publish prices. Expect a quote. |
Public figures on the size of Koios's business conflict. Ask about its commercial scale before you buy.
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Koios Medical to function | |
| A clinical owner in radiology, plus imaging IT | AI tools fail without both. |
| A written plan for connecting to PACS, RIS, and the EMR | Results that land where no one looks create a safety risk. |
| Agreement on which kinds of scans are covered | Trying to cover every kind of scan at once delays results. |
| A plan for who reviews alerts and AI-enhanced images | Lists no one owns get ignored. |
| Agreed times for changes that could interrupt clinical work | New screens that appear without warning during busy hours destroy trust. |
| What will maximize your value | |
| Measure turnaround, reopened reports, or the detection numbers agreed at kickoff | Accuracy in a demo does not prove it works day to day. |
| Start with one common type of scan | A small real win is worth more than a broad launch with nothing behind it. |
| Review false alarms with radiologists every week | Tools that raise too many false alarms get turned off. |
| Keep radiologists in the viewers they use now when possible | Extra reading lists drive radiologists away. |
| Check which of your scan types the FDA clearances cover | Paying for clearances that do not match your scans wastes money. |
| Deal-breakers | |
| There is no imaging IT or clinical owner. | |
| You will not do any connection work. | |
| You expect imaging AI to write clinical notes. | |
| No one will review alerts or AI-enhanced images. | |
| Your legal team blocks the cloud or vendor handling of patient data that you need. | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Plan | 2-4 weeks. Agree on scan types, connections, and how success is measured. |
| 2 | Connect | 4-12 weeks. Connect to PACS, RIS, and the EMR, and test on real cases. |
| 3 | Pilot | 4-8 weeks. Run at one site or for one kind of scan. |
| 4 | Expand | Ongoing. Add sites and make adjustments. |
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.