Diagnostics & imaging AI · Chest X-ray AI platform
DeepTek
DeepTek builds FDA-cleared radiology AI, including chest X-ray tools and the Augmento platform for AI-assisted radiology workflows. It is not an MRI acceleration product or ambient documentation scribe.
Strong fit
- Imaging programs that want FDA-cleared chest X-ray AI and a radiology AI platform, without first buying a large triage system that covers every imaging area
- Teams that will measure detection accuracy and reading time after Augmento or Chest X-Ray AI go live
- Buyers comparing mid-sized imaging AI vendors, not platforms the size of Aidoc
Weak fit
- Sites that only need faster MRI scans (look at Subtle)
- Buyers who need a U.S.-only vendor with no work done in India
- Programs that do few chest X-rays
Bottom line
DeepTek is worth using for mid-sized imaging groups that want FDA-cleared chest X-ray AI and a radiology AI platform without enterprise prices at the start. It suits radiologists who will work from its findings queue. Large systems that want triage across many imaging areas should look at Aidoc.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
DeepTek builds FDA-cleared radiology AI, including chest X-ray tools and Augmento, a platform that brings AI into radiologists' daily work.
Its strength is chest imaging and organizing AI results. That makes it a close peer of Riverain and narrower than Aidoc, which covers many imaging areas.
Results depend on how well it fits into PACS and whether radiologists trust its list of findings. Setting it up is a clinical imaging AI project, and pricing is custom.
Among imaging AI tools we review, DeepTek scores just below Riverain.
Riverain suits buyers mainly comparing ClearRead chest CT and X-ray tools. Aidoc suits those who need urgent-case flagging across many imaging areas, and Subtle suits buyers whose goal is faster scans.
The score reflects solid chest AI for mid-sized buyers.
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 | Software licenses for FDA-cleared chest X-ray AI and radiology AI platform modules. |
| What usually drives cost | The number of sites, scan volume, modules, and whether it runs in the cloud or on your own servers. |
| What to ask before you buy | The cost at your chest X-ray volume, which uses the FDA clearances cover, and how much PACS connection work is needed. |
| Published pricing | DeepTek does not publish prices. Expect a custom quote. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get DeepTek 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.