Description
Aidoc is a clinical AI platform for medical imaging, holding more FDA clearances than any other company in the radiology AI category and deployed across more than 1,600 medical centers worldwide, including Yale New Haven and Cedars-Sinai. Its core product, aiOS, is an AI operating system that runs in the background of a hospital’s existing PACS and EHR infrastructure, scanning imaging data the moment a scan is acquired and flagging time-sensitive findings like stroke, pulmonary embolism, brain bleeds, and aortic dissection ahead of the radiologist’s queue. In January 2026, Aidoc received FDA clearance for CARE, the first comprehensive multi-condition AI triage solution built on a proprietary foundation model, detecting 14 acute findings from a single body CT scan rather than requiring separate algorithms per condition. Aidoc reports supporting clinical decision-making for more than 60 million patients each year. It suits hospital radiology and emergency departments that need FDA-cleared AI to prioritize time-critical cases at scale.
Key Features
- aiOS platform — an AI operating system integrating directly into existing PACS and EHR infrastructure.
- CARE foundation model — Aidoc’s proprietary AI model powering multi-condition triage from a single scan.
- Most FDA clearances in radiology AI — covers stroke (LVO), pulmonary embolism, brain bleeds, fractures, aortic dissection, and more.
- Comprehensive abdomen CT triage — detects 14 acute findings, including liver injury, appendicitis, and bowel obstruction, from one scan.
- Real-time background scanning — analyzes pixel data as soon as a scan is acquired, without disrupting radiologist workflow.
- AI-powered analytics — transparent reporting on flagged cases and turnaround times.
How It Works
As soon as a scan is acquired, aiOS identifies the exam and order characteristics and automatically applies the correct FDA-cleared algorithms in the background, without requiring a radiologist to manually route the study. If the CARE foundation model or another cleared algorithm flags a time-sensitive finding, that case is moved ahead of the queue so the radiologist reviews it sooner rather than in standard first-in-first-out order. The January 2026 clearance for comprehensive abdomen CT triage is a meaningful shift in approach: instead of running 14 separate single-purpose algorithms on a scan, one foundation model detects all 14 conditions in a single pass, reported in an FDA-reviewed pivotal study to achieve 97% sensitivity and 98% specificity. Because aiOS is built to integrate into a hospital’s existing infrastructure rather than requiring a standalone viewer, most hospitals deploy it as the underlying operating layer for radiology AI, adding cleared indications over time rather than picking individual algorithms one at a time.
Technical Architecture & Overview
- Core Engine: CARE (Clinical AI Reasoning Engine), Aidoc’s proprietary, self-developed foundation model for multi-condition detection; a successor, CARE2, is reportedly in development.
- Deployment: Cloud-based aiOS platform integrating directly into a hospital’s existing PACS and EHR infrastructure; backed by a multi-year AWS infrastructure partnership.
- API Surface: Integrates with PACS, EHR, and existing hospital IT systems as part of enterprise deployment; third-party AI modules also run on top of aiOS.
- Known Limits: No public pricing or self-serve access; enterprise deployment requires hospital IT and radiology department integration, and coverage depth depends on how many FDA-cleared indications a given hospital licenses.
Pros & Cons
| Pros | Cons |
|---|---|
| Most FDA-cleared algorithms of any company in the radiology AI category | No published pricing; every deployment requires enterprise sales and IT integration |
| CARE foundation model detects 14 acute findings from a single abdomen CT scan in one pass | Focused specifically on imaging triage, not broader clinical documentation or hospital operations |
| aiOS integrates into existing PACS/EHR infrastructure rather than requiring a separate standalone tool | Value depends heavily on how many cleared indications a hospital licenses and deploys |
| Deployed across 1,600+ medical centers, supporting a reported 60 million patient cases per year | AWS-backed infrastructure partnership ties deployment scale to a specific cloud provider relationship |
Our Take
Aidoc’s real differentiator is breadth of FDA clearance combined with the aiOS operating-layer approach — rather than picking individual algorithms, most hospitals deploy Aidoc as the underlying infrastructure and add cleared indications over time. The CARE foundation model’s shift to detecting 14 conditions from one scan, instead of running 14 separate algorithms, is a genuinely different architecture than most single-purpose radiology AI tools use.
Not ideal for: health systems whose priority is hospital operations, documentation, or revenue cycle rather than imaging — Aidoc is purpose-built for acute-finding detection and triage in radiology and emergency departments, not the broader operational or administrative problems tools like Qventus or Waystar address.
Pricing
Aidoc does not publish pricing on its official site. Like most enterprise clinical AI platforms, it’s sold directly to hospitals and health systems through a sales-led process, with cost depending on which FDA-cleared indications a hospital licenses, deployment scope, and integration requirements with existing PACS and EHR systems. There is no self-serve trial or individual-provider plan; contacting Aidoc’s sales team is the only way to get a quote.
Last verified: August 18, 2026
Platform Availability
Cloud-based (integrates with hospital PACS/EHR)
Best For
Hospital radiology departments | Emergency departments | Health systems | Academic medical centers
Frequently Asked Questions
Does Aidoc publish pricing?
No. Aidoc is sold directly to hospitals through enterprise sales, with cost depending on licensed indications and deployment scope; there’s no published price list.
What is aiOS?
aiOS is Aidoc’s AI operating system, integrating directly into a hospital’s existing PACS and EHR infrastructure to run FDA-cleared algorithms in the background as scans are acquired.
What is the CARE foundation model?
CARE (Clinical AI Reasoning Engine) is Aidoc’s proprietary foundation model, cleared by the FDA to detect up to 14 acute findings from a single body CT scan in one pass, rather than running separate algorithms per condition.
How many hospitals use Aidoc?
Aidoc reports deployment across more than 1,600 medical centers worldwide, supporting clinical decision-making for a reported 60 million patient cases annually.
How does Aidoc differ from Viz.ai?
Aidoc holds the most FDA clearances in the category and emphasizes its aiOS operating-layer approach and foundation-model triage, while Viz.ai emphasizes a broad portfolio of 50+ cleared algorithms across specialties plus built-in care coordination and alerting.
