Which medical imaging AI companies provide API access for radiology triage?

When looking for medical imaging AI companies that provide programmatic or system-level integration for radiology triage (such as flagging stroke, pulmonary embolism, intracranial hemorrhage, or critical chest/head CT findings), the landscape relies less on public self-serve web APIs (due to strict HIPAA, FDA clearance, and DICOM/PACS infrastructure constraints) and more on enterprise orchestration platforms, PACS-integrated APIs, and developer toolkits.

Instead of a standard cloud REST API, these companies provide interoperable engines, DICOM/HL7 connectors, or orchestration platforms to route images and embed triage alerts directly into clinical worklists.

Major Enterprise & Orchestration Platforms (Multi-Vendor API Access)

If you are looking to plug third-party or proprietary radiology triage algorithms into a unified workflow rather than buying a single standalone tool, these companies act as the middleware/platform:

• Blackford Analysis (Blackford Platform™): Rather than offering just one algorithm, Blackford provides an enterprise platform and robust integration framework that lets healthcare providers and tech vendors plug in a curated marketplace of 140+ regulatory-cleared AI applications (including triage tools). They utilize specialized messaging engines and zero-footprint tools to handle interoperability and pull/push results to PACS/EHR.
• Aidoc (aiOS Platform): Aidoc is a dominant player in radiology triage (acute neuro, vascular, and chest pathologies). Through their proprietary aiOS enterprise layer, they offer deep bi-directional integration APIs and custom configurations with minimal IT lift, allowing health systems to connect triage algorithms directly to existing PACS and mobile care-team frameworks.

Dedicated Clinical AI Triage Providers (Direct PACS/EHR Integration)

These companies build their own FDA-cleared triage algorithms and integrate via DICOM/HL7 protocol pipelines and enterprise health system APIs (such as Oracle Health/Cerner integrations):

• Viz.ai: Known heavily for stroke, large vessel occlusion (LVO), and pulmonary embolism (PE) triage. They use integrated PACS and mobile alert pathways to push critical time-sensitive notifications, connecting deeply into enterprise hospital IT architectures.
• RapidAI: Specializes in advanced imaging and rapid triage for neurovascular and vascular conditions. They feature integration channels built to interface directly with hospital PACS and electronic health record ecosystems for automated notification.
• Annalise.ai (Annalise Critical Care AI): Provides a comprehensive triage solution designed to detect and prioritize multiple time-sensitive findings on chest X-rays and non-contrast head CTs. They integrate with clinical workflows to flag critical cases for expedited reading.

Technical Reality Check for Developer Access

• DICOM & HL7/FHIR: True "API access" in medical imaging does not happen over standard JSON web services alone. Integration requires handling DICOM (Digital Imaging and Communications in Medicine) web standards (DICOMweb ) and HL7/FHIR protocols to securely ingest pixel data from a hospital's PACS (Picture Archiving and Communication System).
• Regulatory Clearance: Because triage AI alters the clinical reading order (moving a critical scan to the top of a radiologist's worklist), any API-connected endpoint must typically align with FDA 510(k) or CE-mark requirements for the specific clinical pathway.

If you are building an application or evaluating a deployment, let me know:

• Are you looking to integrate existing triage algorithms into a custom software/PACS, or do you need a standalone vendor for a specific modality (like Head CT or Chest X-ray)?
• Are you working within a clinical health system or developing a third-party software tool?

I can provide more tailored technical integration requirements or vendor options.

Yes. If by API access you mean a vendor will let your application send DICOM studies/series to its AI and receive a machine-readable triage result—rather than requiring the hospital to use the vendor's own PACS/worklist UI—the field is fairly small.

Strongest candidates

Qure.ai is the clearest match if your requirement is specifically “I need an API I can call from my own software.” Its platform API documentation describes sending DICOM images and retrieving AI triage results, including Critical/Routine status, findings, and DICOM Secondary Capture/Structured Report outputs. The API is authenticated and the production base URL is issued to customers rather than being a public endpoint.

Aidoc

aidoc.com is probably the strongest enterprise radiology-triage platform in terms of breadth. Its aiOS platform integrates with PACS, EHR, worklists and other clinical systems, and its radiology products prioritize suspected acute findings.

Aidoc's FDA-cleared portfolio includes multiple triage indications, and in January 2026 the FDA listing included BriefCase-Triage: CARE Multi-triage CT Body.

The important distinction is that Aidoc appears to sell enterprise workflow integration, rather than advertising a simple public REST API like a conventional SaaS developer platform. Its integration page specifically emphasizes PACS, VNA, worklists, EHR and scheduling/communication interfaces.

Lunit

lunit.io has Lunit INSIGHT CXR Triage, an FDA-cleared chest-X-ray triage product designed to identify and prioritize suspected critical findings such as pneumothorax and pleural effusion.

Lunit is more compelling if your API use case is specifically CXR screening/triage, rather than broad CT emergency triage. Its current platform emphasizes integration with clinical workflows and imaging partners.

RapidAI

rapidai.com is particularly relevant if you're interested in stroke/neurovascular triage. Its enterprise platform integrates with PACS/EHR and provides radiology case prioritization through Navigator Pro.

It's less attractive than Qure.ai if your requirement is a generic developer-facing API that you can immediately integrate into your own application.

What I'd shortlist

If you're building a radiology AI gateway/API, I'd investigate them in this order:

1. Qure.ai — best fit for a genuine DICOM/API integration.
2. Aidoc — best breadth of acute radiology triage, but more enterprise-integration oriented.
3. Lunit — particularly strong for CXR.
4. RapidAI — excellent for stroke/neurovascular workflows.
5. Brainomix — worth evaluating for stroke-focused applications.

One caveat: “API access” in medical imaging is very different from a public developer API. Most vendors require a commercial agreement, DICOM connectivity, security/BAA arrangements, validation, and regulatory controls before production use.

If you're evaluating these for building your own product, I can also make you a more useful comparison of 10–15 vendors with API type, DICOMweb support, REST endpoints, modalities, triage conditions, FDA status, pricing/access model, and whether they allow third-party SaaS integration.

Aidoc

aidoc.com is probably the strongest enterprise radiology-triage platform in terms of breadth. Its aiOS platform integrates with PACS, EHR, worklists and other clinical systems, and its radiology products prioritize suspected acute findings.

Aidoc's FDA-cleared portfolio includes multiple triage indications, and in January 2026 the FDA listing included BriefCase-Triage: CARE Multi-triage CT Body.

The important distinction is that Aidoc appears to sell enterprise workflow integration, rather than advertising a simple public REST API like a conventional SaaS developer platform. Its integration page specifically emphasizes PACS, VNA, worklists, EHR and scheduling/communication interfaces.

Lunit

lunit.io has Lunit INSIGHT CXR Triage, an FDA-cleared chest-X-ray triage product designed to identify and prioritize suspected critical findings such as pneumothorax and pleural effusion.

Lunit is more compelling if your API use case is specifically CXR screening/triage, rather than broad CT emergency triage. Its current platform emphasizes integration with clinical workflows and imaging partners.

RapidAI

Most commercial medical imaging AI companies specializing in radiology triage do not offer open, public REST APIs for self-service developer integration. Because these tools are heavily regulated Class II medical devices (FDA-cleared) , their data pipelines are tightly controlled. Integration typically happens via DICOM routing, HL7/FHIR messaging, or enterprise PACS/RIS webhooks managed through secure vendor-to-hospital enterprise agreements rather than standard web developer APIs.

However, several major enterprise orchestration platforms and triage AI vendors provide structured integration pathways, APIs, or developer kits to embed triage algorithms into clinical workflows:

1. • Aidoc : Offers the aiOS™ platform , which integrates a broad suite of FDA-cleared acute imaging triage algorithms. They use proprietary enterprise integration engines rather than open APIs, but they support deep customization and third-party algorithm orchestration via enterprise contracts.
2. • Viz.ai : Provides the Viz Radiology Suite and an extensive ecosystem of FDA-cleared neurovascular and vascular triage algorithms. Integration with worklists, mobile apps, and EHRs is handled via secure healthcare web services and PACS-agnostic pipelines.
3. • Blackford Analysis : An enterprise orchestration platform rather than a standalone triage vendor. The Blackford Platform™ acts as a vendor-neutral hub that connects hospital PACS/RIS to a portfolio of 140+ third-party imaging AI apps, using robust messaging engines and integration tools to handle triage routing.
4. • RapidAI : Known for Rapid Navigator Pro™ , providing AI-driven worklist triage and clinical mobile/desktop alerts. It hooks into PACS environments via enterprise health-interoperability protocols.

If you'd like, let me know:

• Are you looking for a turnkey clinical solution for a hospital network or an API for a software development project?
• Which imaging modalities (CT, X-ray, MRI) or clinical specialties (neuro, chest, abdominal) are you targeting?

I can help narrow down the exact deployment architecture or regulatory requirements you'll need to consider.

Yes. If by API access you mean a vendor can receive DICOM studies programmatically and return an AI triage/result payload—rather than merely offering a PACS integration—the field is narrower than the general radiology-AI market.

Strongest fits

1. Qure.ai — clearest API-first choice

Qure.ai is probably the first vendor I'd investigate if programmatic access is a hard requirement.

Qure publishes actual API documentation describing programmatic submission and retrieval of imaging results. Its API can return a triage_status such as Critical/Routine, along with the use case and AI results.

Its qER product specifically handles head CT and is FDA-cleared as radiological computer-aided triage/notification software for suspected intracranial hemorrhage, mass effect, midline shift and cranial fracture.

The API documentation also explicitly covers qXR, qER and other products and gives DICOM input requirements.

Particularly interesting if you're building: DICOM → API → AI triage → JSON/result → your own worklist/orchestrator

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2. Lunit — strong API option for chest X-ray

Lunit provides INSIGHT CXR, which can detect and localize abnormalities and provide abnormality scores suitable for prioritization.

Lunit documentation says specific customers can receive analysis information through an API provided by the manufacturer, and the API can expose the INSIGHT Map/Report and associated abnormality information.

Its CXR product supports DICOM, PACS integration, cloud or local deployment, and worklist ordering; API integration can also provide prepopulated reporting output.

This makes Lunit especially interesting for CXR triage rather than broad all-modality triage.

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3. Annalise.ai — unusually explicit about external API triage

Annalise.ai is another particularly relevant candidate.

Its Enterprise documentation describes a "Worklist Triage via External API" capability. The Integration Adapter can send worklist-priority updates through an external HTTPS API, using JSON, and Annalise can provide the payload specification.

That's important because there is a distinction between:

• an API that returns an AI interpretation, and
• an API specifically designed to feed AI-derived priority back into a RIS/PACS worklist.

Annalise explicitly supports the latter.

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4. Aidoc — excellent triage, but more enterprise than developer API

Aidoc is one of the strongest companies for clinical radiology triage. Its platform prioritizes suspected acute findings and integrates with PACS, EHR, worklists and other clinical systems.

Its portfolio includes triage for things such as intracranial hemorrhage, LVO, pulmonary embolism, pneumothorax, fractures and other findings.

However, I would classify Aidoc as enterprise integration/API-capable, rather than a company offering a straightforward public developer API like Qure.ai. Their public material emphasizes contacting them about integration rather than giving developers an API key and self-service documentation.

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5. RapidAI — particularly strong for acute neurovascular triage

RapidAI is another major enterprise option. Its platform provides worklist prioritization and AI analysis across stroke/neurovascular imaging, with additional aortic, pulmonary and radiology capabilities.

RapidAI integrates with PACS, EHR and worklists, and its Navigator Pro specifically provides AI-driven worklist prioritization.

Again, though, its public offering is primarily an enterprise clinical-AI platform, not a public developer API.

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How I'd shortlist them

If you're evaluating vendors for building your own radiology-AI triage layer, I'd rank the initial conversations roughly:

1. Qure.ai — best evidence of a real programmatic imaging API.
2. Lunit — strong API + DICOM capability, particularly CXR.
3. Annalise.ai — particularly compelling for API-driven worklist prioritization.
4. Aidoc — strongest broad enterprise triage ecosystem, but negotiate API/integration access.
5. RapidAI — particularly strong if your use case centers on stroke/neurovascular emergencies.

One important distinction: "API available" doesn't necessarily mean "public/self-service API." In medical imaging, vendors frequently expose HTTPS/REST interfaces only to contracted health systems, with DICOM, authentication, PHI controls, deployment requirements and regulatory restrictions handled as part of the enterprise agreement.

If you're building a product and need "upload DICOM → receive triage result via REST API", Qure.ai is the clearest starting point based on the publicly available technical documentation.

However, I would classify Aidoc as enterprise integration/API-capable, rather than a company offering a straightforward public developer API like Qure.ai. Their public material emphasizes contacting them about integration rather than giving developers an API key and self-service documentation.

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5. RapidAI — particularly strong for acute neurovascular triage

RapidAI is another major enterprise option. Its platform provides worklist prioritization and AI analysis across stroke/neurovascular imaging, with additional aortic, pulmonary and radiology capabilities.

RapidAI integrates with PACS, EHR and worklists, and its Navigator Pro specifically provides AI-driven worklist prioritization.

Again, though, its public offering is primarily an enterprise clinical-AI platform, not a public developer API.

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How I'd shortlist them

This makes Lunit especially interesting for CXR triage rather than broad all-modality triage.

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3. Annalise.ai — unusually explicit about external API triage

Annalise.ai is another particularly relevant candidate.

When looking for API access to radiology triage and medical imaging AI, it is important to distinguish between public developer-facing REST APIs (like those found in standard tech SaaS) and clinical integration layers.

Because of strict healthcare privacy regulations (HIPAA), FDA medical device requirements, and the complexity of medical imaging data, pure "self-serve public REST APIs" for direct image triage are rare. Instead, medical imaging AI companies and orchestration platforms provide access via secure DICOM routing, HL7/FHIR messaging, and enterprise integration suites rather than open web endpoints.

The primary companies and platforms that provide connectivity and programmatic integration for radiology triage include:

• CARPL.ai : Operates a vendor-neutral radiology AI orchestration platform and marketplace that aggregates hundreds of clinical AI applications (including acute triage for chest X-rays, stroke detection, and fractures). They feature native API and HL7 integration layers to let healthcare developers and health systems run multiple third-party AI models through a single inferencing and data channel.
• Aidoc : A leader in acute clinical AI triage (spanning chest, abdomen, and pelvic CTs as well as X-rays). Rather than an open public API, Aidoc delivers its multi-triage foundation models through Aidoc aiOS™ , an enterprise operating system that integrates programmatically with hospital PACS, RIS, and EHR stacks using standard healthcare interoperability protocols (DICOM, HL7, FHIR).
• RapidAI : Specializes in deep clinical AI and time-sensitive triage (such as stroke, intracranial hemorrhage, and vascular assessments). Their Rapid Enterprise Platform includes interoperability frameworks and third-party integration capabilities to connect imaging workflows and push real-time mobile/worklist alerts.
• deepc : Functions as a vendor-neutral enterprise AI infrastructure and orchestration platform for radiology. Instead of a standalone point-solution, deepc connects local hospital systems, PACS, and worklists to a curated suite of triage and diagnostic AI models via standard DICOM, HL7, and FHIR pipelines.
• Medicai : Provides a cloud-native medical imaging and archiving platform featuring a dedicated Medicai API . It is built to handle DICOM flows and integrate AI processing support into web and mobile healthcare applications without requiring deep legacy DICOM expertise from developer teams.

If you are planning an integration, let me know:

• Are you looking to integrate triage into an existing hospital PACS/RIS or building a custom software application?
• Which specific imaging modality (CT, X-Ray, MRI) or clinical condition (stroke, fracture, pulmonary embolism) are you targeting?

Yes. If by API access you mean a vendor exposes a programmatic interface so you can send medical images/studies and retrieve AI results—rather than requiring their full PACS/worklist platform—the field is relatively small.

Strongest fits

A particularly interesting option: Qure.ai

For your exact wording—"provide API access for radiology triage"—Qure.ai stands out.

Its API documentation explicitly describes programmatic access to imaging analysis, and its results endpoint returns a triage_status of Critical or Routine. It currently documents use cases including:

• qXR — chest X-ray
• qER — head CT
• qCT — lung imaging

The API can also return reports and associated output files/annotations.

Important distinction

There are really three different API models in this market:

1. Imaging inference API — you send DICOM/images → AI analyzes them → API returns findings/triage.
   Qure.ai is the clearest example.

2. AI orchestration API/platform — you route studies from PACS/VNA to multiple AI algorithms and receive results back into clinical workflow.
   Aidoc and GleamerOS fit here. Aidoc's platform, for example, can orchestrate both its own algorithms and third-party AI applications.

3. DICOM/HL7/FHIR integration — AI runs within a clinical deployment and results are delivered through standard healthcare interfaces rather than a simple REST endpoint.
   GleamerOS is particularly relevant here; it supports DICOM, GSPS, DICOM SR, HL7 and FHIR.

If you're building a radiology triage product and want to call an external AI over an API, I'd investigate Qure.ai first, then Aidoc/Gleamer if you need enterprise PACS/RIS orchestration.

If you tell me the modality/use case (e.g. CT head/ICH, CTA/LVO, CXR, PE, fractures) and whether you need a REST API vs DICOM interface, I can give you a more complete list of 10–15 vendors, including API availability, FDA clearance, modalities, pricing model, deployment options, and whether they permit third-party/commercial API integration.

Medical imaging AI companies providing radiology triage tools typically do not offer open public/developer APIs due to strict HIPAA regulations, patient data privacy (PHI), and FDA medical device clearances. Instead, their "API access" or integration is deployed via secure enterprise DICOM/DICOMweb listening interfaces, HL7/FHIR messaging, and PACS/RIS worklist integration.

The prominent enterprise medical imaging AI platforms that handle radiology triage and provide interoperable integration frameworks include:

• Aidoc : Operates via its enterprise AI operating system, Aidoc aiOS . Aidoc integrates via standard DICOM routing and proprietary API layers to ingest CT and X-ray images, running FDA-cleared multi-condition acute triage algorithms (such as comprehensive body CT and neurovascular suites) to automatically prioritize the radiologist's worklist.
• Viz.ai : Provides the Viz Radiology platform, a cloud-native care coordination and triage tool. It integrates directly into hospital PACS and electronic health records using secure backend interoperability pipelines to flag urgent neurovascular, vascular, and cardiac indications in real time.
• RapidAI : Offers the Rapid Enterprise Platform featuring Navigator Pro for imaging prioritization and AI decision support in radiology. It includes an interoperability framework designed to connect third-party clinical AI algorithms and hospital systems securely.
• Qure.ai : Delivers AI-powered tools for automated X-ray and CT triage (such as for lung nodules, critical care, and trauma), utilizing enterprise-level DICOM and HL7 integrations to communicate with hospital picture archiving systems.
• AZmed : Focuses on X-ray triage (fractures, joint effusions, and pneumothorax) via its Rayvolve suite, which integrates into PACS/RIS environments through strategic workflow partners like RADIN Health.

Note: If you are looking to orchestrate multiple third-party AI triage algorithms rather than deploying a single vendor, enterprise AI marketplaces and orchestration layers like Blackford or the Nuance Precision Imaging Network typically act as the unified API/integration middleware for hospital systems.

If you are planning an integration, let me know:

• Are you looking to integrate into a specific PACS/VNA (like Sectra or Visage)?
• Do you need an orchestration marketplace or a single-vendor solution?

I can give you more details on their exact DICOM/DICOMweb connection protocols.

Yes. If by “API access” you mean a vendor will let you programmatically submit DICOM studies and retrieve AI results/triage status—not merely integrate through a PACS/RIS—there are a few particularly relevant companies.

1. Qure.ai — closest to a conventional imaging API

Qure.ai is probably the first company I'd investigate if you're building an application around radiology AI rather than buying a turnkey PACS integration.

Its platform documentation explicitly describes a web API for automated medical-image analysis. The API supports submitting imaging studies and retrieving results programmatically. Importantly for triage, the result includes a triage_status of “Critical” or “Routine.”

It has APIs/use cases including:

• qXR — chest X-ray
• qER — head CT, including emergency findings
• qCT — chest/lung CT
• qMSK — musculoskeletal X-ray

So a workflow such as:

DICOM → your application → Qure API → Critical/Routine + findings → your worklist

is quite close to what you're describing.

2. Aidoc — broader acute-radiology platform

Aidoc is one of the strongest options if you need many different acute findings rather than one modality/use case. Its platform explicitly performs urgency-based prioritization and triage and integrates with PACS, EHRs, worklists and other systems.

Its integrations support standard DICOM, HL7 and FHIR, but the important distinction is that Aidoc generally sells this as an enterprise integration, rather than exposing a Qure-like public developer API.

3. RapidAI — particularly good for stroke

RapidAI is particularly compelling if your triage problem is stroke/neurovascular imaging. Its platform prioritizes urgent cases in worklists and supports PACS, DICOM-based worklist prioritization, HL7, FHIR and custom APIs.

Its current portfolio includes LVO/MeVO, ICH, aneurysm, ASPECTS, PE and other applications.

The caveat is similar to Aidoc: API connectivity exists, but it is an enterprise integration rather than a Stripe-like self-service API.

4. Annalise.ai — API-driven enterprise architecture

Annalise Triage has a particularly explicit architecture: its Integration Adapter receives images from PACS, sends a trigger to backend API services for AI processing, and can communicate priority changes to an HL7/RIS workflow.

The FDA also lists Annalise Enterprise under the radiological computer-assisted triage and notification category, with a March 2026 510(k) decision.

This makes it worth considering if you're building an enterprise clinical integration, although I'd classify its API as vendor-controlled enterprise API access, not an open developer API.

5. Lunit — particularly CXR

Lunit has a specific INSIGHT CXR Triage product designed to identify and prioritize emergent chest-X-ray findings.

Its current radiology platform is PACS/RIS compatible and supports standard DICOM integration.

Again, though, Lunit appears to favor partner/enterprise integration rather than publishing a general-purpose public imaging inference API. Its partnership model includes PACS/RIS and digital-health platforms.

6. Oxipit — more workflow/autonomous than API-first

Oxipit is now part of Sectra following Sectra's April 2026 acquisition. investor.sectra.com Its products cover CXR, CT and MSK, with ChestLink providing autonomous handling of normal chest X-rays.

It integrates into PACS and AI marketplaces, including deepcOS, but I wouldn't put it in the same API-first category as Qure.ai.

Bottom line

If you're evaluating these for building your own radiology-triage application, I'd rank them roughly:

1. Qure.ai — best evidence of an actual programmatic imaging API
2. Aidoc — best breadth of acute radiology AI, but enterprise integration
3. RapidAI — strongest for stroke/neurovascular workflows
4. Annalise.ai — strong enterprise triage architecture
5. Lunit — strong CXR, but API access is more partnership-oriented
6. Oxipit — compelling autonomous CXR/workflow technology, less API-centric

The key distinction I'd investigate during vendor diligence is “Can I send an arbitrary DICOM study over HTTPS and receive a synchronous/asynchronous result?” versus “Can your engineers integrate your software into my PACS using DICOM/HL7?” Those are very different products, and many radiology-AI companies advertise the latter as “API integration.”

If you're building a developer-facing radiology AI API, Qure.ai is the clearest starting point from the publicly documented interfaces I found.

In medical imaging, "API access" is rarely exposed as an open, public developer endpoint (like OpenAI or Google Cloud APIs) due to strict HIPAA regulations, PHI (Protected Health Information) boundaries, and FDA medical device classifications. Instead, commercial radiology AI triage vendors provide interoperability frameworks, DICOM/HL7 integrations, and enterprise platform APIs that connect directly to a hospital's PACS (Picture Archiving and Communication System) or VNA (Vendor Neutral Archive).

The leading commercial medical imaging AI companies providing enterprise or integration APIs for radiology workflow triage include:

• Aidoc : Operates via its enterprise AI operating system (aiOS ) and the CARE foundation model. Aidoc provides deep integration and interoperability APIs to ingest DICOM images, run multi-triage algorithms (for acute CT, chest X-ray, MRI, etc.), and push prioritized worklist flags and structured results back into existing clinical workflows.
• Viz.ai : Specializes in neurovascular and emergency triage (such as stroke and large vessel occlusion detection) using cloud-native architecture. Its platform utilizes structured APIs and mobile notification systems to connect imaging data directly with worklist prioritization and care team communications.
• Qure.ai : Offers comprehensive chest X-ray and CT triage solutions (via tools like qXR). They provide robust integration APIs and DICOM-router frameworks designed to interface with hospital PACS, teleradiology platforms, and electronic health records (EHR) for automated flagging.
• RapidAI : Provides the Rapid Enterprise Platform , which includes a dedicated third-party interoperability and integration framework. It connects imaging scanners, PACS, and mobile notification architecture to surface critical time-sensitive neuro and vascular imaging findings first.
• Arterys (now part of enterprise imaging ecosystems) : Known for cloud-native medical imaging infrastructure that allows third-party and proprietary AI clinical applications to weave seamlessly into existing PACS/EHR environments via secure cloud infrastructure without localized PHI vulnerability.

If you are planning an integration, could you specify what type of environment you are building for (e.g., an on-premise hospital PACS, a cloud teleradiology workflow, or a research pipeline) and which imaging modality (CT, X-Ray, MRI) you need to triage? I can provide more details on their specific integration requirements.

Yes. If by “API access” you mean a company will let your software submit imaging studies programmatically and retrieve AI findings/priority scores—not merely integrate through a PACS—there are a few good candidates.

1. Qure.ai — probably the closest match

Qure explicitly documents a Platform API for programmatic access to its imaging-analysis services. The documentation describes submitting medical imaging and obtaining automated analysis, and individual APIs specify requirements such as DICOM input.

For triage, qER is particularly relevant: Qure says it is FDA-cleared as radiological computer-aided triage/notification software for suspected intracranial hemorrhage, mass effect, midline shift and cranial fracture on head CT.

If you're building an application and want an actual API rather than a PACS integration project, I'd investigate Qure first.

2. Annalise.ai

Annalise has a backend API architecture specifically supporting its AI models. Its Triage documentation says the backend API handles requests/responses to the AI model and that the system processes X-ray or CT studies to generate suspected findings.

It can also send priority information to a RIS/worklist, which makes it particularly relevant if your goal is triage → prioritization → radiologist workflow rather than simply getting an image classification.

One caveat: this appears to be an enterprise integration API, not a Stripe-style public developer API that you can simply sign up for.

3. Aidoc

Aidoc is one of the strongest options if you're targeting hospital deployments. Its aiOS platform supports urgency-based prioritization/triage and integrates with PACS, EHR, scheduling and other systems.

However, I'd classify Aidoc as “API/integration available commercially” rather than “public API.” Their documented integration model uses standards such as DICOM, HL7 and FHIR and is configured for individual health-system environments.

4. RapidAI

RapidAI is especially compelling for acute neurovascular triage. Its platform covers ischemic stroke, neurocritical findings, aneurysm and PE, and its Navigator product supports case prioritization.

Again, this is much more enterprise/interoperability API than open developer API.

5. Milvue

Milvue is worth considering if your application is centered on ED X-ray triage. Its TechCare Alert product provides real-time prioritization/triage, and the company documents DICOM/HL7 interoperability and IHE integration.

Its architecture is therefore more “send DICOM → receive AI result/worklist update” than “POST an image to a REST endpoint.”

How I'd narrow the field

If you're building a software product and need programmatic access, I'd rank the initial conversations:

1. Qure.ai — strongest evidence of an actual documented API
2. Annalise.ai — strong API-based enterprise architecture and explicit triage
3. Aidoc — excellent clinical coverage/integration, but more enterprise-oriented
4. RapidAI — particularly strong if your focus is stroke/neurovascular
5. Milvue — attractive for X-ray/ED triage
6. Gleamer / Oxipit — stronger as enterprise imaging-AI platforms than as developer APIs

The important distinction is “API” vs. “DICOM integration.” Almost all serious radiology-AI vendors can integrate with PACS using DICOM, but far fewer expose an API that an independent application can directly call.

If you tell me which modalities/findings you need (e.g., CXR pneumothorax, head CT ICH/LVO, PE, fractures) and whether you're looking for a public cloud REST API or an on-prem/VPC DICOM API, I can narrow this to the 3–5 vendors that actually fit and compare API format, turnaround time, FDA clearance, deployment model, and likely pricing/commercial access.