Aidoc vs Bunkerhill Health (2026)
Both sell a health system an operating layer for clinical AI rather than a single algorithm, and the difference is who writes the agents. Aidoc built the enterprise imaging platform, with a deep clearance history of its own, data normalization, continuous performance monitoring and the ability to run many algorithms through one radiology workflow. Bunkerhill sells the toolkit: clinical and operational teams build, deploy and govern their own agents, with more than 20 running simultaneously at a named academic health system, and it holds its own clearances including imaging findings on routine scans. The question underneath is accountability. Buying a catalog leaves validation with the vendor. Building your own agents moves it to your quality committee, and neither vendor publishes how a customer authored agent gets validated, monitored or retired once it is live.
- The regulatory record is the deepest here, with a long history of cleared imaging algorithms and an operating system that handles normalization, continuous performance monitoring and deployment across a health system's imaging estate.
- It solved the problem of running many algorithms in one workflow before anyone called it agentic, which is what an enterprise imaging deployment actually needs.
- Named deployment at scale across health systems gives a buyer references who have already lived through the integration rather than pilot sites.
- The platform lets clinical and operational teams build, deploy and govern their own agents rather than consuming a vendor's catalog, with more than 20 agents reported running simultaneously at a named academic health system.
- Its agents reach beyond imaging into nephrology, pulmonary nodule follow up and oncology prior authorization, and it holds multiple FDA clearances on its own agents rather than on partner algorithms.
- SOC 2 Type II is published with the type named alongside a trust center, and agents take real actions including drafting orders for clinician review rather than only flagging findings.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Aidoc and Bunkerhill Health are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Aidoc | Bunkerhill Health |
|---|---|---|
| Primary category | Radiology & Imaging AI | Health System AI Platforms |
| Founded | 2016 | Not recorded |
| Headquarters | Tel Aviv, Israel | San Francisco, California |
| Website | aidoc.com | bunkerhillhealth.com |
Side by Side
Select any grade to read the note behind it.
Product updates
The latest logged changes from each vendor, newest first, each linked to its source.
Aidoc
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Regulatory / FDA
Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of pneumomediastinum and lobar or lung collapse.
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Clinical evidence
Mercy and Aidoc released a white paper, commissioned by AVIA, reporting on five months of AI deployment across the Mercy health system.
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Regulatory / FDA
The FDA cleared Aidoc's comprehensive abdomen CT triage solution, powered by its self developed CARE foundation model, bringing 11 newly cleared indications together with three previously cleared into a single 14 indication workflow.
Source
Bunkerhill Health
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Regulatory / FDA
CMS established a national billing code and associated payment under the Hospital Outpatient Prospective Payment System for algorithmic analysis of coronary artery calcium and aortic valve calcium on chest CT, effective April 1, 2026.
Source
Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
Aidoc sells clinical AI for imaging triage and follow up to health systems, delivered through aiOS, an enterprise platform that runs Aidoc's own FDA cleared algorithms alongside vetted partner algorithms and carries care coordination and patient management. Aidoc Medical was established in early 2016 in Tel Aviv and is led by cofounder and chief executive Elad Walach.
Source: AI Health Index, August 2026
Agentic AI platform for health systems. Carebricks lets clinical and operational teams build, deploy, and govern their own AI agents across clinical, operational, and administrative workflows rather than buying a point solution per use case. Agents in production include coronary calcium detection on routine chest CT, nephrology triage, lung nodule follow up, referral prioritization, prior authorization packet assembly, and registry automation.
Source: AI Health Index, August 2026
Questions buyers ask
How do Aidoc and Bunkerhill Health work with the EHR?
Aidoc ingests DICOM routed or queried from PACS and VNA or sent from modalities, plus HL7 messages, and returns results to a desktop widget, the native worklist, the reporting system, or PACS as a separate series. Authentication runs through Active Directory, a dedicated single sign on, or sign on through PACS, RIS or dictation software, a practical detail in a radiology department.
Bunkerhill's agents read clinical report and imaging archives and the EHR, and act by generating documentation, notifying care teams, initiating referrals and patient outreach, as the UTMB case study describes. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
How do Aidoc and Bunkerhill Health handle patient data?
In Aidoc's case, the company's security and privacy documentation describes a new DICOM object created before upload carrying only non PHI data and a newly generated identifier; analysis runs on that object, and the identifier re-attaches PHI locally when results return.
Bunkerhill states HIPAA compliance, SOC 2 Type II and ISO 27001, and links a trust center that may hold its policies. Its agents read imaging archives, report archives and the full longitudinal record across a health system. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
What evidence is published for Aidoc and Bunkerhill Health?
With Aidoc, the announcement's means (97 and 98 percent) match that table; its 'up to' figures (98.5 and 99.7 percent) do not correspond to any figure in it.
In Bunkerhill Health's case, the cleared algorithms have 510(k) performance summaries; the agent outcomes have no stated method or baseline. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
How much do Aidoc and Bunkerhill Health leave to the clinician?
Aidoc flags suspected acute findings, reorders the worklist and pushes a notification with a preview image to a desktop widget; results can also go to the native worklist, the reporting system or PACS as a separate series. The K252970 indication states the limits: analysis runs in parallel with the standard read, preview images are for notification only, the device is not for diagnosis, and notified clinicians must view the full images.
Bunkerhill sells outcomes ('Name the outcome. Bunkerhill delivers.'), and its UTMB case study reports 20+ live agents with '100% of agentic workflows fully automated', including agents that flagged patients with incidental coronary calcium and initiated cardiology referrals. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
The two records differ in what a buyer is accountable for after signing. An algorithm marketplace with cleared partner models places validation with the vendor and the algorithm owner; a platform on which the health system builds its own agents places it with the health system, and neither vendor publishes how customer built agents are validated, monitored or retired.
Bunkerhill publishes no retention period, no position on whether customer data trains models and no de identification posture. Neither publishes pricing. Both are strongest where imaging is concerned, so a buyer evaluating them for non imaging workflows is comparing on the least evidenced part of each record.