Aidoc
Healthcare AI platform that analyzes medical imaging to detect conditions and coordinate care across radiology, cardiology, and neurovascular teams.
Official Website ↗
Details and Sources
Status: activeReviewed: 2026-10-14
Aidoc Funding History
Aidoc develops clinical AI software that analyzes medical imaging and supports care coordination. Its platform connects image-analysis capabilities with clinical workflows, serving healthcare organizations that use AI to help manage findings and coordinate the next steps in patient care.
Company Overview
Aidoc Funding Timeline
Series E
$150M
Led by Growth Equity at Goldman Sachs Alternatives. Participation included General Catalyst, SoftBank.
Source · aidoc.com ↗Strategic Financing (CARE Foundation Model)
US$150 million
The financing backed CARE, Aidoc’s healthcare foundation model. Health systems participated in the transaction alongside venture investors.
Led by General Catalyst, Square Peg Capital. Participation included NVentures.
Source · aidoc.com ↗Series C
US$66 million
Aidoc announced the round as it expanded its AI platform across clinical applications beyond individual radiology use cases.
Led by General Catalyst. Participation included TCV.
Source · prnewswire.com ↗Series B Extension
US$20 million (Series B total US$47M)
This was an extension of the existing Series B. The announcement cited growing demand for AI tools used in radiology.
Led by Square Peg Capital.
Source · prnewswire.com ↗Series B
US$27 million
Led by Square Peg Capital. Participation included General Catalyst, Alpha Intelligence Capital, TLV Partners and 1 more on record.
Source · prnewswire.com ↗
Aidoc Products
FAQ
What is the difference between imaging triage and a final diagnosis?
Triage helps prioritize review. A diagnosis involves clinical interpretation and responsibility; an AI flag should not be treated as a replacement for that process.
Does a radiology AI platform have one approval for every use?
Regulatory permissions are tied to particular products, indications and jurisdictions. They should be checked individually rather than inferred from a platform description.
Why does hospital workflow affect imaging AI adoption?
Alerts must reach the right care team and fit existing imaging systems. An algorithm’s performance alone does not show whether the deployment improves care.
How should Aidoc’s later-stage financing be interpreted?
It records a capital event for the company. It does not by itself establish revenue, profitability or clinical outcomes.
Can funding for imaging AI be compared directly with drug-development funding?
The business models, validation requirements and development costs differ. Round size alone is a weak basis for comparing their operating progress.
What evidence matters when assessing an imaging AI deployment?
Look for the specific intended use, relevant validation population, false-alert burden and performance after integration into clinical practice.