Aidoc

Aidoc is an Imaging & Diagnostics AI company founded in 2016 and based in Tel Aviv, Israel. It has raised $384M in total funding, most recently a Series E in 2026.

Aidoc provides an enterprise AI platform (aiOS) that analyzes medical imaging — CT, MRI, X-ray — to flag critical conditions like pulmonary embolism, intracranial hemorrhage, and spinal fractures in real time. $150M Series E at ~$3.5B valuation in 2026. Over 2,500 hospitals deployed. Raised total $500M+. Expanding beyond radiology into cardiology and clinical workflows.

Aidoc is the most scaled clinical AI imaging platform globally, with 18+ FDA-cleared algorithms, $500M+ total funding, and a platform approach that solves the hospital's multi-vendor AI implementation problem.

aidoc.com Imaging & Diagnostics AI

Israelprivate

At a glance

Total raised

$384M

last round series e

Headcount

501-1k

approximate · public range

Headquarters

Tel Aviv

Israel

Founded

2016

10 years active

Status

Private

Imaging & Diagnostics AI

Patents on file

Funding history

Total raised

$384M

Rounds tracked

Latest stage

Series E

Date	Stage	Amount	Valuation	Lead investors
Apr 29, 2026	Series E	$150M	—	Goldman Sachs Alternatives
Jul 24, 2025	Series D	$110M	—	TCV, Alpha Intelligence Capital

Most recent patents

Aidoc Medical Ltd·2026-01-06
Performance Estimation Of Machine Learning Models That Analyze Medical Images
US12518517
Abstract
Performance Estimation Of Machine Learning Models That Analyze Medical Images
US12518517
Abstract There is provided a method, comprising: feeding target metadata parameters of target medical image(s) into a performance estimation machine learning (ML) model, and obtaining a performance metric of a computer vision ML model as an outcome of the performance estimation ML model, wherein the performance estimation ML model is trained on a training dataset comprising records, wherein a record is created by feeding a sample medical image into the computer vision ML model, obtaining an outcome of the computer vision ML model, obtaining a ground truth of the sample medical image corresponding to the outcome, extracting metadata parameters associated with the sample medical image, and wherein the record includes metadata parameters associated with the sample medical image and a ground truth label comprising a performance metric of the computer vision ML model computed based on the ground truth of the sample medical image and the outcome.
View on Google Patents
AIDOC Medical Ltd.·2024-06-18
System For Determining The Presence Of Features In A Dataset
US12014489
Abstract
System For Determining The Presence Of Features In A Dataset
US12014489
Abstract A system for determining whether a dataset including a plurality of cross-sectional images includes a predetermined feature is provided. A first AI receives a dataset including a plurality of cross-sectional images, and analyses the dataset to identify a subset of cross-sectional images of the dataset capable of including the predetermined feature A second AI model receives a first cross-sectional image from the subset, analyses the first cross-sectional image to determine whether the first cross-sectional image includes the predetermined feature, and outputs an indication of whether the first cross-sectional image includes the predetermined feature. A processor is configured to obtain the output from the second AI model, and based on the output from the second AI model indicating that the first cross-sectional image includes the pre-determined feature, determine that the dataset includes the predetermined feature.
View on Google Patents

Aidoc

At a glance

Funding history

In the news

Why Aidoc is taking a generative AI device to the FDA

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Leadership

Products

aiOS™

Radiology AI Solutions

Vascular AI Solutions

Neuro AI Solutions

Most recent patents

Performance Estimation Of Machine Learning Models That Analyze Medical Images

Performance Estimation Of Machine Learning Models That Analyze Medical Images

System For Determining The Presence Of Features In A Dataset

System For Determining The Presence Of Features In A Dataset

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