Airdoc applies retinal AI to detect disease from fundus photographs, powering large-scale screening for diabetic retinopathy and other conditions across China and Asia.
Airdoc built its business on a specific medical insight: the retina reveals systemic health. Its AI analyzes fundus photographs to screen for diabetic retinopathy, glaucoma risk, cardiovascular indicators, and neurological markers, delivering results in minutes from standard retinal cameras. The company’s systems are deployed in hospitals, community health centers, and screening programs across China, where the scale of diabetes and aging populations makes manual specialist screening impractical. Regulatory approvals for its diagnostic software reflect clinical validation across diverse populations, and its models improve continuously from real screening data. For primary care and public health programs, retinal AI turns an accessible, non-invasive test into a broad health-risk screen administered without specialist interpretation. Airdoc’s platform supports population-scale screening logistics — workflow integration, quality control on captured images, and referral pathways for positive findings — since screening only matters when it leads to care. Continuing model updates incorporate findings from ongoing screening programs, keeping performance current as camera hardware, patient populations, and clinical guidelines evolve across the regions where its systems are deployed.
Airdoc works with hospitals, screening programs, and device partners through enterprise agreements, with pricing by deployment and screening volume alongside hardware and service arrangements.
Hospitals, community health systems, and public-health programs — particularly across China and Asia — that need scalable eye-disease and health-risk screening without specialist bottlenecks. It fits primary-care settings where a fast, camera-based screen can identify which patients genuinely need to reach an ophthalmologist.