Cascader offers AI‑powered software that automatically analyses retinal images to detect high‑risk eye diseases such as diabetic retinopathy, glaucoma, and age‑related macular degeneration, integrating with existing imaging workflows in hospitals and primary‑care settings. Its oculomics models also extract biomarkers from fundus photographs to provide early risk assessments for systemic conditions like cardiovascular disease, neurodegeneration, and dementia, delivering evidence‑based results through a secure clinician dashboard.
Funding
Funding not disclosed
Founders
Product
Problem
Clinicians often face high volumes of retinal imaging data and limited tools for rapid, accurate detection of eye diseases and systemic health indicators, leading to delayed diagnoses and suboptimal patient outcomes.
Solution
Cascader provides AI-powered software that analyzes retinal images to identify high-risk eye conditions such as diabetic retinopathy, glaucoma, and age‑related macular degeneration. The platform integrates into existing imaging workflows in hospitals and primary‑care settings, delivering automated, evidence‑based assessments that support clinicians in making timely treatment decisions. In addition to ocular disease detection, Cascader’s oculomics models extract biomarkers from retinal scans to flag early signs of systemic diseases, including cardiovascular risk, neurodegeneration, and dementia. All models are built on peer‑reviewed research and validated in clinical studies, ensuring reliability and regulatory compliance. Results are presented through a secure web interface that highlights disease probability, severity grading, and actionable recommendations, enabling scalable screening and consistent care across high‑throughput environments.
Target Audience
Primary customers are ophthalmology and optometry clinics, hospital ophthalmology departments, and primary‑care practices that perform retinal imaging and require AI‑assisted diagnostic support.
Features
- Deep‑learning algorithms trained on large, annotated retinal image datasets for automated detection of multiple eye pathologies
- Oculomics analytics that derive cardiovascular and neurodegenerative risk scores from standard fundus photographs
- Seamless integration with existing imaging devices and picture‑archiving systems via DICOM and API connectors
- Clinician dashboard with visual heatmaps, confidence scores, and suggested follow‑up actions
- Continuous model updates based on ongoing peer‑reviewed research and multi‑center clinical validation
- Secure, HIPAA‑compliant cloud processing and data storage with end‑to‑end encryption