VzenCare · VisionV-Soft
From an eye-care idea to a working healthcare AI MVP.
Co-built an eye-care MVP with Aryaveer Agrawal and Vaibhav Gupta. The team announcement describes retinal-image disease and stage prediction, supported by a MongoDB backend.
Vision into possibility.RETINAL IMAGING / ML / MONGODBThe problem
Make eye-care screening more accessible. The MVP explores diabetic retinopathy, cataract, and glaucoma through retinal-image analysis.
How it comes together
The team iterated on the ML model across large datasets and GPU training cycles, then connected prediction workflows to a MongoDB-backed data layer.
Follow the flow.
Co-built the MVP with Aryaveer Agrawal and Vaibhav Gupta.
Explores disease identification and stage estimation from retinal images.
Pairs model iteration with a MongoDB backend for medical data.
Extends the VisionV-Soft journey recognized as Startupthon AIR 1.
Why this approach?
Treat model iteration and data management as parts of one product workflow. The team’s next focus is improving accuracy and scalability.
MVP capabilities follow the team’s public announcement. Clinical validation and measured accuracy are not published in the supplied evidence.