Country of Residence
United States
Age
16
Project title
Ocunetra
Project Summary: Describe your project in one sentence
Ocunetra is a low-cost, AI-powered ocular screening platform that utilizes a 3D-printed attachment to transform any smartphone into a clinical-grade diagnostic tool, detecting diabetic retinopathy early to prevent irreversible blindness in underserved healthcare deserts, where expensive fundus cameras are out of reach.
Website URL(s) or social media handles.
https://ocunetra-site.vercel.app/
Project Category
My project is an existing project that I started
Project Stage
Growth (We’ve moved past the very first activities and are beginning to have consistent weekly or monthly impact)
Founding Story: What was the spark that led you to start your project? What was the "Aha!" moment that led you to get started and see the potential for this to succeed?
In the 1980s, life in rural India was unbearably hard. Every day was a battle to put food on the table. Amartya's grandfather, who had diabetic retinopathy, could barely see. The nearest place for surgery was hours away, and he couldn't leave his family for that long. Slowly, his vision faded to near blindness, leaving him helpless with basic tasks. Yet he never stopped working, carrying the weight of his family on hands he could no longer see clearly. Hearing his mother’s stories of his grandfather struggling left an ache in all of our hearts. Inspired by stories like his around the globe, we wanted to develop an app that could improve access to eye care and never let anyone struggle like that again. According to the World Health Organization, over 1.1 billion people live with undiagnosed but reversible eye conditions, often in remote areas with little access to specialists. Smartphones are far more available than trained eye-care providers, offering a way to bring screening closer to patients. Conditions like cataracts and diabetic retinopathy can cause blindness when care comes too late. People lose independence when care is delayed. With our app, we aim to help people recognize when they may need further care. We strive to make eye screening accessible so no one has to face the helplessness Amartya's grandfather did, struggling in the dark.
The Problem: What problem are you helping to solve? Why does it matter to you and your community?
Diabetic retinopathy can damage vision before a person notices symptoms. Regular retinal exams can catch warning signs, but people in rural and low-income communities may face long drives, few specialists, lost wages, and clinic fees. The barrier also affects the clinics trying to serve them: a professional screening setup needs a trained operator and dedicated imaging equipment. Our planning materials estimate a fundus camera at about $13,500, while our proposed smartphone attachment is $47.50 in hardware. That is a target price, not a claim that the two systems are clinically equivalent. For a small clinic or outreach program, equipment and staffing costs can determine whether screening is available at all. This matters to us because Amartya’s grandfather lost much of his sight to diabetic retinopathy in rural India. Specialist care was hours away, and he could not easily leave his family or work. The same pattern persists when people know an eye exam matters but cannot reach one. We want to make the first step toward care easier to bring into underserved communities and help people get professional follow-up sooner.
Your Solution: How are you solving this problem? Share your specific solution.
Ocunetra combines a 3D-printed phone mount, a 90D retinal lens, and an iOS app. The mount holds the lens in front of the phone camera to help capture a retinal image. In the app, a user follows guided capture instructions, takes or uploads an image, and receives an easy-to-read screening result indicating whether professional follow-up may be needed. We trained a diabetic-retinopathy model on thousands of labeled retinal images and worked to run image analysis on the device, which could help in places with limited connectivity. Our app work also includes a separate conjunctivitis model, visual heatmaps to explain model output, and self-tests such as an Amsler grid, color-vision test, and contrast-sensitivity test. Together, these features give users more than a single opaque score: they offer a clearer picture of their eye health and a reason to seek care when needed. We have designed and printed the attachment, developed the app, revised the models, and used the combined kit to screen 50 people. Next, we plan to improve image-quality checks, make the mount fit more phones, strengthen the app’s plain-language guidance, and add a more reliable way to find or connect with nearby eye-care professionals. We also want a clinician-guided pilot to improve the workflow and evaluate how the system performs with images captured through our own kit. Our goal is a portable first screening step that community programs could eventually use where conventional equipment is difficult to obtain.
Impact: How has your project created impact / made a difference so far? Or, if at an early stage, what will impact look like?
We have put substantial work into moving Ocunetra from a family story to a working prototype. Our three-student team researched gaps in diabetic eye care; learned to train, debug, and revise machine-learning models using thousands of public retinal images; designed and printed the lens mount; and built a mobile app that brings the pieces together. We have used the app and attachment to screen 50 people. Those are 50 people reached with our prototype, not a claim that we have prevented blindness or clinically validated the system. We have also taken the idea to VC meetups and pitch events, where feedback helped us sharpen the product, explain the access problem, and think more seriously about practical deployment. Our team won the 2025 Congressional App Challenge for Texas’s 31st District. The next impact is to learn what happens after screening: whether images are usable, whether people understand their results, and whether they can reach professional follow-up. Challenge funding would let us buy more lenses and prototype materials, test across more phone models, document results more consistently, and work toward a supervised clinic pilot. It would turn early reach into evidence we can use to improve access responsibly.
Your Innovation: What is different about your project compared to other programs or solutions already out there? How is your project new or innovative?
Our closest alternatives are traditional retinal exams and clinic-based AI systems such as Eyenuk’s EyeArt. These rely on patients reaching a facility with imaging equipment and trained staff. For people who live far from an eye specialist, that trip, its cost, and time away from work can be enough to delay screening. Ocunetra is designed to bring an initial check closer to them. Our proposed $47.50 hardware kit uses a reusable 3D-printed mount to align a 90D lens with a smartphone camera, rather than requiring a dedicated fundus camera that can cost thousands of dollars. The app guides a user through capturing a retinal image, runs our diabetic-retinopathy model on the phone, and presents a plain-language result that can prompt professional follow-up. On-device analysis can also support use where connectivity is unreliable. We have developed visual heatmaps to show which regions influenced a model output, plus an Amsler grid, color-vision test, and contrast-sensitivity test in the same app. We are working on image-quality checks and a clearer route from a screening result to a nearby eye-care professional. The innovation is the full pathway: affordable optics, guided capture, understandable results, and distribution through community clinics and nonprofits that already reach people in health care deserts. Our team built both the attachment and software and has used them to screen 50 people, giving us practical experience beyond public image datasets. Funding would let us improve the kit across phone models and test the full workflow with clinicians before scaling it. We are aiming to complement professional exams, not claim that our prototype already matches a validated clinical system.
How many people are on your team?
3
Your team: What role(s) do your team members play? How do you share leadership with them?
Three students lead Ocunetra. I’m Amartya, CEO, and lead outreach, community relationships, and potential clinical partnerships. Ronit is CTO and leads research and development, including hardware and model testing. Pranav is CFO and manages the software and app portion. We share leadership by reviewing feedback together, deciding priorities as a team, and dividing work according to our strengths. We built the prototype together, and as a team, our strengths complement each other.
What’s Next: What are the next steps you plan to take to grow or strengthen your project over the next year? If your project is still in the idea stage, describe the steps you will take over the next three months to launch or begin developing it.
Over the next year, we will build on our prototype and 50 initial screenings. We will improve lens alignment, image-quality checks, app guidance, and compatibility with more phones, then collect structured feedback from people with diabetes and eye-care professionals. We plan to approach Retina Consultants of Austin about a clinician-guided pilot comparing images and model outputs from our kit with professional grading. We will also work through consent, privacy, safety, and regulatory requirements before broader clinical use. Funding would directly accelerate our research and development. We would buy lenses, printing materials, and test devices; run more consistent hardware and software trials; improve the model using appropriate feedback; and prepare a supervised pilot. We would measure usable image rates, user understanding, and agreement with expert review. In parallel, we will seek nonprofit and community-health partners that could eventually distribute the kit in underserved areas, starting with small, well-supported deployments and using what we learn to refine the product.
How do you encourage other people to join your project or learn about the problem you’re working on? If you have a new idea, tell us how you will do this in the future.
We began by bringing together three students with different strengths in outreach, research, and software. We have shown the prototype to potential users and used the app and attachment to screen 50 people. We have also sought feedback from eye-care professionals and at VC meetups, using those conversations to improve how we explain the problem and plan the product. Our next step is to invite screening participants and clinicians to give structured feedback on image capture, clarity, and the path to follow-up care. To reach communities with few eye-care resources, we plan to partner with nonprofits and community-health programs that already have local trust and distribution networks. They could help us identify where the need is greatest, introduce the kit to clinics or outreach teams, and connect people flagged for follow-up with qualified professionals. We will run an education campaign explaining diabetic retinopathy, why routine eye exams matter, and why a phone screening result does not replace a professional exam. We will track who joins, what they contribute, and how their feedback changes Ocunetra.
