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Eyebou: AI for eye-screening children to detect vision disorders

Eyebou Data Science+AI United Arab Emirates
Nov 09 , 2022
Eyebou mobile app
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Data Science+AI


United Arab Emirates
Amount invested $103,643 USD Funding Status active early period Founded in 2020 by Farris Massoudi & Amy Fehilly
Female Founded
Generating Revenue

The team behind Eyebou aims to resolve access to healthcare, specifically eyecare, and empower children toward access to education where they may have failed or dropped out of school due to unresolved or unknown vision issues.  

In this interview with Eyebou Co-Founder Amy Fehilly, learn more about the UAE-based startup developing an AI tool for virtual eye exams to detect vision disorders in children. The solution is optimized for low-resource environments and limited connectivity and can be accessed using a mobile device.  

Tell us about your startup and what you are building. 

At Eyebou we are using technology to make eyecare accessible and affordable around the world. We have built vision screening tools which can detect a variety of vision and eye health-related issues using a smartphone app. 

How did you come up with your solution and what inspired you to form your company? 

I  come from a family of optometrists but my personal interests have always been in social impact and NGOs. The creation of Eyebou allowed us to take medical knowledge, combine it with technology (the interest of my co-founder, Farris Massoudi) and create software that can be used to have a huge social impact.  

"The UNICEF Venture Fund investment helps Eyebou to build robust artificial intelligence in the eyecare space. With this investment, we will directly be helping over 10,000 children to receive eyecare but we hope the collaboration with UNICEF will create more opportunities allowing us to give eyecare to many more. In this way, we hope to improve the quality of life and access to education for more children globally." - Amy Fehilly, Co-founder, Eyebou

The Solution

How would you describe your solution to a non-technical person? 

Our first vision screening tool conducts an adapted visual acuity test through a smartphone app and with this data we can determine issues with long-distance vision. Our second vision screening tool requires a photo to be taken of the eyes. We use a heightened flash and high-resolution image to determine whether there is any issue with the direction of the pupils (strabismus) and any other anterior vision issues which can be solved with referral to a local practitioner.

What is unique about your solution and how is it different from what currently exists? 

Our solution is unique because we are able to use a smartphone with no need for physical hardware or attachments. Our software also works in areas with low connectivity, without the data collected being compromised. Our software can also be used by non-medically trained persons, meaning the scalability and reach is huge.  

EYEBOU team for UNICEF engagement

Using Frontier Technology

We believe AI can help screen for and detect these vision issues rapidly from the data we are able to collect. This technology can assist optometrists and be used as a second opinion, as well as speed up the grading process, enabling access by more children to healthcare.  This technology is promising as we have seen its ability to detect vision issues in people where issues were previously undetected.  

We're also developing as Open Source. Being able to work with people in the medical or technology fields to improve our software and work to detect more issues in the future will be beneficial to more people.  

Team and Diversity

Our team covers a range of disciplines and backgrounds, and we are therefore all able to bring different perspectives and skills to the project, which is crucial in a project ranging from data collection to grading to analysis and ML creation.  
The value of our startup is made up by our team. Our team is diverse in background, as well as in skill sets and disciplines, which means we can work together to accomplish huge goals needing multiple skill sets.  

Use of the Investment

We plan to roll out a large-scale social impact project with 10,000 children to screen their vision and collect data to build out our machine learning models. We aim to build powerful AI with accurate detection tools and with this offering, which is incredibly practical and useful, we aim to leverage follow-on investment to build out our business model and roll out with other organizations and clinics.  

Finalizing our open-source business model remains a challenge, but we are looking to network and meet with potential new partners.  

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