UNICEF invests in AI-powered education and health system solutions
Nine startups developing digital solutions to improve access to and delivery of digital services and systems join the UNICEF Venture Fund
The UNICEF Venture Fund invests in nine new startups developing Open Source, artificial intelligence (AI) and machine learning technology platforms for accelerating learning outcomes, generating data to forecast health and healthcare needs, and providing access to online tools at lower costs and in low connectivity settings.
The new cohort will receive equity-free investments in USD and/or cryptocurrency through the UNICEF Venture Fund and UNICEF CryptoFund and year-long mentorship with UNICEF’s technical and programme experts and partners.
Five of nine startups in this round of investments are female founded/co-founded, bringing the Fund’s overall female-led/founded portfolio composition to 43%. The cohort also expands the Fund’s geographic reach to Indonesia and the UAE.
COVID-19 has put a spotlight on the digital divide within and between countries and regions, making access to digital platforms and services a key priority. The growth of technology and online tools means we can deliver learning, health and psycho-social support opportunities anywhere, at any time. The Fund received more than 450 submissions from over 75 UNICEF programme countries.

Jobzi (Brazil) is a data intelligence company focusing on human capital markets and connectivity. They are developing a solution to predict school connectivity and to analyse the relationship between connectivity and employment.

Portal Telemedicina (Brazil) is developing a platform that provides fast, reliable, and low-cost diagnostics to over 300 cities in Brazil and Africa, by enabling doctors to make online diagnoses, leveraging an artificial intelligence (AI) integrated layer and AI insights for medical providers.

Cirrolytix (Philippines) is developing a platform for dengue prediction using climate and health data for epidemic management. Their solution has been recognized as a digital public good (DPG).

Eyebou (UAE) is 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.

Neural Labs (Kenya) is developing a computer vision and image recognition algorithm to detect diseases through chest X-rays.

Bookbot Technology (Indonesia) is developing a gamified app leveraging real-time, on-device speech recognition technology that listens to the user reading out loud, providing feedback through pronunciation modeling.

AfriLearn (Nigeria) is developing an application for accessible, adaptive learning, aligned with national curricula. The prototype developed includes audio, video, practical quizzes, and class notes for all lessons.

Om3ga (Serbia) is developing a deep learning, virtual speech-to-text solution integrated with a chatbot builder. The app currently supports Serbian, Bosnian, Croatian, and Montenegrin, with Russian in development. It also works offline, making it possible for children with disabilities to communicate, even in remote areas without Internet access and when they are on the move.

AQAI (India) is developing a machine learning predictive model for air quality, delivered using an open source geographic visualisation engine comprised of layers showing child population density against regions with concentrations above WHO-recommended limits.
About the UNICEF Venture Fund
Launched in 2016, the Fund is specifically designed to finance early stage, open source technology that can benefit children. The core motivation of the Venture Fund is to identify “clusters” or portfolios of initiatives around emerging technology - so that UNICEF can both shape markets and learn about and guide these technologies to benefit children. We invest in solutions clustered around $100 billion industries in frontier technology spaces, such as: blockchain, virtual and augmented reality, machine learning, and artificial intelligence.