In 2016 alone, startups across Africa raised $129 million in funding, a 16.8% increase in the number of of successfully funded startups in 2015. South Africa, Nigeria and Kenya account for 80.3% of the total funds raised and Egypt saw a 100% increase in startup funding, making it the fourth ranked startup destination. It’s not just in these countries; startup success has been developing across Africa.
Although the pandemic has shifted the landscape, we thought we’d share 5 of what we think are the most dynamic and exciting startups emerging from Africa.
Instabug: Egypt’s Instabug allows users to offer feedback from within apps to report bugs found when using the apps, using in-app conversations, crash reporting and advanced analytics. By June 2016, the startup had closed a $1.7 million seed round led by Accel Partners. To date, Instabug has been used to report over 20 million bugs already.
RoamSmart: Created in Tunisia, this tech startup’s aim is to assist mobile operators to manage their roaming businesses more efficiently. They help operators optimise workflows and monetise existing roaming sources through an automated data reporting and analysis platform. They already help out Vodacom and Orange and secured its first funding round in 2016.
Tutorama: This educational-tech startup from Egypt is a platform developed to connect parents with top quality tutors in their area. Parents can use the startup to pay for the tutoring sessions and to monitor their child’s progress online. Tutorama won first place in the ideas track of the MIT Enterprise Forum Arab Startup Competition, securing $50,000!
Jamii: Developed in Tanzania, this offers a mobile micro-health insurance product for the low income and informal sector. They’ve built a mobile policy management platform that acts as an insurer to allow users to access cheap insurance through USSD. They’ve already received backing from the Bill and Melinda Gates Foundation
Dr CADx: From Zimbabwe, Dr CADx is developing a computer-aided diagnostic system to help doctors diagnose medical images more accurately and to provide pervasive radiology diagnostics in regions that don’t have radiologists. So far, their prototype has achieved an accuracy of 82% in distinguishing between chest X-rays of healthy people from X-rays of patients with TB and those with lung cancer.
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