Scoping the ecosystem
For an initiative to be included into our ecosystem map, it needs to either generate a technical solution based on AI technology (AI product) or further enable its development by means of funding, skilling or networking opportunities (AI enabler). As such, we look at start-ups, companies, research labs, funding opportunities as well as a wide range of communities ranging from professional associations, industry conferences and initiatives to informal meetups and networks. We take this broad approach because a comprehensive scope of the AI landscape cannot be limited to AI technology and products in isolation.
While our map-out identifies core components and key players in the system, it is by no means final or comprehensive. Rather, we consider this mapping exercise to be a snapshot of a dynamic system that continually evolves. To reflect this, we will continually update this database and look forward to entries of new initiatives.
New initiatives can register here
Featured initiatives
CHIL AI Lab
CHIL AI Lab’s flagship product is a mobile application that leverages artificial intelligence to diagnose both, cervical and breast cancer. The company has also created machine learning-powered self-testing kits to make it easier to scale its service and reach the underserved.
Wefarm
Wefarm is the world’s largest digital farmer-to-farmer network which helps farmers share agricultural information with each other online or via SMS. Farmers can query the network about agricultural information they look for. Wefarm’s natural language processing libraries can identify three regional African languages – Kiswahili, Luganda, and Runyankore – in addition to English. Wefarm’s machine learning algorithms then match each question to the best-suited responder. The average time it takes for a farmer to receive an answer to their question is under six minutes – even for farmers without internet. This way, the wefarm network enables small-scale farmers to access crowdsourced information and to share techniques and advice on a wide topic range.
Women in Machine Learning & Data Science
WiMLDS has the mission to support and promote women and gender minorities who are practicing, studying or are interested in the fields of machine learning and data science. By hosting talks as well as technical workshops, networking events and hackathons, WiMLDS aims to create opportunities for members to engage in technical and professional conversations in a supportive environment. The Kampala chapter is headed by Anne Namuli and Viola Nuwaha.
Ocula
Ocula is a point-of-care diagnostic tool for microscopically diagnosed diseases including malaria, tuberculosis, intestinal parasites and blood anemia. It works through a custom-developed smartphone application that is able to attach to a microscope. Using Machine Learning to process the smartphone images from the microscope eye piece, this tool improves disease diagnosis both in terms of speed and accuracy. Additionally, it can facilitate teaching.
