Zindi, a South African crowd-solving startup has built a community of data scientists. The company is concerned about using AI to solve real-world problems for companies and individuals. It has done that over the last three years of its existence.

Last year, a group of data scientists led by Zindi used machine learning to improve air quality monitoring in Kampala, while another group assisted Zimnat, a Zimbabwean insurance company, in predicting customer behavior, particularly who was most likely to leave and what interventions could persuade them to stay. Zimnat was able to keep its consumers by providing customized services to people who would have left otherwise.

These are some of the solutions that have been developed to address the data-related concerns that businesses, non-governmental organizations, and government agencies have presented to Zindi.

Zindi posts challenges and asks its data scientists to participate in problem-solving competitions. Data scientists who participate submit their solutions, and the winner receives a monetary award. The competition hosts get to use the best outcomes to meet the issue they were given, such as in AirQo’s air quality monitoring project, which sought solutions for forecasting air pollution across Uganda, and in assisting Zimnat in reducing its losses.

“As a result, AirQo now has a dashboard where the public can examine air quality and forecasts. “One of the interesting aspects of this project is that AirQo has engaged two of the competition winners to assist with the project’s execution,” stated Celina Lee, co-founder, and CEO of Zindi. Megan Yates from South Africa and Ekow Duker from Ghana are the platform’s other co-founders.

“AirQo also raised funding from Google based on the solution that they built, and they’ll now be replicating it in other African countries,” Lee said of the competition, which was organized in collaboration with the University of Birmingham’s Digital Air Quality East Africa (DAQ EA) project and Makerere University’s AirQo project.

Microsoft, IBM, and Liquid Telecom UNICEF, and the South African government are among the significant private and public companies that have used Zindi.

Lee is pleased with what Zindi has accomplished thus far and optimistic about the community’s future, given how quickly the crowd-solving startup has developed since its inception. The platform is now providing alternatives and increasing competition against traditionally pricey consulting firms operating across Africa.

Since the beginning of last year, Zindi’s user base has tripled to 33,000 data scientists from 45 nations across Africa. It has also awarded $300,000 in prize money to data scientists.

This number is expected to rise as it prepares to hold the third inter-university Umoja Hack Africa challenge in March of next year, in which college students will compete for various solutions.

The inter-university competition is being used by Zindi to expose students to realistic data science experiences and to tackle real-world problems with AI. Last year’s event drew roughly 2,000 students, despite the fact that the event was held virtually due to the pandemic.

“Students get to develop their first machine learning models, and it opens up all kinds of avenues for their professions and education,” said Lee, a native of San Francisco.

To “shorten the road from studying to earning,” Zindi has created a job platform. By posting job openings on the talent placement platform, businesses can access their talent pool.

After recognizing a knowledge gap and the need for training, the crowd-solving platform plans to incorporate a learning component that would provide training material to aspiring data scientists. Furthermore, according to Lee, the majority of Zindi’s users are university students in need of learning experience and better skills to tackle real-world challenges.

The expanded plans will be made feasible by the platform’s recent $1 million seed funding.

“For us, it’s all about scaling the community and providing more value to all of our data scientists,” Lee explained.

“As a result, we’re going to use the cash to offer a lot more learning content, because one of the things we recognize is that data science is such a young subject, especially in Africa.” And many of our data scientists are still in school or are just starting out in their professions. And all they want is an opportunity to study and improve their talents.”

Shakti, a San Francisco-based venture capital firm, led the seed round, which also included Launch Africa, Founders Factory Africa, and five35.

According to Lee, all of these activities are aimed at developing a strong data science community in Africa and for the continent, with the goal of reaching one million users in the near future. This, she said, will be accomplished through providing early-career data scientists with training opportunities and building a robust community that supports collaboration and mentorship.

“We want to make data science something that every young person interested in pursuing this career has access to the tools, the connections, and the experience that they need to have a successful career in this industry,” Lee said.

“Our goal is to make AI accessible to the general public.”