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12 November 2025 | Story Onthatile Tikoe | Photo Supplied
CartZA
The CartZA team (from the left): Richard Molefe (CEO), Kenny Netshitanzwani (COO), Tshepo Lencoe (CMO), and Lehlohonolo Molaba Duncan (CTO), UFS students driving innovation through technology.

In an inspiring display of innovation and collaboration, a group of University of the Free State (UFS) students have reimagined campus convenience through CartZA, a student-developed food delivery app that is transforming how students access meals and services. What began as a late-night idea during exam season has grown into one of the university’s proudest examples of student entrepreneurship.

 

From late-night hunger to a campus-wide solution

The idea for CartZA was born in November 2024, when Kenny Netshitanzwani, now Chief Operations Officer, and Tshepo Lencoe, now Chief Marketing Officer, found themselves waiting endlessly in queues at the Thakaneng Bridge during a late-night study session. “We waited nearly 40 minutes just to get food and thought, what if students could order in advance and collect without waiting?” recalls Netshitanzwani.

By December 2024, the two self-taught developers began building a website prototype from their homes. They tested the concept through an online poll that received an overwhelming 97% approval from 425 students. On 27 February 2025, they launched the website during Ms Winnie Sereeco’s entrepreneurship lecture, processing ten orders on the first day and more than a hundred by the end of the semester.

Their pitch attracted Lehlohonolo Molaba Duncan, now Chief Technology Officer – a BCom Finance student and systems architect who joined to develop the mobile app. Later, he introduced Richard Molefe, a BCom Honours in Finance student with strong corporate and leadership experience, who became Chief Executive Officer, completing the CartZA founding team.

 

Turning queues into clicks

By August 2025, the team had launched a fully functional app available on Google Play and the Apple App Store. Within weeks, it had surpassed 1 200 downloads, now exceeding 2 000. The app allows users to order ahead for collection or opt for delivery, with CartZA’s slogan, ‘Add to Cart and Cut the Queue,’ capturing its mission to simplify student life through technology and convenience.

 

Overcoming challenges and gaining recognition

The journey was not without challenges. The team self-funded the project through allowances and side hustles, even borrowing a fellow student’s MacBook, affectionately known as Comfort the Barber, to publish on Apple’s platform. Their breakthrough came when The Deli restaurant joined the platform, expanding access to more outlets.

Their innovation has since gained recognition across the province. CartZA was named among the Free State Top 10 in the Youth Innovation Challenge, hosted by the Young African Entrepreneurs Institute and Absa Bank, and will represent the province at the national finals in November. The team also received the Student Entrepreneurial Excellence Award at the 2025 Executive Director of Student Affairs (EDSA) Prestige Awards.

Beyond convenience, CartZA now employs 15 active student delivery partners and has 30 more registered on standby across Bloemfontein, empowering peers while reshaping campus life.

 

Looking ahead

With plans to expand to other universities, CartZA aims to become a nationwide lifestyle platform connecting students, service providers, and opportunities. “Our journey shows that innovation starts with identifying the needs around you,” says Molefe. “CartZA is proof that when students collaborate and persist, they can create meaningful change.”

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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