The company, founded in 2020, is developing screening solutions designed for use in low-resource settings where access to diagnostic infrastructure remains limited.

Its core product combines a digital stethoscope, known as Ostium, with proprietary AI software that analyses lung sounds to identify patterns linked to TB.

The system is built for use by frontline healthcare workers, allowing early screening without reliance on X-rays or specialist clinicians.

The latest funding round was led by The Steele Foundation for Hope, with participation from the iFSP Group and the Global Innovation Fund.

Existing backers, including Africa Health Ventures and Savant, also contributed additional capital.

AI Diagnostics said the investment will be directed towards clinical validation studies, further development of its hardware and software, and strengthening operational capacity to support expansion across South Africa, other parts of sub-Saharan Africa, and selected markets in Asia.

South Africa remains one of the countries most affected by TB globally, with an estimated 249,000 infections and 54,000 deaths recorded in 2024 alone.

A significant challenge is that many cases go undetected due to limited access to diagnostic tools and the high proportion of patients who show no symptoms, making traditional screening methods less effective.

Investors backing the company argue that the approach addresses a long-standing gap in healthcare delivery.

“We back technical entrepreneurs who are closest to the problems they’re solving, and AI Diagnostics is a clear example of why that matters,” said Joe Exner, CEO of The Steele Foundation for Hope.

“They’ve built novel hardware: an AI-enabled digital stethoscope that detects TB through lung sound analysis with point-of-care accuracy that simply wasn’t possible before. In communities without X-ray infrastructure or specialist clinicians, this puts real diagnostic capability in the hands of nurses and community health workers.”

The company’s model is focused on decentralizing screening. By shifting the initial detection process closer to where patients first seek care, AI Diagnostics aims to reduce delays in diagnosis and treatment. According to CEO Braden van Breda, the system is designed to identify potential cases instantly during routine check-ups.

“The AI model flags individuals whose lung sounds have signals associated with TB in real time so healthcare providers can refer them for diagnostic testing immediately,” he said. “For health systems trying to close the detection gap, this changes the availability and the geography of screening.”

AI Diagnostics has already received approval from the South African Health Products Regulatory Authority and has screened more than 1,000 patients locally.

The company is also running clinical research programmes in over ten countries across Africa and Asia as it prepares for broader deployment of its technology.