Scaling Niramai: Disrupting Breast Cancer Detection Using Artificial Intelligence

The case titled ""Scaling Niramai: Disrupting Breast Cancer Detection using Artificial Intelligence"" describes the relentless efforts of Dr. Geetha Manjunath, the founder of Niramai, to improve early-stage breast cancer detection in women. India was plagued by a lack of medical facilities, poor access to early-stage cancer screening programs, and a lack of awareness of breast cancer in rural areas. These were the primary causes of the high rate of death due to cancer among women, of which breast cancer was a major contributor. The case study explores the different stages of Niramai's journey and poses the key question of what Niramai should do to scale its innovative and crucial offering for marketplace success. Manjunath, a healthcare research scientist, developed an innovative thermal-analytics-based solution to detect early-stage breast cancer. Niramai's innovative product received global recognition; it was the only Indian start-up to be listed on the global business data intelligence platform CB Insights. She had the noble vision of providing an affordable early-stage breast cancer solution to women, especially the underprivileged in the hinterland of the country. Manjunath considered her start-up to be much more than merely a business. The company raised US$7 million from investors for business expansion and growth. Given the potential upside, the opportunities to raise funds and scale globally created a plethora of dilemmas and challenges for Niramai's senior management team. It was a challenge for Niramai to simultaneously balance social impact and financial goals. The case ends with Manjunath and her team contemplating various options to scale Niramai. From an analysis of the case, students will appreciate the need for an organization to develop a framework that helps it analyze the company's current situation, identify opportunities, and make key strategic decisions to boost growth.