The Pune-based healthcare AI company plans to expand disease screening across three Indian states using an offline mobile application designed for frontline health workers.
Pune-based healthcare artificial intelligence company Froncort.AI has secured $2.3 million in funding from Google.org to expand its AI-powered disease screening technology in India. The company will use the grant to develop a mobile application that helps frontline health workers identify high-risk areas, prioritise households and conduct targeted disease screening.
In addition to the funding, Froncort.AI will receive $200,000 in Google Cloud credits and pro bono technical support from Google. The company is among 15 organisations selected under Google.org's Impact Challenge: AI for Government Innovation.
The funding will support the development of mAI-NETRA, a mobile version of the company's existing AI-NETRA platform. The application is designed to assist health workers in identifying areas with a higher risk of tuberculosis (TB) and other infectious diseases.
The system will combine government health programme data with Google's Earth AI models and local indicators, including population density, land use, rainfall and flooding patterns. These inputs will be used to identify potential disease hotspots and develop screening plans.
According to Froncort.AI, the technology can identify high-risk areas within 300-metre zones and convert the findings into prioritised household clusters and routes for health workers.
The application will operate offline and support local languages, allowing frontline workers to access screening information in areas with limited internet connectivity. The company said government health data would be stored and processed locally in India.
Dr. Ujjwal Rao, Founder and CEO of Froncort.AI, said the platform aims to make specialist knowledge accessible to health workers conducting household-level screening.
The company's approach has previously been evaluated in collaboration with Maharashtra's state tuberculosis programme.
During a Pune-based validation study, AI-guided teams screened 66,095 people and identified 10 confirmed pulmonary TB cases. In comparison, conventional screening covered 177,322 people and identified nine cases.
The findings indicated that AI-guided screening required fewer screenings per confirmed case. According to the company, the estimated cost per confirmed case declined from approximately $29,000 to $10,000, while 92 per cent of participating frontline workers reported a reduced workload.
Froncort.AI plans to expand the platform to cover six diseases, including tuberculosis, leprosy, malaria, dengue, cholera and leptospirosis.
The proposed deployment will cover up to eight high-burden districts across three Indian states, potentially reaching between two million and three million people.
The programme will be independently monitored against targets related to disease detection, screening efficiency, sample transportation, government expenditure and frontline worker earnings.
Froncort.AI also intends to release mAI-NETRA as an open-source blueprint, allowing other governments to adapt the technology for their public health programmes.
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