Froncort.AI Secures $2.3 Mn Google.org Grant to Scale AI-Based TB Screening in India

The planned rollout will cover two to three million people across up to eight high-burden districts in three Indian states.

Pune-based healthcare AI startup Froncort.AI has secured a $2.3 Mn grant from Google.org to expand AI-guided tuberculosis (TB) screening in India.

The funding will support mAI-NETRA, an offline-first mobile application designed to help frontline health workers prioritise households at higher risk of TB.

“The world does not lack experts. It lacks their reach. AI-NETRA puts that expertise in the health worker’s hands at the door: where to go, whom to screen, and when. Google.org brings more than funding: Google’s Earth AI models and engineers we wouldn’t have access to. Add our clinicians’ judgment and a startup’s speed, and the world’s 2030 goal of ending these epidemics comes back within reach,” Dr Ujjwal Rao, Founder and CEO of Froncort.AI, said.

Froncort.AI's mAI-NETRA is the mobile application built around its AI-NETRA geospatial intelligence platform. It combines government health programme data with satellite-derived insights from Google's Earth AI models and local environmental indicators, including settlement density, land use, rainfall and flood exposure.

The system identifies high-risk areas within geographic zones as small as 300 metres and generates prioritised routes for health workers to follow during field visits.

The application is designed to operate offline and support local languages, allowing frontline workers to use their own mobile phones.

While Google's models provide satellite and environmental insights, government health programme data and patient records remain stored and processed within India's domestic infrastructure.

The planned rollout will cover two to three million people across up to eight high-burden districts in three Indian states.

The initiative will also provide an open-source blueprint that other governments can adapt for public health screening. TB is the initial focus, with Froncort.AI identifying leprosy, malaria and dengue as potential future applications.

Froncort.AI is one of 15 recipients selected from more than 2,600 proposals for Google.org's $30 Mn Impact Challenge: AI for Government Innovation. The support includes $200,000 in Google Cloud credits and pro bono engineering expertise, building on Google.org's backing of an initial AI-NETRA validation study in 2025.

Early results from Pune have indicated improvements in screening efficiency. Data from the pilot, which involved the Maharashtra State TB Cell and FIND, showed that the proportion of confirmed cases among presumptive TB patients increased from 1.2% to 4.3% under AI-guided targeting. Additionally, 92% of participating frontline workers reported a reduction in workload.

The wider rollout will be independently assessed against five performance targets, including finding at least 20% more TB cases, reducing the number of people screened per confirmed case by more than 50%, speeding up sample transportation, lowering detection costs and improving performance-based earnings for frontline workers.

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