Froncort.AI Secures $2.3M from Google.org to Scale AI Disease Screening Across India

Froncort.AI Receives Google.org Funding to Transform Disease Detection

Pune-based healthcare AI startup Froncort.AI has secured $2.3 million in Google.org funding to expand its AI disease screening capabilities across India1

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. The support package includes $200,000 in Google Cloud credits and pro bono technical expertise from Google's AI specialists1

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. Founded in 2024 by physician-scientist Dr. Ujjwal Rao, Froncort.AI was selected among 15 global recipients for Google.org's Impact Challenge: AI for Government Innovation, building on Google's previous backing for the company's AI-NETRA validation study1

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AI-NETRA Platform Demonstrates Remarkable Efficiency in Tuberculosis Screening

The AI-based disease surveillance platform AI-NETRA has shown promising results in Maharashtra's state TB programme. In a published Pune pilot report, AI-guided teams screened 66,095 people and identified 10 bacteriologically confirmed, NAAT-positive pulmonary TB cases, while standard screening campaigns covered 177,322 people to identify nine cases1

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. This translated to 6,610 people screened per confirmed case in the AI-guided approach, compared with 19,702 under standard screening methods1

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. The cost reduction proved equally significant, with costs per confirmed case dropping from approximately $29,000 to $10,0001

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. Notably, 92% of participating frontline health workers reported experiencing lower workload2

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Mobile Version mAI-NETRA to Target Six Infectious Diseases

The Google.org funding will support development of mAI-NETRA, a mobile version designed to help frontline health workers identify high-risk areas for tuberculosis and other infectious diseases1

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. The platform combines government health programme data with Google Earth AI models and local indicators including settlement density, land use, rainfall and flooding1

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. The application identifies high-risk areas within 300-metre zones and converts them into ranked work paths, household clusters and routes for health workers1

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. Designed to work offline and in local languages, the mobile application allows workers to access screening plans directly on their phones1

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. All government health data will be stored and processed locally in India to ensure compliance and security1

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. The platform will extend beyond tuberculosis to cover six infectious diseases: TB, leprosy, malaria, dengue, cholera and leptospirosis1

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Ambitious Deployment Plans and Public Health Innovation Goals

Froncort.AI plans to deploy the application across up to eight high-burden districts in three Indian states, covering two to three million people1

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. The deployment will be independently monitored against five targets: finding at least 20% more cases, reducing the number of people screened per case by more than 50%, faster sample transportation, lower government costs per case detected, and higher performance-based earnings for frontline health workers1

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. Dr. Ujjwal Rao explained the vision: "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"1

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. The company plans to publish mAI-NETRA as an open-source platform blueprint, allowing other governments to adopt and adapt the technology for their public health programmes1

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. This funding arrives as AI deployment in India's public healthcare infrastructure gains momentum, with the government reporting a 27% decline in adverse TB outcomes through AI-enabled tools within the National TB Elimination Programme2

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. AI funding in India grew 235% year-over-year in Q3 2025, reflecting growing investor confidence in the sector2

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