Meet the Startups Behind India's Offline AI Bet

Power constraints and patchy networks make cloud AI unreliable in India. Offline AI sidesteps those challenges

- Shadma Shaikh

BENGALURU Back in 2020, as the covid-19 pandemic swept across the world and overwhelmed healthcare systems, Qure.ai, a medical diagnostic startup, was field-testing its most promising leap in medical artificial intelligence (AI): a software that could detect signs of tuberculosis and lung cancer from chest X-rays with high accuracy.

But there was a catch. Each scan, roughly 100 MB in size, had to be uploaded to the cloud, processed and the results sent back. This cycle was time-consuming because of internet connectivity issues and power outages, common to rural areas. It resulted in a long line of patients waiting for results. The delayed scan reports made it harder to isolate a patient or start treatment in time.

This was a reminder of the mismatch between cutting-edge AI and the ground realities it was built for.

"If you're building healthcare solutions for the Global South, you have to assume the testing conditions are far from ideal. The internet will be patchy. Electricity supply will be irregular. Machines need to have longer battery lives to last at least a day," said Prashant Warier, co-founder of Qure.ai.

So, the team found a way to re-engineer their system. Instead of directing every scan through the cloud, they embedded the AI model directly onto local laptops attached to X-ray equipment, making the diagnostics system work even in offline mode. These laptops with 'edge AI' chips handled the heavy computing needed to analyze the scans on the spot, in under 20 seconds.

Today, Qure.ai partners with more than 15 medical device makers to embed AI directly into edge devices, making advanced diagnostics practical in places where stable internet connectivity is still a luxury. In 2025, the company announced it had crossed five million AI-enabled chest X-rays across 20 countries in Asia, Africa, the Middle East and Latin America.