While India has one of the world’s most affordable healthcare facilities, for many, accessibility is tough, and the costs are still high. Apart from finances, many deal with crowded diagnostic labs and wait times.
A new wave of AI-powered healthtech startups, however, is rewriting that experience by making diagnostics faster, cheaper, and more accessible, especially for people living in non-metro regions.
Using technologies like machine learning, computer vision, portable diagnostic devices, and cloud-based platforms, these companies are turning complex lab tests into quick, point-of-care solutions.
AI algorithms can now read X-rays, MRIs, or CT scans in minutes with accuracy comparable to radiologists, while smart diagnostic kits detect conditions like anemia, diabetes, or infections on the spot. Some startups even integrate wearable sensors and smartphone-based imaging, enabling continuous health monitoring outside hospitals.
The impact is profound. Among other things, AI promises to lower testing costs, bridge doctor shortages, and give millions in Tier II and III cities access to reliable diagnostics. What was once limited to urban labs is now reaching villages, powered by AI.
Here’s a look at the innovators who are making healthcare diagnostics smarter and more inclusive.
Qure.ai
Qure.ai, founded in 2016 by Prashant Warier, is a Mumbai-based health technology startup with an additional headquarters in New York. The startup develops AI tools to interpret medical imaging such as X-rays, CT scans, and ultrasounds, helping clinicians detect conditions like tuberculosis, lung cancer, COPD, stroke, heart failure, and traumatic brain injuries.
Its flagship product, qXR, can analyse chest X-rays in under a minute to identify more than 50 abnormalities, while other algorithms support neurocritical care and emergency cases.
Qure.ai’s technology integrates with hospital systems and is used across clinics and hospitals on both pay-per-use and on-premises models, enabling quicker diagnosis and reducing pressure on radiologists. Its products are certified by regulatory bodies, including the US FDA and CE, and have been recommended by the WHO.
SigTuple
, founded in Bengaluru in 2015 by Tathagato Rai Dastidar, Rohit Kumar Pandey, Apurv Anand, and Pranat Bhadani, develops AI-driven diagnostic solutions that automate microscopic examination of biological samples such as blood, urine, and semen. Its flagship product, AI100, combines digital microscopy with cloud-based AI algorithms to analyse samples, helping reduce turnaround times and minimize manual errors.
The integration of robotics and microfluidics further automates sample handling, lowering operational costs and easing reliance on routine manual work.
By enabling remote analysis and supporting diagnostic workflows, SigTuple’s technology is aimed at making medical testing faster, more accurate, and accessible, particularly in regions with limited access to pathologists.
The startup has secured patents, partnerships with hospital networks, and in 2023 received US FDA clearance for its AI100 platform with the Shonit™ model.
AarogyaAI
, founded in 2019 in Bangalore by Dr. Praapti Jayaswal and Avlokita Tiwari, develops AI- and genomics-based tools for diagnosing antimicrobial resistance, with a focus on diseases such as tuberculosis. Its platform, AAICare, analyses genomic sequencing data from patient samples to identify pathogens and their drug susceptibility profiles, significantly reducing diagnosis time from weeks to hours.
The system also detects novel genetic mutations linked to drug resistance, enabling more accurate treatment decisions. Built on AWS cloud infrastructure, AarogyaAI’s pipelines use tools like SageMaker for model development and deployment.
The startup works with clinical and commercial partners and is backed by investors including Redstart Labs and Entrepreneur First UK, with the broader aim of making advanced diagnostics more accessible and contributing to improved infectious disease management.
Docturnal
, a Hyderabad-based healthcare technology startup founded in 2016, develops non-invasive, point-of-care diagnostic solutions for lung health. Its tools use machine learning to analyse cough sounds and clinical data for early screening of conditions such as tuberculosis, pneumonia, COVID-19, Chronic Obstructive Pulmonary Disease, and asthma.
The startup’s flagship product, TimBre, screens for TB without relying on sputum or skin tests, providing real-time results that improve accessibility in resource-limited settings. Alongside TB, Docturnal is working on solutions for other infectious and chronic respiratory diseases.
The startup was founded by Rahul Pathri, Balakrishna Bagadi, Arpita Singh, and Vaishnvi Reddy Gutha, and is headquartered at T-Hub, Hyderabad.
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Endimension Technology
Technology, founded in 2018 and incubated at IIT Bombay, is a healthcare AI startup working on radiology-focused solutions. The startup develops algorithms that analyze medical scans such as X-rays, CT scans, and MRIs to detect abnormalities, assist diagnosis, and ease the workload of radiologists.
Its cloud-based platform integrates with existing workflows to provide automated analysis, reporting support, and quantitative insights. Endimension’s tools are currently used in over 350 imaging centress with more than 1,000 installations, impacting over 1 million patients across India. The founding team includes Bharadwaj Kss (CEO), Apparao MLV (COO), and Kurien Zacharia.
Hearzap
, founded in 2019 by S. Raja and based in Hyderabad, is a digital hearing care platform that provides assessments, consultations, and hearing aid devices through online platforms, clinics, and home visits.
The startup uses AI-driven diagnostics to enable faster and more accurate detection of hearing loss, reducing waiting times and clinical visits. Users can book tests, consult certified audiologists, and access after-sales support via the Hearzap app or physical centers.
By combining digital tools with audiology expertise, Hearzap aims to make hearing care more accessible and cost-efficient across urban and semi-urban regions.
Edited by Affirunisa Kankudti
