In the modest town of Parbhani, Maharashtra, an unusual medical event unfolded—one that reflects the future of diagnostics in India’s smaller towns.
A child was brought to Dr. Chaitanya Killarikar’s clinic with common symptoms—fatigue, fever, and a skin infection. Initial blood tests seemed normal, and a local lab concluded it wasn’t serious. But Dr. Chaitanya, relying on his training and experience, had doubts. He decided to re-examine the blood smear using the SigTuple AI100 scanner, a tool powered by artificial intelligence (AI) that analyzes blood samples with remarkable precision.
What the AI system revealed was shocking: clear signs of acute leukaemia, a diagnosis missed by manual review.
Dr. Chaitanya immediately escalated the case. The boy was referred to a government hospital over 200 km away. There, a pathologist confirmed the AI’s finding. The child was promptly admitted, and treatment began.
The early detection proved lifesaving.
Small towns like Parbhani often lack trained pathologists, and lab technicians may be overburdened or under-resourced. As a result, misdiagnosis or delays in treatment are not uncommon.
This is where tools like SigTuple come in.
Founded by Tathagato Rai Dastidar, SigTuple develops AI-based diagnostic tools that automate microscope analysis. The AI100 device not only scans blood smears but also assists in identifying abnormalities with consistency and speed.
“We started SigTuple with the aim of making life easier for pathologists with AI, and thereby help the end patient. Our AI helps reduce the turnaround time for diagnosis, makes diagnosis more accurate and reliable, and enables pathologists to remotely review samples without physically traveling to the laboratory. It is a huge shot in the arm for us to see that vision unfold in front of our eyes, in small towns such as Parbhani.” says Dastidar.
AI doesn’t replace human expertise, but it acts as a second pair of eyes—especially useful when specialists are unavailable.
SigTuple’s AI scanner has now been deployed in several labs across India. It’s part of a growing movement to make digital pathology accessible in tier-2 and tier-3 cities, ensuring no child’s illness goes undiagnosed simply because of location.
Dr. Chaitanya, who has integrated AI-based diagnostics into his practice for several years, noted that the tool has transformed his clinical approach. He explained that where once he relied solely on his microscope and professional judgment, he now benefits from a technological safety net that verifies and supports his assessments.
As India aims to improve healthcare outcomes beyond urban centers, AI tools offer a way to standardize diagnosis, reduce errors, and enhance trust in medical systems—even in remote settings.
What happened in Parbhani isn’t just a case study—it’s a glimpse into how technology can democratize healthcare.