Niramai vs SigTuple

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Niramai employs 50-200 people, while SigTuple has 100-500 employees.

SigTuple has raised more in total funding at $20M, compared to Niramai's $17M — a gap of $3M.

Both Niramai and SigTuple share the same Awaira Score of 60/100. The Awaira Score is a composite metric that factors in valuation, total funding raised, company stage, employee count, and market category.

Niramai was founded by Geetha Manjunath in 2016. SigTuple was founded by Rohit Kumar Pandey in 2015. Visit each company's profile on Awaira for a full founder biography.

Niramai: Niramai has developed a radiation-free, non-contact breast cancer screening solution that uses thermal imaging combined with AI-powered image analysis to detect early-stage breast cancer, addressing the significant access and cost barriers that prevent widespread mammography screening in low- and middle-income countries. The technology works without X-ray radiation, requires no radiologist for initial interpretation, and can be deployed in mobile screening units.\n\nThe company raised approximately $17M in Series B funding and has conducted clinical validation studies demonstrating sensitivity and specificity metrics competitive with mammography for early detection. Niramai has deployed its screening solution at hospitals, corporate wellness programs, and rural health camps across India.\n\nBreast cancer is the most common cancer among Indian women, yet screening rates remain critically low due to equipment costs, specialist shortages, and cultural barriers to mammography. Niramai's AI-powered thermal screening addresses each of these barriers simultaneously, positioning the company at the intersection of AI healthcare innovation and a major Indian public health challenge. SigTuple: SigTuple develops AI-powered automated pathology solutions that digitize and analyze microscopy slides for blood, urine, sputum, and semen samples, enabling high-throughput diagnostic testing without the constant presence of trained pathologists. The company's AI-Minth platform uses robotic sample preparation, high-resolution imaging, and deep learning analysis to deliver diagnostic-grade results.\n\nThe company raised approximately $20M in Series B funding and has deployed its automated microscopy systems at diagnostic labs, hospitals, and blood banks across India, processing millions of diagnostic samples. SigTuple has received regulatory approvals for its diagnostic AI products and has established partnerships with major diagnostic laboratory chains.\n\nIndia faces a severe shortage of qualified pathologists relative to population, creating an acute need for AI-assisted diagnostic automation. SigTuple's approach of combining hardware, robotics, and AI in an integrated system addresses the complete diagnostic workflow rather than just the software layer, creating higher deployment barriers but also higher switching costs and stronger network effects from accumulated diagnostic data.

SigTuple was founded first in 2015, giving it 1 year of additional market experience. Niramai was founded later in 2016. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Niramai has approximately 50-200 employees, while SigTuple has approximately 100-500. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Niramai and SigTuple are direct competitors — both operate in the AI Healthcare space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.