Aidoc vs Niramai

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Aidoc employs 300 people, while Niramai has 50-200 employees.

Aidoc has raised more in total funding at $370M, compared to Niramai's $17M — a gap of $353M. Combined, the two companies have completed 8 known funding rounds.

Aidoc holds the higher Awaira Score at 67/100, compared to Niramai's 60/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 7-point gap that reflects meaningful differences in scale or traction.

Aidoc was founded by Elad Walach in 2016. Niramai was founded by Geetha Manjunath in 2016. Visit each company's profile on Awaira for a full founder biography.

Aidoc: Aidoc is an Israeli artificial intelligence company founded in 2016 that develops clinical decision support software for radiology and medical imaging. The platform uses deep learning algorithms to analyze medical images, prioritize critical findings, and alert radiologists to potential abnormalities, particularly focusing on conditions requiring urgent intervention. Aidoc's core offering integrates into existing hospital workflows and PACS systems, enabling radiologists to identify and triage high-risk cases more efficiently. The company operates in the clinical AI segment, competing with firms like Zebra Medical Vision and Enlitic in automated imaging analysis. Aidoc's technology addresses the growing bottleneck of radiologist workload and diagnostic delays by automating preliminary image screening and flagging priority cases. The platform reportedly covers multiple pathologies including stroke, pulmonary embolism, and other acute conditions. As of the latest available data, Aidoc has secured $370 million in total funding through Series D stage, though its valuation remains not disclosed. The company has expanded internationally and serves healthcare institutions across multiple regions. Aidoc's growth trajectory reflects increasing institutional adoption of AI-assisted diagnostic tools in radiology departments globally, driven by workforce shortages and demand for faster diagnostic turnaround times in clinical settings. Aidoc focuses on clinical workflow integration rather than replacement, embedding AI directly into existing radiology infrastructure to accelerate diagnostic processes. 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.

Both Aidoc and Niramai were founded in the same year — 2016. Despite sharing a founding year, they may have launched at different times within that year, which can matter in fast-moving AI markets.

Aidoc has approximately 300 employees, while Niramai has approximately 50-200. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Aidoc and Niramai 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.