Nabla vs Niramai

Nabla has a disclosed valuation of $180M, while Niramai's valuation is not publicly available, making a direct size comparison difficult. Nabla employs 80 people.

Nabla has raised more in total funding at $30M, compared to Niramai's $17M — a gap of $13M. Combined, the two companies have completed 1 known funding rounds.

Nabla holds the higher Awaira Score at 73/100, compared to Niramai's 60/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 13-point gap that reflects meaningful differences in scale or traction.

Nabla was founded by Alexandre Lebrun in 2018. Niramai was founded by Geetha Manjunath in 2016. Visit each company's profile on Awaira for a full founder biography.

Nabla: Nabla is a French AI health company founded in 2018 that develops artificial intelligence solutions for clinical documentation and patient care workflows. The company has raised $30M in total funding and operates at Series B stage with a valuation of $200M. Nabla's core offering focuses on AI-powered clinical documentation tools designed to reduce administrative burden on healthcare providers. The platform leverages natural language processing and machine learning to automate medical note-taking, allowing physicians to spend more time with patients rather than on paperwork. The company targets hospitals, clinics, and healthcare systems across Europe, with particular strength in the French market. Nabla's technology integrates with existing electronic health record systems and clinical workflows. The company competes in the growing digital health and healthcare AI sector alongside players focused on clinical automation and documentation efficiency. Nabla's approach emphasizes practical integration into existing healthcare infrastructure rather than building standalone applications. The company has demonstrated traction in European healthcare markets where administrative burden on clinicians remains significant. Its Series B funding stage indicates successful product-market fit validation and positions Nabla for expanded market reach and product development in the healthcare AI space. Nabla addresses the specific pain point of clinical documentation burden through AI automation, allowing European healthcare providers to improve operational efficiency. 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.

Niramai was founded first in 2016, giving it 2 years of additional market experience. Nabla was founded later in 2018. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Nabla has approximately 80 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, Nabla 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.