Aidence vs Paige AI

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Aidence employs 1-50 people, while Paige AI has 100-500 employees.

Paige AI has raised more in total funding at $125M, compared to Aidence's $20M — a gap of $105M.

Paige AI holds the higher Awaira Score at 65/100, compared to Aidence's 45/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 20-point gap that reflects meaningful differences in scale or traction.

Aidence was founded by Jeroen Vendrig in 2016. Paige AI was founded by Leo Grady in 2018. Visit each company's profile on Awaira for a full founder biography.

Aidence: Aidence develops AI radiology software for lung cancer detection, building CE-marked and FDA-cleared deep learning algorithms that analyse CT scan images to identify and characterise pulmonary nodules requiring clinical follow-up. The Amsterdam company tools assist radiologists in national lung cancer screening programmes and in routine clinical CT reading, providing AI-generated nodule measurements, growth tracking, and malignancy risk scores that reduce reader variability and improve early detection rates.\n\nThe company raised approximately $20 million in venture funding and has deployed its Veye Chest algorithm across multiple European radiology networks and hospital systems participating in national lung cancer screening initiatives. Aidence received CE marking for its software as a medical device and has published clinical validation studies demonstrating performance that is non-inferior to specialist radiologist reads on lung nodule detection tasks.\n\nAidence competes in the AI radiology market alongside Annalise AI, Enlitic, Behold.ai, and Lunit, all of which target chest X-ray and CT reading assistance. The lung cancer screening market has expanded significantly as multiple European countries and the United States have implemented or planned national screening programmes for high-risk smokers, creating a growing workflow automation opportunity for AI lung nodule detection tools. The company was acquired by Coreline Soft, a South Korean medical AI company, as part of a broader consolidation in the AI radiology market. Paige AI: Paige AI develops AI-powered pathology software that assists pathologists in identifying cancer and other diseases in digital whole-slide images. The platform received the first-ever FDA authorization for an AI-based primary diagnostic tool in pathology, a milestone that establishes regulatory precedent for clinical AI deployment in histopathology workflows.\n\nThe company raised approximately 125 million USD and partners with major academic medical centers and pathology laboratories to integrate its diagnostic AI into clinical workflows. Paige has expanded beyond prostate cancer detection into additional cancer types and is building a multi-cancer detection platform intended to function as a comprehensive AI layer across pathology departments.\n\nDigital pathology combined with AI represents one of the clearest near-term commercialization opportunities in medical AI, as the transition from glass slides to whole-slide imaging creates a digital substrate that AI can operate on at scale. Paige FDA clearance creates a significant regulatory moat that competitors must match before selling comparable diagnostic tools in the US market, giving the company a durable first-mover advantage in the AI-augmented pathology workflow.

Aidence was founded first in 2016, giving it 2 years of additional market experience. Paige AI 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.

Aidence has approximately 1-50 employees, while Paige AI 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, Aidence and Paige AI 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.