For a patient with a high genetic risk for breast cancer, a negative mammogram can be a false reprieve. The standard of care, annual or biannual screening, operates on a timeline that cancers can outrun. A new company, medara, is building predictive AI models designed to spot the subtle, longitudinal changes in medical images that could signal a tumor forming, long before it becomes visible to a human radiologist or a single-image AI tool. Its bet is that catching cancer in this short-term window, specifically for patients with negative screenings, can shift outcomes meaningfully [Cornell Tech].
A wedge in the serial image
Medara’s technology emerges from the Sabuncu Lab, a research group spanning Cornell Tech and Weill Cornell Medicine Radiology. The core innovation is an AI system built to detect and quantify clinically relevant changes across a series of medical images over time [news.cornell.edu, 2025]. While many AI tools in breast imaging are built to analyze a single scan, medara’s models are designed for the longitudinal dataset. They analyze sequences of mammograms or MRIs, along with integrated clinical data, to generate a short-term risk score. The target is the high-risk patient whose latest screening came back clear, but whose underlying biology may be quietly shifting toward malignancy [Cornell Tech].
The academic spinout path
Founded in January 2025, medara is a classic academic spinout, having been developed within the Jacobs Technion-Cornell Institute Runway Startup Program at Cornell Tech [Cornell Tech]. The founder and CEO is Kendra Batchelder, PhD, a medical researcher who transitioned from PhD work to founding the company. Her background includes electrical engineering and a prior co-founding role at WAVED Medical [ZoomInfo]. The company’s early credibility is inextricably linked to its institutional roots and the published research underpinning its models.
Navigating a competitive landscape
The market for AI in breast imaging is already active. Medara will encounter competition on multiple fronts:
- Risk stratification incumbents. Companies like Volpara Health and LIBRA have built businesses around breast density assessment and long-term risk prediction.
- The detection pure-plays. Startups like Clairity focus on improving the accuracy of cancer detection in a given scan.
- The platform giants. Larger AI imaging platforms may eventually extend their capabilities into longitudinal analysis.
Medara’s differentiation rests on its specific combination of longitudinal analysis and short-term risk prediction for a narrowly defined, high-stakes population.
The road to clinical utility
The immediate path for medara is one of validation and de-risking. The company has not disclosed funding rounds or early customers. The next twelve months will likely focus on strengthening the clinical evidence for its models, pursuing necessary regulatory clearances, and securing initial pilot partnerships. For patients with BRCA mutations or other high-risk profiles, the clinical promise of a tool like medara’s is not just earlier detection, but a more informed and personalized surveillance schedule that could provide peace of mind or prompt earlier intervention.