Gleamer, a French startup specializing in AI-enhanced medical imaging, is broadening its capabilities by moving into magnetic resonance imaging (MRI). After developing AI tools for X-rays and mammographies, the company is expanding its reach through the acquisition of Caerus Medical and a merger with Pixyl.
Medical imaging is a complex field that involves multiple technologies. While AI-driven solutions have gained traction since the mid-2010s, many early startups failed to scale. However, Gleamer has emerged as a leader, following in the footsteps of companies like Nanox and Tempus, which have driven consolidation in the sector.
Founded in 2017, Gleamer has developed an AI assistant for radiologists, serving as a diagnostic copilot for medical imaging. The technology enhances accuracy and efficiency, helping radiologists make faster and more reliable interpretations of medical scans.
The startup has already convinced 2,000 institutions across 45 countries to adopt its software, processing over 35 million examinations. It has received CE and FDA certifications for its bone trauma interpretation tool and offers AI-powered solutions for chest X-rays, orthopedic imaging, and bone age assessments in Europe.
Expanding into MRI with Strategic Acquisitions
MRI is an entirely different technological landscape compared to X-rays or mammographies. It involves multiple functions, including segmentation, detection, characterization, classification, and multi-sequence imaging. Rather than building from the ground up, Gleamer is acquiring Caerus Medical and merging with Pixyl, two companies with years of expertise in AI-driven MRI analysis.
“These two companies will become our core MRI platforms, with the goal of covering all MRI use cases within the next two to three years,” said Christian Allouche, Gleamer’s co-founder and CEO. The company has not disclosed financial details of these acquisitions.
AI-powered imaging is not just about improving diagnostics—it’s shaping the future of preventive healthcare. While Gleamer’s technology already shows impressive results, AI models are still evolving. For example, its mammography tool detects four out of five cancers, whereas human radiologists typically identify three out of five cases without AI assistance.
Despite AI’s limitations, its potential to enhance efficiency and reduce diagnostic errors is game-changing. A missed tumor today may resurface in a follow-up exam months later, but AI-driven solutions could help catch these issues earlier.
“In the near future, routine whole-body MRIs could become standard practice, covered by insurance providers, as they don’t involve radiation exposure,” Allouche predicted.
However, the demand for radiologists is already exceeding supply in many cities. If the industry moves toward preventive imaging, AI will be essential for managing the increased workload efficiently.
AI as the Future of Medical Imaging
Looking ahead, Gleamer envisions AI as an orchestrating and triaging tool in medical imaging. Many radiological exams are conducted to rule out diagnoses, meaning automation could drastically reduce human workload while improving sensitivity levels beyond those of human specialists.
“So, there’s a real need to automate all of this with a solid AI model that delivers a much higher level of sensitivity than a human alone,” said Allouche.
By integrating MRI into its suite of AI-driven imaging tools, Gleamer is positioning itself at the forefront of the medical imaging revolution—one that could fundamentally reshape how healthcare providers detect and prevent diseases.
