The result is Ezra (Hebrew for “help”), the full-body MRI scanning company Gal founded in 2018. In 2025, it was acquired by Function Health, a personalized health-testing platform, and the cost of an Ezra scan fell from $1,500 to $499. The basic MRI scan, which takes less than 30 minutes, images the head, neck, abdomen, and pelvis and can identify more than 500 potential conditions, including cancers in those areas. It also looks for signs of stroke, sinus inflammation, fatty liver disease, gallstones, uterine fibroids, kidney stones, abdominal aortic aneurysm, and more. The company relies heavily on AI to interpret images and identify potential issues, though board-certified radiologists also review Ezra scans.
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Over the past few years—buoyed in part by celebrity endorsements—full-body MRIs have become a health trend. In addition to Ezra, companies like Prenuvo and simonONE offer such scans at various price points. Still, no major medical association recommends a full-body MRI as preventive care, especially for people with no symptoms or unique risks. In those cases, there’s a good chance you’ll find out about an abnormality that isn’t actually anything to worry about, kicking off anxiety, more medical appointments, and potentially unnecessary interventions that carry risks of their own. (According to Ezra, nearly 5% of clients have had a highly suspicious finding for cancer that requires additional follow-up.)
Yet to Gal—who has long enjoyed treating himself as a guinea pig for longevity hacks—more information is always a good thing. As part of TIME’s series interviewing leaders in the longevity field, we caught up with him to talk about how the Ezra scan works, what the company says it does to minimize false positives, and how he tries to optimize his own health.
This interview has been condensed and edited for clarity.
How exactly does Ezra work?
We have three AIs at Ezra that we use. No. 1 is called Ezra Flash. It enables us to acquire MRI images faster and then enhance their quality. The challenge with MRIs is that it’s a very “noisy” environment, and so to make the scan more high-signal, you need to scan multiple times, which adds time. We just do the scan once, and then we use AI to remove the noise. It allows us to acquire MRI images much faster.