Side-by-side comparison of AI visibility scores, market position, and capabilities
Yellowstone-derived fungi protein company; $500M+ raised from SoftBank and Al Gore's Generation; makes breakfast patties and cream cheese from Fy protein.
Nature's Fynd is a Chicago-based food technology company founded in 2012 (commercialized 2018) by Thomas Jonas and Mark Kozubal. The company's core innovation is Fy — a novel protein derived from Fusarium strain flavolapis, a microbe originally discovered in the geothermal springs of Yellowstone National Park. Fy can be grown in a compact vertical bioreactor using minimal water, land, and energy compared to conventional animal or plant protein production.\n\nNature's Fynd has raised more than $500 million in venture capital from investors including SoftBank Vision Fund, Generation Investment Management (Al Gore), Breakthrough Energy Ventures (Bill Gates), and others. The company produces a line of consumer products under the Nature's Fynd brand including breakfast patties, dairy-free cream cheese, and yogurt alternatives sold at Whole Foods, Sprouts, and online.\n\nThe company's sustainability story is compelling: Fy protein produces 94% less greenhouse gas emissions and uses 99% less land compared to beef protein. As the broader alternative protein sector faces market headwinds in 2025, Nature's Fynd has focused on building awareness in the natural grocery channel and educating consumers on the unique Yellowstone origin story that differentiates Fy from commodity soy and pea proteins.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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