Side-by-side comparison of AI visibility scores, market position, and capabilities
Fastest-growing US greenhouse lettuce brand; $100M+ retail sales, world's largest CEA leafy greens producer after 2025 PA campus expansion.
Little Leaf Farms is a Devens, Massachusetts-based indoor greenhouse farming company founded in 2015 by Paul Sellew. The company grows baby lettuce, arugula, and salad greens in purpose-built greenhouse facilities that use hydroponic growing systems, natural sunlight supplemented by LED lighting, and closed-loop water recycling. Little Leaf Farms raised $300 million in capital in 2022 from The Rise Fund (TPG) and Bank of America.\n\nThe company broke $100 million in annual retail sales in 2023 and has continued rapid expansion, with major new facilities announced in Texas, Georgia, and Pennsylvania. In October 2025, Little Leaf Farms completed a major expansion of its Pennsylvania campus that made it the world's largest controlled environment agriculture (CEA) leafy greens producer by square footage. New facilities in Tennessee were also announced in 2025, creating hundreds of jobs and investing approximately $75 million.\n\nUnlike high-tech vertical farming startups that struggled with energy costs, Little Leaf Farms' greenhouse model leverages natural sunlight, which dramatically reduces electricity consumption. This structural cost advantage, combined with disciplined geographic expansion targeting high-density markets, has allowed the company to scale profitably while competitors collapsed.
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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