Topicals vs a2z Radiology AI

Side-by-side comparison of AI visibility scores, market position, and capabilities

Topicals

EmergingConsumer Lifestyle & Wellness

Skincare & Beauty

Clinically formulated skincare brand targeting hyperpigmentation and eczema; $25M raised, sold at Sephora and Ulta, championing inclusive beauty.

About

Topicals is a Los Angeles-based skincare brand founded in 2020 by Olamide Olowe and Claudia Teng. The company focuses on clinically formulated products for skin conditions including hyperpigmentation, eczema, and uneven texture, with an explicit emphasis on inclusive representation for consumers with deeper skin tones who are often underserved by mainstream beauty brands.\n\nTopicals has raised $25 million in total funding across four rounds, including a Series A led by CAVU Consumer Partners with strategic investment from Jay-Z's Marcy Venture Partners and Kelly Rowland. The brand is available at Sephora, Ulta Beauty, and directly through its website, expanding its omnichannel footprint since initial DTC-only launch.\n\nThe brand's marketing is deliberately rooted in mental health, body positivity, and destigmatizing chronic skin conditions — themes resonating strongly with Gen Z consumers. Topicals has become one of the fastest-growing indie skincare brands in the US, earning recognition on Fast Company's Brands That Matter list in 2025 and building a loyal community through social-first campaigns and clinical transparency about active ingredients.

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a2z Radiology AI

EmergingEnterprise AI

Medical Imaging AI

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.

About

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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