Side-by-side comparison of AI visibility scores, market position, and capabilities
Pequity is a compensation management platform for equitable pay decisions, raised $11M+ in San Francisco.
Pequity was founded in 2020 in San Francisco by Kaitlyn Knopp, a former compensation leader at Google and Cruise, who built the platform based on her experience designing compensation systems at scale inside large technology companies. The company raised over $11M to bring compensation management tools previously available only to large enterprises down-market to mid-sized and growth-stage companies, with pay equity as a core design principle throughout the platform.\n\nThe platform provides compensation band management, offer generation and approval workflows, merit cycle planning, and equity compensation modeling. Pequity's band management system is built to be easily maintained and communicated to employees, supporting the growing expectation of pay transparency in the technology sector. The platform also includes robust analytics that allow HR and finance teams to audit compensation decisions for potential bias across gender, ethnicity, and other demographic dimensions.\n\nPequity integrates with ATS systems and HRIS platforms to pull candidate and employee data into compensation workflows automatically, reducing manual data entry and the risk of errors in offer calculations. The company targets technology companies with 100 to 2,000 employees that are building out formal compensation programs for the first time, competing with Assemble, Pave, and Ravio in the emerging compensation technology category.
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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