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NYC-based recipe management and culinary intelligence platform for professional chefs and restaurant groups; digitizes recipes with costing, scaling, and training tools.
Meez is a recipe management and culinary intelligence platform headquartered in New York City, designed specifically for professional chefs and restaurant groups. Founded by a former chef, Meez takes a culinary-first approach to recipe management, allowing kitchen teams to build digital recipe libraries with precise measurements, costing data, step-by-step photos, and video instructions. The platform aims to standardize culinary execution across restaurant locations and preserve institutional knowledge as kitchen staff turns over.\n\nMeez's platform includes intelligent unit conversion and scaling tools that allow chefs to resize recipes instantly without manual recalculation errors. Its costing module attaches ingredient costs to every recipe and updates automatically when ingredient prices change, giving culinary and finance teams visibility into recipe-level margin. Meez also offers training tools that allow managers to assign recipes to new kitchen staff with quizzes and competency tracking, reducing the time-to-proficiency for new hires.\n\nMeez targets independent restaurant groups, multi-unit operators, hotel culinary teams, and food and beverage consultants who manage large recipe libraries. The platform differentiates from broader food management tools like Apicbase and Crunchtime by focusing on the culinary workflow and chef usability rather than procurement or accounting. Its growing popularity in the culinary community has been driven by word-of-mouth among chefs, making it a rising platform in the restaurant technology stack.
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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