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AI optimization software for transportation and logistics operations. Phoenix, AZ. Products cover driver planning, load matching, and network optimization for trucking and rail.
Optym is a Phoenix, Arizona-based transportation optimization software company that applies operations research and AI to solve complex scheduling, routing, and resource allocation problems for trucking companies, railroads, and logistics operators. Founded by academics and operations research experts, Optym has built a portfolio of optimization products that span driver scheduling, load planning, and network design for large-scale transportation enterprises.\n\nThe company's HosOptimizer product automates Hours of Service-compliant driver scheduling for truckload carriers, reducing empty miles and improving asset utilization. Optym also offers locomotive planning and crew scheduling solutions for Class I and regional railroads, applying constraint-based optimization models to one of the most complex scheduling problems in transportation.\n\nOptym serves some of the largest transportation companies in North America, including major truckload carriers and several Class I railroads. The company's specialized expertise in mathematical optimization distinguishes it from general-purpose logistics software providers, and its solutions deliver measurable efficiency gains in fuel consumption, empty miles, and labor costs for large fleets.
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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