Side-by-side comparison of AI visibility scores, market position, and capabilities
Fluent Commerce is a cloud-native distributed order management system for omnichannel retailers, raised $30M+ and based in Sydney, Australia.
Fluent Commerce was founded in 2013 in Sydney, Australia and raised over $30M to build a cloud-native distributed order management system (DOM) designed for large omnichannel retailers. The company's platform solves one of the most operationally complex challenges in modern retail: routing customer orders to the optimal fulfillment location across a network that may include warehouses, stores, drop-ship vendors, and third-party logistics partners, in real time and at scale.\n\nFluent Order Management is built as a highly configurable, API-first platform that allows retailers to model their unique fulfillment network and define custom orchestration rules without requiring code changes. This flexibility makes it suitable for complex retail operations where a pre-built rules engine would be too rigid. The platform handles order capture, inventory availability checking, fulfillment location selection, shipment tracking, and returns management, with a store fulfillment module that enables buy-online-pick-up-in-store (BOPIS) and ship-from-store capabilities.\n\nFluent Commerce counts major global retailers among its customers and competes against IBM Sterling, Blue Yonder, and Manhattan Associates in the enterprise DOM market, as well as against newer competitors like Kibo Commerce. Its differentiation lies in the combination of a truly cloud-native architecture — contrasted with the legacy on-premise roots of many DOM incumbents — and a partner ecosystem that makes implementation more accessible for retailers without large internal IT teams.
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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