
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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AIMS360 apparel software is the most popular ERP for the fashion industry. The fashion software features cover the entire fashion business lifecycle. AIMS360 business management software covers production, material and finished goods purchasing, omni-channel order taking, order processing, automated inventory management, warehouse management, shipping, invoicing, accounts receivable, and more. Get a demo of AIMS360’s 100+ apparel software features & integrations.
Our most popular integrations: Shopify, JOOR, NuOrder, Brandboom, EDI, DSCO, Dropship, 3PL Integrations, Factoring, & more.
See the AIMS360 fashion ERP website for our full features & integrations list.
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Red Ant
Red Ant's RetailOS is a sophisticated clienteling platform crafted to elevate the omnichannel retail experience. It encompasses a comprehensive suite of applications, including clienteling, assisted sales, omnichannel point of sale, actionable analytics, and machine learning, all geared towards creating seamless customer journeys. The Clienteling application equips store associates with in-depth customer insights, encompassing purchase history, wish lists, sizing, preferences, and communication records, which empowers them to deliver personalized service in both physical and virtual environments. Meanwhile, the Assisted Sales feature provides associates with immediate access to the entire product catalog, thereby streamlining the process of making informed recommendations and closing sales efficiently. The Omnichannel POS system facilitates flexible transactions across multiple channels, ensuring customers enjoy a consistent checkout experience regardless of how they shop. Actionable Analytics delivers timely data insights for effective store management, while the SellSmart Machine Learning component harnesses cognitive technology to fundamentally enhance business operations. Overall, RetailOS not only improves the customer experience but also drives operational efficiency for retail businesses.
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ALPHA
ALPHA is a comprehensive clienteling suite that transforms the shopping journey by delivering tailored services, including direct messaging, tracking client preferences, scheduling store appointments, and enabling remote sales functionalities. It encompasses features such as client requests, a detailed client database with CRM integration, in-depth client profiles, and valuable analytics and insights. The system streamlines client registration via QR codes or text messages, empowering sales associates to effectively manage client interactions and enhance sales performance. Designed for seamless integration with current systems, ALPHA eliminates the need for complicated setups and focuses on improving client satisfaction while driving sales growth. Furthermore, ALPHA seeks to eliminate the sterile complexity often associated with digital tools, emphasizing the importance of human connections and personal engagement in redefining luxury experiences. Ultimately, ALPHA aims to create a more enriching and engaging environment for both clients and sales associates alike.
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