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Private Beta Release for Catalog and Fulfillment

fabric AI introduces AI-driven automation and intelligence to optimize product catalog management and order fulfillment. This private beta enhances real-time analytics, operational decision-making, and efficiency through AI-powered recommendations, helping businesses streamline operations and reduce manual workload.

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Catalog AI

fabric AI improves product catalog accuracy by automating product classification, attribute enrichment, and SEO optimization. AI-driven insights help retailers enhance product discovery and site search relevance while reducing manual merchandising efforts by up to 50%. By integrating real-time inventory data, Catalog AI also supports demand forecasting, enabling better stock management and omnichannel shopping experiences. For more information about Catalog AI and its use cases, see the Catalog AI documentation.

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Fulfillment AI

fabric AI optimizes order fulfillment through AI-powered orchestration, dynamically evaluating:
  • Inventory availability across fulfillment centers
  • Carrier capacity and cost efficiency
  • Delivery time commitments and service levels
AI continuously recommends fulfillment rules and automation workflows to minimize split shipments and shipping costs while ensuring faster, more efficient fulfillment. Additionally, fabric AI’s learning model adapts based on historical fulfillment patterns to improve:
  • Optimal warehouse and store location selection
  • Pick/pack efficiency
  • Workload balancing across distribution centers
fabric AI provides real-time analytics and recommendations across inventory and fulfillment operations. Operators can use natural language queries to:
  • Retrieve real-time order and inventory metrics
  • Analyze split shipment trends and on-time delivery performance
  • Get automated insights to improve fulfillment decision-making
For more information about Fulfillment AI and its use cases, see the Fulfillment AI documentation.