一站式了解 Blue Yonder 的人工智能驱动仓库管理、SaaS 迁移、安全性和用户体验。
This resource provides clear answers to the most common questions about our next-generation, AI-driven warehouse management solution. Learn how AI-powered WMS enhances efficiency through machine learning, supports seamless migration to SaaS, ensures data security, and delivers an intuitive user experience. Whether you’re exploring advanced slotting, robotics integration, or planning your upgrade path, this FAQ is your go-to guide for understanding the future of warehouse operations.
正在加载组件...
安全和数据隐私
Blue Yonder WMS 及其他 Blue Yonder 产品中的数据完全保留在 Blue Yonder 平台的安全范围内。模式和元数据都是我们专有知识产权的一部分，在处理时严格遵守知识产权保护标准。
不会。您的数据在 Blue Yonder 平台内是安全的，不会被共享。每个客户的数据都是完全隔离的，只有该客户才能访问。在对机器学习 (ML) 模型和代理进行培训时，只使用您特定环境中的可用数据，按客户进行培训。
We designed AI-powered WMS as our next-generation warehouse management solution (WMS). It leverages artificial intelligence (AI) and machine learning (ML) to optimize warehouse operations, improve decision-making, and enhance overall efficiency. Unlike traditional systems that rely solely on static rules, our AI-powered WMS learns from your data to predict demand, optimize slotting, and orchestrate resources in real-time. It represents a shift from reactive execution to proactive, autonomous supply chain management.
AI-powered WMS is a SaaS-only solution. The advanced AI and machine learning capabilities require the computational power and scalability of the cloud to function effectively. If you choose to remain on-premise, we will continue to support your operations with technical stack updates, security patches, and bug fixes. However, the AI-native features, such as advanced slotting agents and predictive resource orchestration, are exclusive to the SaaS environment. The only exception is the Warehouse Ops Agent (specifically for briefs and analysis), which is available for on-premise use.
When you invest in AI-powered WMS, we deploy the full WMS stack. This includes:
We built AI-powered WMS to drive interoperability. The platform integrates seamlessly with various automation providers, allowing us to orchestrate both human and machine resources toward single service level agreements (SLAs). The embedded WES moves beyond simple integration to true orchestration. It improves throughput by leveraging automatic interleaving and consolidation opportunities. Furthermore, the platform connects easily with other Blue Yonder solutions—such as Yard Management and Transportation Management—to ensure end-to-end visibility and synchronized execution across your network.
No, the AI-native functionality in AI-powered WMS is additive. We have not removed any of the functionality or hard rules that your operations depend on today. This approach puts you in control of your own pace of change. For example, you can choose to use the AI slotting agent in just one zone of a warehouse to test it, while maintaining standard rules elsewhere. Different warehouses in your network can move at different speeds based on their specific needs and complexity.
The majority of the agentic AI and AI-powered features are available starting with the 2025.2 release of the SaaS WMS. If you are migrating from an older version, our upgrade scripts will guide your environment sequentially to this version to ensure data integrity and configuration retention.
用户体验（UX/UI）
Customers moving from heritage WMS to AI-powered WMS will enjoy the same familiar user experience they are accustomed to, ensuring a smooth transition with minimal retraining. However, we are introducing significant enhancements to drive efficiency. The WebUI will feature a new agentic experience that allows users to interact with the WMS like never before, providing real-time answers to questions through both text and visual elements.
Yes. We recognize that navigating multiple tabs to view critical inventory data is inefficient. Our AI-powered WMS offers an improved user experience that consolidates LPN, location, status, and lot/batch codes into a single, unified inventory view to streamline your operations.
培训与变革管理
We are actively building comprehensive education courseware on the new capabilities. Since ML and AI is new to WMS, we are still learning what information is most useful to you. Please share your learning interests and feedback with us so we can deliver the most relevant training, enablement and certifications.
您无需聘请数据科学家或 ML 专家即可使用我们的 WMS 人工智能和 ML 功能。我们的产品中包含了所有复杂的 ML 工作。不过，我们开始看到一些客户表示有兴趣在他们的数据上建立自己的模型，而我们的平台也支持这种做法。最主要的变化是现有运营团队要转变观念，与自学系统协同工作。
迁移和版本管理
是的。我们制定了专门的迁移战略，将专业服务与人工智能工具相结合，确保迁移更顺利、更快速。我们的数据库无关性数据迁移工具支持任何 Blue Yonder WMS 迁移，我们还提供由大型语言模型 (LLM) 支持的加速集成，用于模式映射和代码自动生成。云原生 WMS 支持所有现有配置，现有扩展只需稍作修改即可迁移，与安全更新架构兼容。
The migration path depends on your current version, but it is a straightforward process. You run the standard upgrade scripts to bring your environment to the 2024 version, and from there, another script transitions you to AI-powered WMS. We rearchitected the solution while keeping the core schema and business logic intact, allowing us to port forward your configuration, setup, and data. The main effort focuses on two areas: integration and extensions, and we have tooling to support both.
No, you can go straight to AI-powered WMS. While our upgrade scripts are iterative and will step your environment through each version sequentially in the background (e.g., from 2023 to 2024, then to 2025), your user experience will be a direct transition from your current version to AI-powered WMS. For example, the 2024 version will only exist for the few hours it takes to run the 2025 conversion scripts.
Dispatcher functionality is converging into the AI-powered WMS, which will be our single WMS of the future across all industries, complexities, and warehouse sizes. We will continue to support Dispatcher with tech stack updates, bug fixes, security patches, and customer-funded innovation. We are also developing migration tooling to simplify your conversion to AI-powered WMS.
人工智能和 ML 功能
The AI-native functionality in our AI-powered WMS is additive, meaning we haven't removed any of the rules-based functionality you depend on. This allows you to control your pace of innovation. For example, you can test the AI slotting agent in one warehouse zone while using existing rules elsewhere. The AI and ML capabilities enhance operations by:
