AutoScheduler.AI has made its AI App Builder generally available as part of the Warehouse AI Platform. The capability is aimed at planners, supervisors and site leaders who need to solve operational issues without commissioning separate IT development.
Users describe a requirement in plain language. The builder then combines live warehouse information, a semantic layer covering connected systems and production-grade optimisation algorithms to produce an application for monitoring, decision support or process automation.
The launch extends AutoScheduler.AI’s existing orchestration role across warehouse management, ERP, labour, yard and automation systems. Customer-built examples include labour planning, OTIF monitoring, replenishment control, inventory-flow analysis, production planning, wave optimisation and dock-door schedule compliance.
AutoScheduler says the platform is differentiated from generic AI and low-code products by its warehouse-specific data model and optimisation library. The company reports six years of experience across nearly 100 sites. In one working session, a customer created an application in under 15 minutes. Another site planner built and deployed a replenishment-monitoring tool within two weeks, after which the site allocated a six-figure annual budget to it.
Applications use the same integration as the orchestration platform, removing the need for separate data infrastructure for each use case. They run alongside Daily Plan, Wave Planner, Network Scoreboard and Warehouse AI Agent, and can write tasks back to the WMS where required. The offering is available through the AutoScheduler.AI Warehouse AI Platform.
A multilingual professional experienced in Europe, Canada, and China, Herbert has developed invaluable networks in the automotive and energy industries. He has led high-profile projects involving ENBW, Mercedes-Benz Group, Siemens Group, and the Fraunhofer Institute.