Description

Warehouses are getting harder to run: demand swings, automation from several vendors and now AI agents. Every warehouse records what happens, every order, task, confirmation and movement, across WMS, material flow control, TMS, ERP and HR. But the data is scattered. Control rooms firefight from lists, and every new site relearns its processes after go-live. As one control room told us: “We were just blind.”

Warehouse Kosmos brings order to that world. It turns the events from every system into one validated, object-centric model of the entire warehouse: orders, tasks, handling units, customers, suppliers, people, robots and agents, mapped to the real layout and refreshed in near real time. AI-assisted mapping connects new source systems, and validation rules from years of warehouse projects check the data before anyone relies on it.

Built once, it serves every role. Control rooms see the live material flow in 3D and act on risks before they hit a truck. Shop-floor teams see their part of the flow. Analysts find the inefficiencies that matter most. Management steers every site on one global KPI basis. Staff build the dashboard or alert they need by prompt, released by an expert. IT rolls out one blueprint to every site and WMS. Agents work on the same model and propose actions within approved rails; a person approves before anything is written back.

Innovations

Today every new tool, robot and agent brings its own data logic, and AI runs on whatever data it gets. Warehouse Kosmos answers with six innovations.

1. One ordered model instead of many tools. Kosmos is the one validated model underneath all systems, robots and agents. A shop-floor number, a 3D view, a dashboard and an agent proposal trace back to the same events and KPI definitions.
2. AI-built integration and views. AI maps new source systems to the warehouse model and lets business users build dashboards and alerts by prompt; experts release them, so speed never costs trust.
3. Real-time material flow in 3D. Material flow control data puts conveyors, shuttles, robots and people on the site’s real layout, with every order and task behind it. Any shipment can be replayed task by task without an expensive 3D digital twin project.
4. Value before go-live. Kosmos runs on the test system of a new WMS, checks migrated data and KPI definitions in UAT, and a new site steers with data from day one. In a reference customer’s words: “you should not wait until things are operational.”
5. Human in the loop by design. The model holds the actions a site has approved. Agents propose only within these rails, a person approves, then the action writes back; every decision is recorded.
6. Global scale. One core model for every site, WMS and automation vendor, plus local extensions, so every facility is compared on one definition per KPI.

Market relevance

Warehouse complexity is rising on three fronts.

Automation: Gartner expects 50 percent of new warehouses in developed markets to be robot-centric by 2030, often with mixed fleets. Fragmentation: only 23 percent of surveyed operations report fully integrated systems (Kardex/Modern Materials Handling, n=127, 2025). AI: 56 percent of chief supply chain officers call integrating AI with legacy systems a major challenge (Gartner, n=140, 2026). On top, over half of DACH logistics companies rate themselves as not adaptable enough to ongoing disruption (BVL, 2023/24). Warehouse groups rarely run one WMS, one layout or one KPI definition, and every new site, WMS change or migration repeats the learning curve after go-live. Network operators ask: “in which facility are we the most effective in receiving?”

Target group: Manual, semi-automated and highly automated warehouses on any WMS, from single sites to networks with hundreds of locations.

Reuse instead of projects: core model, KPI definitions, validation rules and approved actions are reused; only mapping, layout and local extensions are site-specific. Low entry barrier: no hardware, no sensors, no change to the WMS or automation; a cloud service with standard connectors.

Why now: networks are moving to new WMS and adding robots and AI agents at the same time. Warehouse Kosmos provides the validated model once per site, and every new app and agent builds on it.

Customer benefits

• Today control rooms rebuild problem shipments by hand, every new site relearns after go-live, and AI runs on unvalidated data. Warehouse Kosmos changes that for every role. Control rooms manage instead of firefight: risks show up before a truck is missed, and a problem shipment is replayed task by task instead of rebuilt by hand for half a day.
• Shop-floor teams own their performance and see how they contribute to the overall flow. As team leads put it: “this is what we wished for.”
• Process analysts find the most critical inefficiencies on data that is already validated.
• Management gets one global KPI basis to steer every site and compare facilities area by area.
• IT gets the blueprint to scale: every new site, WMS change or migration starts from the same model.
• Agents get the data foundation and rails to deliver trusted results; they take over desk work, people decide, and time goes back to the floor.
• Proof: at a highly automated European distribution hub, the model went live during the ramp-up and became the shared truth from management to the shop floor. Business IT, “very skeptical in the beginning”, was surprised by the speed of data integration and validation. Cutting through the complexity with data and giving control and ownership back to the teams improved throughput by 40% during the ramp-up and shortened the ramp-up by three months, saving EUR 3 million.