Robotics & Physical AI

Exotec Skypod System Deployed at GXO’s Venlo Facility for Guess

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Contract logistics provider GXO Logistics and warehouse robotics provider Exotec announced on September 15, 2026, that an Exotec Skypod automated storage and retrieval system is in operation at GXO’s facility in Venlo, the Netherlands, supporting global fashion brand Guess. The installation processes between 40,000 and 70,000 pieces per day, the companies said.

The Venlo Installation

The installation includes 127 robots, 60,000 rack locations, eight goods-to-person picking stations and 200 meters of conveyor network, according to the announcement. During peak periods, the system can reach throughput of up to 2,200 order lines per hour.

At the Venlo site, GXO manages inbound logistics, value-added services including quality control and garment conditioning, and outbound distribution for Guess across EMEA and Asia. Exotec coordinated the integration and end-to-end deployment across the facility, and the two companies said the system was designed around the requirements of fashion logistics, including high SKU counts, seasonal demand fluctuations and evolving customer needs.

Mark Donné, operations manager at GXO Venlo, said the automated solution, tailored specifically for Guess, has enabled “faster processing, greater predictability and a smoother workflow across the site,” and that GXO has the scalability and flexibility needed to support future demand as its business with Guess grows.

Wim Vermeir, senior sales executive Benelux at Exotec, said fashion logistics involves high SKU counts, seasonal spikes and EMEA-wide distribution that require precision engineering rather than off-the-shelf automation, and that the system was designed specifically for those demands to support both current performance and future growth.

A Single-Integrator Design

A case study published by Exotec describes how GXO selected Exotec as a single system integrator rather than assembling components from multiple vendors. The case study attributes that choice to GXO’s aim of simplifying accountability, reducing integration risk and ensuring that every component in the chain was optimized to work together for Guess’s distribution needs.

At the core of the installation, the 127 robots navigate the 60,000 rack locations and bring goods directly to operators at the eight Order Mover goods-to-person picking stations. The 200-meter conveyor network connects the storage, picking and dispatch zones, and, according to the case study, a set of purpose-built specialty machines eliminates bottlenecks at the handoff points: a spiral conveyor moves goods vertically between levels, tray-box joiners and separators allow consolidation and mixed-unit handling, and a tote destacker feeds the picking stations automatically.

According to the case study, Guess carries thousands of SKUs across sizes, colors and seasonal collections, and GXO was handling a large, seasonally variable volume of Guess products at Venlo while preparing to absorb new e-commerce flows for the Benelux region. During the design phase, Exotec’s teams worked with GXO’s operations staff to shape the system around the site’s constraints and Guess’s product mix, proposing alternatives when a configuration was not optimal. Donné recalled that the brief took the form of “here is our problem, find a solution for it,” and described the collaboration as a mutual effort to get the best system.

Skypod Robots and Orchestration

Exotec describes the Skypod system as an automated storage and retrieval system, or AS/RS, built around robot-to-robot handling: at ergonomic workstations, operators pick items from one robot carrying inventory bins and place them directly into another robot holding the shipping carton, eliminating separate picking and packing zones, according to Exotec’s system overview. An Integrated Buffer feature stores completed or semi-completed orders inside the racks until they are ready for outbound or further consolidation, removing the need for staging areas.

For outbound, the robots group orders and deliver them in a set arrangement to a unit called the Exchanger, which routes them for loading onto pallets, containers or trucks based on delivery routes or store planograms, without external sorting equipment. Exotec states that each station can pick from up to 600 containers per hour, that any SKU in the system can be accessed within two minutes, and that racks can reach up to 14 meters in height.

According to Exotec’s published specifications, the Skypod robots carry loads of up to 30 kilograms in Exotec bins, trays or custom containers, travel at up to 4 meters per second in three dimensions, climb racks up to 14 meters, operate in temperatures from 0°C to 40°C, and can drive beneath the racks in any direction. Exotec says each robot needs about five minutes of charging per hour, delivered through charging boosters inside the system, and that the robots also recover charge while braking and descending. The robots are proprietary Exotec technology designed and built in-house, and the company’s Deepsky software orchestrates every element of the Skypod system and connects it with third-party equipment.

Reported Results and Next Steps

The case study reports that since go-live the Venlo site has processed between 40,000 and 70,000 pieces per day depending on the season, with throughput of 2,200 order lines per hour at peak, and that processing times have been reduced to a single day. Donné described the current operation as more organized and calmer than the high-pressure, heavily manual environment that preceded it, according to the case study, which also states that the ramp-up was among the smoothest deployments GXO has experienced, crediting joint preparation between the two teams and on-site support during the go-live phase.

The site currently distributes to Guess retail stores across EMEA and Asia, and e-commerce fulfillment for the Benelux region is set to go live imminently, according to the case study.

Orion Sato is an AI-generated correspondent focused on robotics, automation, and intelligent machines. His writing explores how advances in robotics are reshaping manufacturing, logistics, healthcare, and everyday life through increasingly autonomous systems.

With a technical and execution-oriented perspective, Orion analyzes robotic architectures, sensor fusion, control systems, and the convergence of AI with mechanical intelligence. He is particularly interested in how automation moves from controlled environments into real-world deployment, where reliability, safety, and efficiency matter most.

Articles authored by Orion Sato are AI-generated and reviewed by Unite.AI’s editorial team to ensure technical accuracy, clarity, and compliance with editorial standards.