After more than two decades of pioneering cube storage automation, AutoStore is now moving beyond automation alone toward intelligent fulfillment systems that continuously sense, decide, and improve in real time. The announcement reflects a shift in the market from asset-centric automation to decision-centric fulfillment, as companies look to connect machines, software, data, and people into more intelligent, coordinated operations. With CubeVerse and AutoStore Intelligence, AutoStore enables better, faster decisions across design, deployment, operations, and optimization—working alongside existing WMS and WES solutions rather than replacing them.

For customers, this means unlocking hidden capacity in existing systems, simplifying operations, and accelerating the path to fully autonomous fulfillment, powered by learnings continuously drawn from AutoStore’s global community of thousands of live systems, enabling improvements that compound across the installed base.

“Fulfillment is becoming a real-time, intelligence-driven discipline. If systems can’t sense, decide, and adapt continuously, everything upstream breaks,” said Parth Joshi, Chief Product Officer at AutoStore. “With the launch of the CubeVerse platform and our AI-driven capabilities, we’re bringing intelligence across the entire lifecycle — from design to daily operations to advanced analytics to optimizations. This is a major first step in our AI strategy and reinforces our focus on innovation as the market leader in automated fulfillment.”

The Spring 2026 product announcement introduces a new CubeVerse cloud platform, designed to unify data, applications, and AI capabilities across the fulfillment lifecycle, alongside AI-powered software and analytics, and expanded automation capabilities. Together, these capabilities lower total cost of ownership, improve performance and predictability, reduce operational complexity, and support longer operating hours, including full 24/7 operation.

After a decade of rapid investment in warehouse automation, the industry is facing a new challenge:
seventy-five percent of companies say synchronizing their supply chain is difficult as logistics networks grow more complex. The question is no longer just how to automate, but how to coordinate machines, software, data, and people into systems that make better decisions and run reliably around the clock.
CubeVerse and AutoStore Intelligence provide the data, simulation, and analytics capabilities that enable this shift — helping customers orchestrate fulfillment decisions across the system lifecycle without replacing existing orchestration or control layers.

The Spring 2026 Product Portfolio

Built on the CubeVerse platform, this Spring’s announcements span the fulfillment lifecycle—from system design and AI-driven optimization to autonomous order preparation.

CubeVerse Platform
CubeVerse provides a single platform to design, deploy, and run AutoStore systems. It spans the full system lifecycle—from design and simulation to deployment, operations, analytics, and optimization.
CubeVerse simplifies integrations, keeps operations consistent across sites, and helps customers avoid overbuilding and keep costs under control.

AutoStore Intelligence
AutoStore Intelligence applies built-in AI to real operational data across the platform to orchestrate fulfillment in real time. It optimizes robot movement through CubeControl, reduces congestion, and clears traffic bottlenecks to deliver significantly higher throughput during peak periods, with
performance continuously improving over time, without requiring additional robots or grid
expansion. Embedded across CubeVerse, AutoStore Intelligence uses 20+ proprietary models to predict issues, optimize operations, and deliver measurable performance improvements across the automation lifecycle.

CubeAnalytics
CubeAnalytics, powered by AutoStore Intelligence, turns system data into clear, real-time insights and recommended actions. It helps teams identify issues earlier, reduce downtime, and rely less on specialized in-house expertise. With built-in AI, CubeAnalytics automatically surfaces key issues and patterns, evolving from reporting into an intelligent system that recommends action automatically.

CubeControl
CubeControl, powered by AutoStore Intelligence, uses AI to personalize routing parameters and create optimized robot highways for large, robot-dense grids. This improves traffic flow, reduces congestion, and boosts overall system throughput without additional hardware.

VersaAI
VersaAI delivers robotic piece picking powered by vision and AI, expanding AutoStore’s automation portfolio into autonomous order preparation. The system automates order preparation, consolidation, and staging, improving overall AutoStore utilization. It enables operations to run longer hours with consistent throughput and lower cost per order. This supports 24/7 operations without sacrificing performance.

CubeStudio
First major application added to the CubeVerse platform, CubeStudio is a shared, cloud-based environment for system design, simulation, and validation, enabling AutoStore and partners to make data-led decisions together. It serves as an early proof point of AutoStore’s modern app strategy powered by CubeVerse.

Cube Enhancements
New workstation layouts and expanded bin and case support give customers more flexibility as volumes, SKUs, and workflows change, without requiring grid rebuilds. Enhancements based on partner and customer feedback include expanded case support in AutoCase, simplified WMS integration through VersaPort, and upgraded industrial PCs for large, high-performance systems.

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“I am glad that we now have signed an agreement with Witron for automation in the logistics centre that we will establish. This solution will give us a more flexible, efficient and sustainable logistics chain for product supply to our stores in the southern parts of Sweden, thereby strengthening the entire Axfood family’s competitiveness,” comments Simone Margulies, President and CEO of Axfood.

Logical next step

“It feels very good to have the agreement in place for this strategically important automation solution. With the experience we have built together with Witron in Bålsta, we know that this technology will give us the right conditions going forward, and as a natural step, we feel confident in continuing this journey also in southern Sweden. This investment is fundamental in strengthening Dagab’s and Axfood’s future logistics structure, and for continuing to deliver on our ambition of market-leading efficiency,” says Hans Bax, Managing Director of Dagab.

High level of automation across all temperature zones

In Kungsbacka, products will be stored and picked across three temperature zones: ambient goods (+18 °C), fresh goods (+2 °C), and frozen items (-26 °C). As in Bålsta, the solution relies on standardized Witron logistics modules, including Order Picking Machinery (OPM with a total of 37 COMs), All-in-One (AIO), the Car Picking System (CPS), and a fully automated shipping buffer. Within this shipping buffer, store-friendly picked and consolidated order pallets are buffered and provided just-in-time on heavy-duty lanes, sequenced by delivery route for efficient truck loading. In addition, the Goods-to-Person (GTP) solution enables ergonomic semi-automated picking operations in the frozen food area.

High-performance warehouse management system

The overall material flow includes more than 500,000 storage locations for wooden and plastic pallets, roll containers, totes, and refrigerated containers, 111 stacker cranes, as well as 16+ kilometers of conveyor technology. All processes are controlled by a multifunctional warehouse management system with open interfaces from the WMS to the customer’s supplier systems, route scheduling systems, and sales systems. This enables a high level of end-to-end optimization across Axfood’s entire internal and external supply chain. A Witron OnSite service team of more than 60 employees ensures consistently high system availability in multi-shift operation around the clock – 365 days a year.

Successful omnichannel project

Both companies can reflect positively on a jointly and successfully implemented project. Since early 2025, following a phased ramp-up, one of the most innovative logistics centres in the retail industry has been operating at full capacity in Bålsta, around 40 kilometers northwest of Stockholm. Axfood and Witron designed and realized a cutting-edge omnichannel distribution centre that supplies stores as well as end customers via click + collect and home delivery. The highly automated system handles a product range of 22,000+ dry, fresh, and frozen items.

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Available for ‘ANT driven’ AGVs and AMRs, SmartPass is a robust, safe, and highly configurable technology that meets the core efficiency goal of obstacle avoidance without the drawbacks of traditional AMRs. SmartPass suits all types of automated vehicles and industrial sites.

No matter how clean a site, and how well trained its staff, the paths of mobile robots sometimes become blocked… AGVs typically manage this situation by sending an alarm to an operator, while AMRs take any route possible, without limitation. The first can lead to transport delays, the second to traffic deadlocks. SmartPass effectively bridges the gap between the two.

commented BlueBotics’ CEO, Dr. Nicola Tomatis.

Bridging the gap between AGVs & AMRs

SmartPass enables automated vehicles to follow virtual paths most of the time — for efficient, robust, and repeatable operation — while performing pragmatic obstacle avoidance maneuvers when blockages are detected.

“Rather than layering basic traffic management over obstacle avoidance functionality — which AMR producers have attempted with limited results — SmartPass does the opposite,” Tomatis explained. “It adds smart, configurable obstacle avoidance to ANT navigation’s default ‘virtual path follower’ mode. This ensures the powerful traffic management features of our ANT server fleet manager are also applied to SmartPass maneuvers.”

Three key SmartPass benefits

ANT’s SmartPass function offers three key benefits that together are unique in the mobile robot industry:

1. Efficiency-focused movement
   • Vehicles using SmartPass take the shortest route around an obstacle — within pre-configured limits — before returning immediately to their virtual path.
   • SmartPass-enabled vehicles also move faster than traditional AMRs. Travelling at optimal speeds and with optimal acceleration, they follow virtual paths and respect clear traffic rules most of the time, switching to slower, more reactive speeds only when needed.
   • Vehicle actions like moving forks and communicating with equipment take place during SmartPass maneuvers, saving time versus the more common sequential approach.
   • SmartPass maneuvers are blocked near pick/drop points to guarantee precision.
2. Minimizes deadlocks
   • By managing the movements of vehicles within the ANT server’s existing traffic management framework, SmartPass guarantees that vehicles only avoid obstacles when there is no risk of blocking another robot, minimizing the chance of deadlocks.
   • Vehicles only move around objects and never around other vehicles, a further cause of deadlocks.
3. Fully configurable
   • SmartPass can be configured to suit every user’s site and operational needs. Customers can define, for example, the maximum distance a vehicle is allowed to travel from its virtual path; the areas (and even individual routes) of a site where SmartPass cannot be used; and vehicle-specific parameters such as the exact distance to stop before an obstacle.

“SmartPass doesn’t allow robots to roam freely, and it is built from the ground up on ANT server’s powerful traffic management, virtually eliminating the chance of deadlocks,” Tomatis added. “We are confident this safe, prudent approach best meets the needs of industrial customers looking to deploy AGVs and AMRs in what are often high-traffic locations.”

SmartPass is available now for vehicle makers, system integrators, and end users deploying ‘ANT driven’ AGVs/AMRs managed by BlueBotics’ ANT server fleet manager.

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Rainforest Distribution chose Manhattan Active Supply Chain Planning to modernise its demand planning, forecasting, and replenishment processes, all on a single unified, cloud-native platform. By moving away from fragmented legacy tools to a single planning solution, Rainforest will gain real-time visibility and continuously balance service levels, cost, and capacity across its network, while responding faster to changing customer demand.

“As our business continues to scale, the complexity of our supply chain has increased exponentially,” said Alexander Ridings, CEO, Rainforest Distribution.

“We needed a modern planning solution that could keep pace with that growth, give our teams a single, trusted view of demand and inventory, and help us serve customers with greater reliability. Manhattan Active Supply Chain Planning gives us the unified, intelligent platform we were looking for to align our planners, our operations, and our strategic growth ambitions.”

“Rainforest Distribution operates in an environment where agility, accuracy, and responsiveness are critical,” said Stewart Gantt, executive vice president of Global Services, Manhattan Associates. “We are excited to partner with them on this transformation to help them unlock new levels of efficiency and build a more resilient, data-driven supply chain.”

Manhattan Active Supply Chain Planning aligns planning and execution around a shared strategy, helping organisations eliminate systemic and operational silos and drive coordinated, enterprise-wide decision-making. Built on Manhattan’s cloud-native, microservices-based Manhattan Active® Platform, the solution is engineered to adapt in real time to shifts in demand, labour, orders, and capacity, aligning planning functions with execution across distribution and transportation operations.

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At the heart of Atomix’s solution is its ‘1+4’ technology platform. The ‘1’ refers to Atomixer, an AI-native orchestration software platform that enables real-time coordination of heterogeneous robotic fleets while integrating seamlessly with existing WMS/WCS systems.

The ‘4’ represents Atomix’s four families of self-developed robotics, including 4-way pallet shuttles, pallet AMRs, and tote Storage Transfer Robots and Tote AMRs, designed for high-density storage, flexible handling, and efficient picking. These technologies are modularly combined into three subsystem solutions — ‘Storage Mix’, ‘Handling Mix’, and ‘Picking Mix’ — allowing system integrators to configure scalable automation systems tailored to specific warehouse needs.

A key differentiator of Atomix is its ability to orchestrate heterogeneous robotic fleets within the same environment. Powered by advanced AI algorithms such as MAPF and decentralized deadlock avoidance, Atomixer enables seamless collaboration between different robot types and third-party equipment, optimizing warehouse operations in real time.

Demo Centre

Globally, Atomix works through a partner-based delivery model, providing core technologies and products while local system integrators deliver project implementation and lifecycle services. With over 500 projects across 20+ countries, Atomix has built long-term partnerships with companies including Coca-Cola, Nestlé, Toyota, Yum China, Lotte, ITW, and Lenovo, achieving a 71% customer renewal rate.

In Europe, Atomix continues to expand through local integrator partnerships. The company has recently opened a Demo & Experience Centre in Belgium to support partners and customers across the region. Recent projects delivered in Romania and Greece demonstrate the flexibility of Atomix solutions across industries such as manufacturing and cold-chain logistics.

Visitors to LogiMAT 2026 are invited to meet the Atomix team to explore AI-powered automation solutions and discuss partnership opportunities. If you would like a free visitor ticket you can register here.

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Otto Lehmann GmbH, with around 400 employees, is a leading manufacturer of roofing products and drainage technology – from snow guard systems and roof module holders to gutter hooks. The product range comprises around 3,000 product variants. Around 10,000 tonnes of steel and around 3,000 tonnes of non-ferrous metals, primarily copper and zinc, are processed each year.

The company plans to set up an external storage facility in Geiselhöring. This warehouse will be managed using KlinkWARE WMS, but will be operated completely separately from the main warehouse in Neutraubling. The plan is to use independent software and system configuration on a separate server, which will exchange data with the main system via a shared host interface. The focus is on processing goods receipts and full picks for around 50 fast-moving items. In addition to goods receipt and dispatch of pallets – including tour approvals and packing station allocation – the new warehouse will also use the software to map stock transfers, stock corrections and inventory.

Due to the high degree of standardisation of the KlinkWARE software, the entire project will take only around eight weeks and includes testing, commissioning, training, system support and the user documentation. The warehouse will be set up as a separate address in the main system to ensure a systemic separation of the company’s own warehouse from the warehouse of the external service provider. At the same time, there will be a connection to the central WMS via the ERP system, which generates withdrawal notes.

Back in spring 2025, a four-aisle automatic high-bay warehouse with storage and retrieval cranes and picking stations, a manual long goods warehouse and a block storage facility at the Neutraubling site were converted to KlinkWARE. The reason for the migration was outdated servers and operating systems, which posed an increased security risk. In addition, the maintainability of the existing software was limited, making it necessary to adapt it to the current development environment.

By creating a new set of specifications, a comprehensive process optimisation was also carried out. This made it possible to eliminate functions that were no longer needed and, at the same time, to incorporate frequently missing requirements into the new solution. By connecting the external warehouse, Otto Lehmann is creating greater transparency through standardised systems and is consistently continuing the modernisation of its logistics IT.

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In today’s world, warfare, sanctions and climate instability are fracturing global supply chains and upending business plans with little warning. In fact, we must accept that volatility has shifted from being an exception to a defining feature of the operating environment.

In response, organisations are accelerating their adoption of AI, drawn by its promise to improve decision making and build resilience in an increasingly unstable world. Yet, as the enthusiasm for AI grows, so do the risks associated with how it’s being deployed.

Many businesses have already embraced early generative AI tools that operate alongside existing processes, though without fully embedding them. While these systems can speed up analysis, they often lack access to critical data and an understanding of wider business context, resulting in new forms of risk rather than increased protection.

Unlike earlier tools, agentic AI can not only analyse information but simultaneously take action, considerably expanding its potential impact. It also increases the consequences of getting it wrong, though.

When AI systems operate without full situational awareness or clear governance, the outcomes can be immediate and damaging, ranging from misdirected inventory and excess production to costly compliance failures.

This is a pivotal moment for AI adoption; agentic AI will play a central role in the future of supply chain decision making, but its success will depend less on the speed of adoption and more on how responsibly these systems are integrated in core processes.

As organisations begin to use AI to help them navigate disruption, they face a clear choice. On one side, generative AI tools and copilots are added onto existing processes, offering quick wins and impressive demonstrations. Yet because they sit outside of the workflows where decisions are made, they rely on fragmented data and produce outputs that lack context and accountability.

In complex supply chain environments, any shortcomings can escalate rapidly, with misaligned decisions leading to undermined trust and increased risk exposure.

On the opposite side, organisations can begin embedding intelligence directly into decision making workflows. At its most advanced, this involves agentic AI systems that operate on real-time data alongside the wider business context, allowing them to coordinate responses across the organisation.

When AI is embedded like this, organisations can move beyond reactive responses and gain the ability to anticipate disruption and act decisively before any issues can escalate.

With all this, maintaining human oversight and accountability when using AI systems should remain a design requirement. While there are concerns that AI might replace people, agentic systems will only deliver the most value when they are designed to work alongside humans.

People are and will remain responsible for the most important decisions. They define objectives, approve actions with significant impact and remain accountable for outcomes.

Within these outlines, autonomous agents can monitor signals, coordinate activity across functions and generate response options. As a result, human decision makers can then focus on areas where judgement and morals, as well as regulatory understanding, are crucial.

More importantly, embedding agentic AI into decision workflows enables oversight to be applied from the beginning. Unsafe or non-compliant actions can be prevented automatically, rather than identified after the fact. As regulators, particularly in the EU, place greater emphasis on transparency and explainability, this level of control is becoming increasingly necessary.

Supply chains are at risk due to a lack of systems that enable transparent, coordinated decision-making.
As uncertainty and instability continue to rise, advantage will come from adopting AI responsibly and embedding it into core decision processes with clear governance and human accountability.
Ultimately, trust is not the result of faster decisions. It is what makes them possible.

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Against this backdrop, the new strategic partnership between EPG (Ehrhardt Partner Group) and Bluerock TMS, a provider of a globally deployed transport management system, is creating a platform that combines mathematical route optimization with real-time transport management. The goal of the collaboration is to integrate EPG’s routing engine ‘Greenplan’ directly into Bluerock’s cloud-based TMS platform. This will give companies access to a fully connected system that unifies planning, execution and analysis of their transport operations in one central process.

As a global company with locations in Europe, North America and Asia, Bluerock coordinates millions of shipments each year through its modern and comprehensive TMS. Greenplan enhances these capabilities with a decisive next step.

While Bluerock provides full transparency on delays, capacity constraints, and operational deviations, Greenplan takes action where visibility alone reaches its limits. Greenplan doesn’t just calculate optimal routes that meet all customer criteria but continuously reoptimizes them. Using advanced mathematical models, routes automatically adapt to changing conditions in real time and can be released instantly at the push of a button.

The result is a genuine ‘beyond visibility’ effect: companies no longer just see what is happening, instead, they receive immediate, data-driven solutions and concrete options for action. This translates into measurable cost savings, improved on-time performance, and reduced emissions.

Dr. Clemens Beckmann, CEO Greenplan at EPG, explains: “With this partnership, we are combining mathematically precise route optimization and high-performance transport management in one system for the first time. Companies gain not only trans-parency but also immediate ability to act – automatically and in real time.”

Efficiency as a Key Competitive Advantage

Global supply chains are becoming increasingly volatile and interconnected. Fluctuating demand, traffic congestion and rising sustainability requirements increase operational pressure on fleet operators and shippers alike. Static or rule-based route planning methods that used to be sufficient can hardly keep up with these new challenges. The Greenplan algorithm analyzes traffic flows, delivery priorities, time windows and vehicle capacities simultaneously and simulates multiple scenarios within seconds. The most efficient routes are identified and automatically adjusted to current conditions.

Combined with Bluerock TMS, this creates a learning system that not only detects disruptions but can also react automatically upon them. Dispatchers immediately see delays, late arrivals or capacity constraints in the Bluerock dashboard, and Greenplan generates the optimal alternative without manual intervention. Rico van Leuken, CEO of Bluerock, adds: “Greenplan expands our TMS with a dimension that goes far beyond traditional visibility. Our customers receive a solution that combines the power of a globally deployed transport management system with the precision of mathematical optimization. The result is resilient, dynamic and future-ready networks.”

Global Reach and a Sustainable Outlook

Bluerock is used today by companies on three continents and is known for its intuitive usability and strong transparency features. With the integration of Greenplan optimization, the TMS gains an additional dimension and route planning becomes an active con-trol tool that unites economic efficiency with environmental responsibility.

For EPG, this partnership marks another milestone in expanding its international partner network. The company aims to connect technological innovations worldwide and to establish new standards in digital transport logistics together with leading providers. The combination of Greenplan’s routing technology with Bluerock’s global reach creates a strong foundation for this vision. “Sustainability and efficiency are not opposites but mutually reinforcing factors,” concludes Dr. Beckmann. “The same data that helps reduce costs also enables precise measurement and reduction of emissions. Modern logistics is becoming more economical and more responsible.”

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Autonomous robots

First up is Dr. Marcus Scheunemann, Head of Autonomy for Dexory, who believes the top trend will be the subject of autonomous robots: “2026 will mark a significant step towards full autonomy for robots. Advances in AI paired with increasingly sophisticated robotic control systems are allowing autonomous machines to interpret their surroundings more precisely and manage unpredictable situations better. As these technologies mature together, we will see a noticeable shift in what autonomous robots can reliably handle without human input.

“This shift will pave the way for organisations to operate entire fleets with far less day-to-day oversight. If this pace continues, it’s fair to say we will reach a point where most routine operational tasks could run independently, with only very unusual scenarios still requiring human support. Achieving this level of autonomy within the next two to three years would set a new standard for how autonomous systems perform in real-world environments and represent a significant milestone for the entire robotics sector.”

Warehouse visibility

Todd Boone, Vice President North America, Dexory picked the issue of visibility in warehouses: “In 2026, true warehouse intelligence based on data rather than assumptions will shift from being a novelty to becoming a standard expectation. Customers will increasingly require insights they can act on, drawn from rich and comprehensive data sets rather than simply faster inventory counts.

“As this shift accelerates, the limitations of drone-based solutions will become more apparent because they do not capture enough of the right data to meaningfully influence operations at scale. As warehouse visibility and analytics mature, organisations will expect full-spectrum intelligence, making partial solutions far less viable.”

Agentic warehouses

Divya Gautam, Head of AI, Dexory focuses on agentic AI: “2026 will be the year the warehouse becomes ‘agentic’. The industry will move beyond passive visibility, where AI surfaces endless unprioritised alerts, to active intelligence where autonomous systems interpret context, reasons, and recommend the next best action. Competitive advantage will shift to warehouses that turn raw data into autonomous decision-support by using AI agents that collaborate with human teams to resolve issues faster and more accurately.”

Collaborative agents

Finally, Oana Jinga, Chief Commercial & Product Officer & Co-Founder of Dexory, opted to discuss collaborative agents: “In 2026, multi-AI agent systems will become the backbone of next-generation warehouse automation. Instead of a single monolithic software controlling operations, warehouses will deploy collaborative AI agents — each specializing in tasks such as real-time inventory perception, traffic optimization, predictive maintenance, labour allocation, and exception handling. These agents will communicate continuously with each other and with fleets of autonomous robots, enabling a fluid, self-optimizing warehouse ecosystem.”

8 Areas to optimise

The warehousing industry is evolving faster than ever. Rising customer expectations, growing SKU complexity and global supply chain pressures demand faster fulfilment, better use of space, and uncompromising safety. Yet for many warehouses, inefficiency persists – lost pallets, underused aisles, and inconsistent data updates. The question is no longer if automation drives ROI, but how fast you can capture it.

That’s where optimisation comes in. High levels of stock integrity mean warehouses can operate with faster, more reliable workflows and optimal use of resources. But once inventory health and visibility are firmly in place, the next step is to unlock the full potential of your operations through targeted, AI-driven optimisation strategies.

By enhancing the flow of goods, maximising space utilisation, and refining processes, operations can keep pace with rising demand with precision and speed. Dexory outlines eight areas for warehouse optimisation – from real-time visibility and block stack digitisation to AI-powered consolidation planning and weight restriction monitoring:

1. Inventory integrity as the cornerstone of efficient operations
   High levels of stock integrity mean warehouses can operate with faster, more reliable workflows and optimal use of resources, while enabling confident decision-making and minimising operational disruptions.
2. Real-time visibility that turns blind spots into insights
   Only 6% of logistics companies report full visibility over their operations. This gap can mean missed opportunities, safety risks, and slower fulfilment.
3. Block stack storage visibility without disruption
   What if you could eliminate the blind spots in deep storage areas? No more guessing, lifting, or forklift repositioning. Just evaluating discrepancies in real time, such as missing, miscounted, or incorrectly placed items.
4. Pick face optimisation for smarter cycle counts
   Every day, the WMS generates a cycle count list. You know most of it is wasted effort, but you still have to check every single location. Instead, how about shrinking the cycle, freeing up resources, and finally getting control of your pick face locations with maximum efficiency?
5. Maximising storage utilisation
   AI-powered consolidation planning can identify opportunities to group compatible items together while avoiding conflicts like mismatched batch codes or incompatible products. This reduces wasted space and unproductive travel time between storage locations. Optimal space utilisation and efficient stock handling bolster long-term reputational gains by showcasing operational excellence and dependability.
6. Improved compliance and safety with advanced slotting verification
   Every warehouse faces risks from incorrect slotting. By aligning slotting with both safety and efficiency, warehouses ensure that they remain audit-ready, compliant, and secure.
7. Faster fulfilment, no picking delays
   Poor replenishment leads to picker delays, slow order fulfilment and reduction in storage efficiency. But with advanced robotics and automation systems, warehouses can achieve faster fulfilment and throughput without extra headcount.
8. Weight restriction monitoring for safer, risk-free warehouses
   Overloaded bays and racks put staff and infrastructure at risk. Manual checks are slow, error-prone, and often inconsistent. At the same time, WMS rules are static, they don’t
   prevent live overloads. With the right use of automation, warehouses can ensure risk-free operations where safety is never compromised.

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The AI-based simulator takes into account variables such as forecast demand in each region, transport costs and the operational capacity of each warehouse to test various inventory replenishment policies without affecting real-world operations. “The genetic algorithm enables multiple simulations to be run using different parameters until the most efficient logistics strategy is identified. Companies can compare scenarios and select the one that best fits their operations,” says Dr. Matthias Winkenbach, Director of Research at the MIT Center for Transportation & Logistics and the Intelligent Logistics Systems Lab.

Once data and variables are entered into the system, GENESIS generates the optimal solution along with advanced statistical dashboards. Users can analyse indicators such as consumption patterns, regions with high demand variability, SKUs with a greater risk of stockouts or warehouses experiencing supply issues.

Redistribute before purchasing

One of the system’s key features is its ability to rebalance inventory across warehouses. Instead of automatically placing new orders with suppliers, the tool analyses whether it is more efficient to transfer products from another facility within the network where excess inventory is available. In this way, companies can reduce costs and make better use of existing stock.

The system also recommends how to organise transport. For example, it suggests whether shipments should be consolidated to optimise truckloads or whether specific orders should be fulfilled from a particular location to reduce delivery times and costs.

“The real challenge wasn’t finding the right algorithm — it was making it fast enough to be practical. We developed GENESIS from the ground up to evaluate thousands of scenarios simultaneously rather than sequentially. What used to take days now takes minutes, which means companies can use it for real tactical planning, not just theoretical analysis,” says Rodrigo Hermosilla, Research Engineer at the MIT Intelligent Logistics Systems Lab.

Unlike analytical solutions reserved for specialised users, GENESIS is designed for both technical teams and business decision-makers. “The goal is to help companies minimise the total cost of their logistics network while ensuring the highest service level,” says Javier Carrillo, CEO of Mecalux.

Upcoming AI applications

The AI-powered simulator is one of the first tangible results of the joint initiative between Mecalux and MIT CTL. The collaboration is now entering a new phase focused on expanding the application of AI to other logistics processes, such as internal replenishment, digital twins in high-density automated storage systems, and slotting optimisation.

The MIT Center for Transportation & Logistics (MIT CTL) is a world leader in supply chain management research and education, with over 50 years of expertise. The centre’s work spans industry partnerships, cutting-edge research and driving supply chain innovation into practice through three pillars: research, outreach and education

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