Fulfillment is getting harder to manage. Labor is hard to find and costs more, products and orders vary more, and capital is under review, so every investment must be defended. Solving isolated efficiency challenges is no longer enough when operational complexity is growing across every part of the business.
That is why autonomy has moved up the agenda. Supply chain leaders are pursuing it because the complexity of fulfillment is becoming harder to manage through labor-intensive operations, patchwork workarounds, isolated automation and static planning. As presented at this year's Gartner Supply Chain Symposium/XPO, 80% of supply chain executives expect autonomy of both people and machines to become the primary way of doing business by 2030.
The question is how to get there in a way that is practical and financially defensible.
That's what is behind AutoStore's 2026 Fall Product Announcement and its theme, “From Automation Toward Autonomy.” It's a set of practical steps available now to move you toward “light-out fulfillment.”
Lights-out operations help organizations move people up the value chain. FlexBinsPort™, Pio Pal™, and new AutoCase™ capabilities automate manual fulfillment tasks across the flow, enabling employees to focus on oversight, problem-solving, and other higher-value activities.
FlexBinsPort handles all standard Bin heights (220 mm, 330 mm, and 425 mm) from a single Port, so changing SKU profiles can be managed in one Grid through one workstation, with 10% to 15% higher storage utilization and improved labor efficiency. It is not a like-for-like replacement for CarouselPort™, which remains the more economical option for systems using a single Bin height.
AutoCase™, released in Fall 2025, handles case and each-picking flows in one Grid. It now supports case sizes up to 600 mm x 400 mm and includes FlowStream software that distributes a single task group across multiple AutoCase stations for faster downstream packaging and palletizing.
Pio Pal extends robotic picking to small and mid-sized businesses through the bundled Pio offering, with throughput up to 540 order lines per hour and a service-based model that lowers the commitment to start. Pre-picking multiple order lines into one Bin raises performance up to three times without adding labor. Pio Pal is in live pilot in Norway at Famme.
Autonomy depends on better decisions, not only better machines. AutoStore Intelligence™ moves planning from assumptions to intelligence-backed decisions, in the two places where getting it wrong is most expensive: justifying the investment and designing the solution.
CubeExplore is a new application that helps organizations evaluate, quantify, and justify AutoStore investments before a project begins. Using operational benchmarks from comparable AutoStore deployments and AI-assisted scenario modeling, it builds a defensible business case in minutes rather than weeks.
AutoStore Intelligence in CubeStudio™ applies the same principle to design, recommending modules and comparing scenarios against customer expectations, and cutting simulation iterations from between 10 and 20 down to 1 or 2 at the same level of confidence. The result is a lower risk of overbuild, underperformance, and costly redesign.
What customers receive is a business case grounded in comparable projects, and a design tested against how their operation will actually run.
Autonomy raises the bar beyond go-live, because sustained continuity matters as much as execution. CubeFleet™ gives maintenance teams earlier awareness of service needs across one site or many.
Many teams still work from fixed-interval schedules or reactive servicing backed by spreadsheets and institutional knowledge, which drives unnecessary cost or catches issues too late. CubeFleet uses live operational usage data from CubeAnalytics™ to monitor module utilization against maintenance thresholds. It then triggers alerts, provides guidance, and creates work orders automatically.
Acting before avoidable issues disrupt operations helps reduce unplanned downtime by 35% to 45%. It provides proactive maintenance visibility, complements existing maintenance processes rather than replacing it.
Autonomy also depends on how easy the technology is to adopt, deploy, and operate. Six updates broaden where AutoStore applies and reduce the effort of running it day to day.
Pio expands AutoStore-powered, standardized plug-and-play automation into SMB manufacturing, parts storage, retail, and back-of-store environments.
Together, these updates make autonomy more practical and commercially viable by delivering:
A clearer route toward lights-out fulfillment
Better handling of variability across SKUs and workflows
AI-generated decisions in system design
Improved maintenance visibility beyond go-live
Broader adoption across more environments with less complexity
Autonomy is a journey, and what organizations need today are capabilities they can put to work in the operation they already run. AutoStore's role is to make that journey possible, step by step: Fall 2025 expanded the path to end-to-end fulfillment, Spring 2026 strengthened the digital foundation, and Fall 2026 turns those foundations into deployable products. This announcement is a collection of practical capabilities that make autonomous fulfillment more attainable. After all, progress that can be defended in a budget review is worth more than a vision that cannot.
Yes. However, to get the most value from FlexBinsPort, the system should be configured to multiple Bin heights/types (FlexBins).
Basic ROI calculations in spreadsheets oversimplify assumptions and fail to account for dynamic variables, market benchmarks, and AutoStore experience from similar projects. CubeExplore shifts from aspirational selling to quantified storytelling, focusing on execution and investment justification by generating business cases with high-confidence estimates using AutoStore Intelligence.
The AI design assistance uses operational benchmarks, solution design patterns, and performance data from similar AutoStore projects and simulations as foundation to support solution designing.
It refers to the intelligent insights derived from aggregated patterns across similar AutoStore projects’ solution design (e.g., module configurations, throughput behavior, and design outcomes) and simulations.
Partners responsible for service delivery: Partner service or maintenance teams managing service obligations for one or multiple AutoStore deployments.
Customers maintaining their own AutoStore: Maintenance manager, site operations teams, or service technician responsible for keeping the operational running reliably.