Kitch'n

Kitch'n, Norway's leading kitchen and homeware retailer, operates 200 stores nationwide alongside a high-volume online shop, with goods-in-transit including fragile materials like glass and ceramics that require careful handling. Their distribution centre at Bryne processed roughly 650,000 parcels in 2024, with 35% volume growth forecast for 2025. While storage was automated via AutoStore, order fulfillment remained manual at the AutoStore ports: staff physically sorted items requiring value-added services (VAS) — such as bubble wrap packaging — to packing stations, then re-sorted completed parcels by courier. This sequential manual process created severe bottlenecks during peak periods like Black Week and the wedding season, and simply could not scale to meet projected demand.

Working with system integrator Element Logic, OmniMod deployed the OmniPacker — a compact 3×8 meter OmniSystem purpose-built for VAS optimization — at Kitch'n's Bryne distribution centre. The system automates fulfillment in four stages: inbound goods from the AutoStore enter on a conveyor, are buffered awaiting available VAS stations, sorted to those stations, and automatically routed to outbound conveyors post-VAS for dispatch preparation. At its core, the OmniPacker runs multiple in-house-developed machine learning models that jointly handle reliable goods detection and tracking, adaptive route planning that responds to station availability in real time, and coordinated goods transportation across the conveyor network. The software layer is designed to be flexible and expandable, enabling Kitch'n to add functionality or capacity without requiring significant hardware changes as volumes continue to grow.

The OmniPacker delivered measurable gains across speed, capacity, and space utilization. Order fulfillment efficiency improved 4–5x over the prior manual process, driven largely by eliminating operator walking time, removing sorting interruptions near the AutoStore, and enabling a distraction-free workflow at ergonomic VAS stations. Throughput doubled to 2,000 parcels per hour, freeing AutoStore retrieval capacity for higher-volume cycling. The system's footprint is over 20% smaller than traditional conveyor-based solutions of equivalent throughput. Qualitatively, sorting errors decreased and AutoStore operations stabilized, as the manual congestion that had previously constrained retrieval rates was removed from the port area entirely.

• 4–5x faster order fulfillment vs. prior manual process
• 2,000 parcels/hour throughput (up from ~1,000)
• >20% footprint reduction vs. traditional alternatives
• Reduced sorting errors and freed AutoStore retrieval capacity

• Automating VAS sorting separately from AutoStore ports can unlock retrieval capacity gains that extend well beyond the fulfillment workflow itself.
• Multi-model AI combining detection, tracking, and adaptive routing outperforms single-algorithm approaches in dynamic, high-SKU warehouse environments.
• Compact modular systems (3×8 m here) can deliver enterprise throughput in space-constrained DCs — footprint should not be assumed a barrier to automation.
• Seasonal demand spikes (Black Week, wedding season) are a reliable forcing function for scoping capacity headroom; design for peak, not average volume.
• Partnering a hardware vendor with a specialist integrator (OmniMod + Element Logic) accelerates deployment in complex intralogistics environments.