Where It Began

While working with logistics and warehouse teams across industries, we found a common pattern: pallet-loading decisions were mostly manual, inconsistent, and rarely measured. Even in facilities with advanced systems, pallet utilization relied on experience rather than data. Small inefficiencies—unused pallet space, uneven loads, and extra shipments—were treated as inevitable. Over time, those small losses compounded into significant cost, operational strain, and reduced throughput.

That observation led to a single question that became PalletIQ's foundation: what if pallet loading could be measured, optimized, and continuously improved using data?

Turning Observation into Innovation

PalletIQ was designed not simply as another tool, but as a way to bring clarity and intelligence to an overlooked operational layer. We began by analyzing key drivers of inefficiency:

• Pallet utilization patterns — how space is used and wasted
• Load consistency across shifts — variability that creates rework and risk
• Cost implications of inefficient stacking — freight, materials, and labor impacts
• The gap between effort and outcomes — where manual work fails to deliver measurable results

The Result

By converting observational insight into measurable metrics and actionable recommendations, PalletIQ helps teams reduce waste, improve load consistency, and lower shipping costs. The platform turns routine pallet decisions into repeatable, data-driven processes that scale across operations.