LogisticsAI implementation case study

Logistics – National 3PL Provider: Slotting, Labor & Wave Optimization AI

Full AI automation for dynamic slotting, pick wave generation, labor forecasting, and SLA breach orchestration.

This case study documents a real client implementation. Identifying details may be withheld where confidentiality applies.

Key takeaway

PrimeAxiom automated warehouse operations with AI agents optimizing space, labor, and waves as a single system—not static slotting rules.

The engagement

From operational friction to a connected AI system

01 · Context

Business overview

Industry: contract 3PL. Size: multi-DC. Complexity: omnichannel retail clients.

02 · Challenge

Core problem

Manual slotting, wave inefficiency, labor mismatch.

03 · Approach

Solution

PrimeAxiom deployed warehouse AI: continuous slotting recommendations, AI-built waves, labor forecast agents, and SLA breach automation with carrier rerouting suggestions.

04 · Impact

Results

Pick path efficiency +17%; labor overtime −29%; SLA breach incidents −44%; inventory accuracy +0.3 pts (high-value SKUs).

System design

The full automation system

The implementation connects triggers, AI decisions, business rules, human approvals, and downstream actions in one controlled workflow.

Slotting Agent, Wave Agent, Labor Agent, SLA Agent.

Workflow

How the automation runs

1. Inbound forecast. 2. AI suggests moves. 3. Waves built. 4. Labor rostered. 5. SLA monitors. 6. Carrier exceptions. 7. Feedback loop.

Intelligence layer

AI agents and decision logic

Optimization Agent, Forecast Agent, Risk Agent.

Under the hood

Technical architecture

WMS integration, OR solvers, real-time telemetry.

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