SAP EWM
Intelligent Slotting & Replenishment
Use demand patterns, product velocity, and handling constraints to continuously improve slotting and replenishment decisions.
Applied logistics AI
AI topics that create operational value.
We focus on practical AI use cases that strengthen SAP logistics execution, decision quality, and resilience, without adding another disconnected system.
- SAP EWM
- SAP TM
- MFS
- S/4HANA
AI decisions126 / HR
Confidence94%
Logixi AI operating layer
Observe. Predict. Recommend. Orchestrate.
Our AI layer sits on top of your SAP logistics data. It turns live signals into ranked, explainable recommendations, and keeps people in control of every decision.
Observe
Stream demand, inventory, ETA and equipment events from EWM, TM and MFS.
Predict
Forecast workload peaks, stock risks and delivery delays before they happen.
Recommend
Generate explainable actions ranked by business impact and confidence.
Orchestrate
Execute approved actions in SAP: traceable, auditable and reversible.
Warehouse operations
Labor & Workload Prediction
Forecast inbound and outbound workload so shifts, waves, and automation resources can be planned with greater precision.
Exception management
Predictive Process Monitoring
Detect congestion, stock risks, and process deviations early, then prioritize the exceptions that need human attention.
SAP Transportation Management
ETA & Route Risk Intelligence
Combine live transportation signals with historical performance to improve ETA confidence and identify route disruption risks.
Freight analytics
Cost & Carrier Anomaly Detection
Surface unexpected freight charges, service-level deviations, and carrier performance patterns before settlement.
Yard & dock
Dock Appointment Optimization
Balance yard capacity, door availability, labor, and vehicle arrival patterns for smoother dock operations.
From use case to value
Build an AI roadmap around your SAP logistics priorities.
How we deliver AI
Practical AI, production-ready.
No science projects. We start with a measurable business problem, prove value quickly, then scale securely on your SAP landscape.
Step 1 · 2 to 3 weeks
Use Case & Data Assessment
Prioritize AI opportunities by value and feasibility, and check data quality in EWM, TM and MFS.
Step 2 · 6 to 8 weeks
Pilot & Prove Value
Build a focused pilot with operations users, measured against agreed KPIs and baseline.
Step 3 · Ongoing
Scale & Operate
Industrialize models with monitoring, governance and SAP-integrated actions across sites.
AI readiness
Turn logistics data into better decisions.
Book an AI discovery session and leave with a prioritized use-case shortlist for your SAP logistics landscape.