Orchestrating Complex Operational Decisions in Production with O137
How a global logistics and transport operator centralized AI governance across warehouses, carriers, and customs to eliminate decision inconsistencies and operational risks.
Client Context
An international logistics and transport operator managing:
The company had started integrating AI for:
- •Volume forecasting
- •Planning assistance
- •Anomaly detection
- •Partial decision automation
The Problem
AI was working... but it was no longer under control.
1. Critical Decisions Made Without Global Control
Teams were using:
- •Different models
- •Different scripts
- •Different rules
All without a unified view.
Result:
- • Inconsistent decisions
- • Untraceable arbitrations
- • Strong dependency on local implementations
2. No Real Governance
Impossible to answer simple questions:
- •Why was this decision made?
- •Which model was used?
- •What data was used?
- •What business rules were applied?
This level of opacity is incompatible with industrial-scale operations.
3. High Operational Risk
- •No fallback if a model fails
- •No centralized cost control
- •No clear distinction between automatable decisions and those requiring human escalation
The O137 Solution
O137 is deployed as the central AI control system.
1. Connection to Existing Systems
O137 connects directly to:
- •ERP (orders, billing, customer priorities)
- •TMS (carriers, capacity, SLAs)
- •Field data (delays, incidents, sensors)
- •External sources (weather, customs, local constraints)
👉 O137 is not a source of truth—it relies on existing systems.
2. Multi-Model Orchestration
To analyze a situation (delay, overload, constraint conflict), O137 can:
- •Use multiple AI models
- •Compare their results
- •Arbitrate based on:
Models are interchangeable:
- • No lock-in
- • Automatic fallback
- • Evolution possible without breaking the system
3. Contextual Decision Making
O137 doesn't just produce a response. It reasons from:
- •The global system state
- •Decisions already made
- •Defined business rules
- •Acceptable risk thresholds
Example:
- • Automatically reschedule certain shipments
- • Propose multiple scenarios ranked by impact
- • Escalate only high-risk cases requiring human intervention
4. Governance and Traceability
Every decision is:
- •Timestamped
- •Linked to data used
- •Associated with models called
- •Explained by rules applied
👉 Result: auditable, explainable, and deployable AI in critical environments
Results Observed
After deployment:
What O137 Enables
In Summary
O137 transforms AI from a collection of isolated tools into a governed, traceable, and controllable system that operates at the heart of critical business processes. It's not about replacing existing systems—it's about orchestrating them intelligently.