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Agentic AI · Move
Substitution Decision Agent
Autonomous agents that perceive, decide and act across systems — executing multi-step workflows end-to-end.
Medium impactIdentified
Business objective
Reduce stockouts and fulfilment cost while accelerating cycle time.
Value
Meaningful operational lift — productivity, speed or quality gains.
Who uses it
Supply ChainLogisticsStore Operations
Business outcomes
- Always-on execution across systems
- Lower unit cost of routine work
- Faster cycle time and SLA adherence
How it works — workflow
Typical agentic ai loop powering this use case.
Step 1
Perceive event
Step 2
Plan multi-step action
Step 3
Execute across systems
Step 4
Human-in-loop for exceptions
Step 5
Measure & self-correct
Data required
- • Live event streams
- • Operational thresholds & rules
- • System APIs for action
- • Outcome telemetry for learning
- • Guardrails & audit logs
Connected systems
- • WMS
- • TMS
- • OMS
- • Store inventory
- • IoT / cold-chain sensors
Business processes
- • Inbound & DC operations
- • Store replenishment
- • Last-mile & click & collect
- • Returns & reverse logistics
- • Cold chain & compliance
What's required to be successful
- Reliable, real-time integrations
- Decisioning + guardrails
- Action APIs across systems
- Observability & audit
- Reversibility / human-in-loop
Underpinned by the Xfuze Foundation — see the five pillars.
Related use cases
Same stage or AI type — useful when scoping an end-to-end ambition.
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