FINANCIAL SERVICES LOGISTICS

ATM cash-out prediction and dispatch agent

ATMs that run out of cash cost money in emergency dispatches and downtime. Wexa built a working agent that predicts cash-outs and creates prioritized refill tasks.

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to build and deploy the working POC
prediction horizon
prediction-accuracy target for the pilot

CLIENT: Global cash-management and secure-logistics company
REGION: Global
WHEN: 2025
ENGAGEMENT: Proof of concept
WEXA COMPONENTS: Prediction agent · dispatch process flow · operations UI

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The challenge

Cash-outs detected after failure
Costly emergency dispatches
Downtime hurts customers; idle cash float

What Wexa built

Ingestion of ATM transactions, balances, events and holidays
Cash-out risk prediction 24–72 hours ahead; at-risk ATMs flagged on a dashboard
Automatic, prioritized refill dispatch tasks with slot assignment
Execution tracking and outcomes logged for the learning loop
Integration design for ATM management, field-service dispatch and vault inventory systems

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How it runs on Wexa

FigureHow this use case runs on Wexa: client systems connected, ontology discovered, context graph in the Wexa memory layer, agents and process flows, and governance. Highlighted components are central to this use case.

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Solution workflow

FigureAgent workflow: data ingestion → risk prediction → risk flagging → task creation → execution tracking.

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Results

Measure	Before / without Wexa	With Wexa
Emergency cash dispatches per year	1,200 dispatches	360 dispatches
Annual cost of the process	$960K	$288K
Time to implement the AI solution	6 months	6 weeks
AI build cost (one-time)	$480K	$44K
AI operating cost per year (models, infrastructure, upkeep, platform)	$312K	$166K
Total AI cost in year 1	$792K	$210K