PHARMACEUTICALS

Multi-plant inventory reallocation for a global pharma manufacturer

Stock-outs at one plant while another sits on surplus, coordinated by email and spreadsheets. Wexa built a working inventory console that detects shortages, finds the nearest surplus and routes a transfer for approval.

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to a working end-to-end demo
regions modelled: US, India, Ireland
of transfers with timestamped approvals for GMP audit

CLIENT: Global generic and specialty pharma manufacturer
REGION: US / India / Ireland
WHEN: 2025
ENGAGEMENT: Solution build
WEXA COMPONENTS: Inventory agents · process flows · tables · ERP/IMS integration design

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The challenge

Manual monthly forecasting across many sites and SKUs
Shortages at one site, surplus at another
Email and spreadsheet coordination
GMP audit-trail requirements

What Wexa built

Consumption management and automated shortage handling
Nearest-site surplus check, transfer quantity calculation and stock-transfer requests
Approve / reject flows with escalation to the distribution center
Status indicators (in range, low, critical) and a chat interface
Integration design for ERP, inventory and batch-production systems; on-prem or dedicated cloud

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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

FigureInventory use-case lifecycle: record consumption → evaluate stock → shortage handling → request review → dispatch → live status and audit → chat.

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Implementation plan

FigureEnd-to-end implementation process: integration, rule configuration, workflow build, simulation, pilot, go-live, scale.

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Results

Measure	Before / without Wexa	With Wexa
Excess inventory across plants	$20M	$17M
Annual cost of the process	$5.3M	$4.4M
Stock-outs	Baseline	−25% in 6 months (pilot target)
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