Food & beverage / solution example

What you use today changes what you can make years from now.

Compare what to consume today with what to preserve for future products and demand.

Aged-liquid allocation
Aged-liquid allocation - illustrative connected workflowAGED STOCK / ONE CHOICE, TWO HORIZONSMatureinventoryUse nowMeet current product demandKeep agingPreserve future eligibilityQuality rules + evaporation + future targets
Illustrative workflow and data. The implementation follows your business rules.
The business problem

Inventory age is both an opportunity and a constraint.

Product eligibility, liquid characteristics, evaporation, and future targets interact across the planning horizon. Build an allocation model that exposes those assumptions and compares alternatives.

01

Establish eligible inventory

Connect barrels, age, measurements, availability, and product-specific requirements.

02

Model use versus preservation

Evaluate current consumption alongside maturation, loss assumptions, and future production needs.

03

Compare allocation scenarios

Contrast a baseline policy with a constrained plan and explain where targets or eligibility bind.

The workflow in practice

Preserve the options you still need.

Compare product targets across the full planning horizon.

What You Use Today Changes What You Can Make Later.WHAT YOU USE TODAY CHANGES WHAT YOU CAN MAKE LATER.Aged stockAge, proof, volumeAllocation choiceUse now or keep agingFuture supplyEvaporation and maturityUse for productionMeet current targetsKeep agingPreserve future optionsReview scenariosCompare the trade-offsCompare product targets across the full planning horizon.
Illustrative workflow and quantities, not customer results. On smaller screens, scroll the diagram to inspect the detail.
From source records to a decision

A decision you can trace.

A mature barrel can help satisfy today's target, but consuming it removes eligible stock from a later premium product.

Current choice

Consume eligible liquid now

Alternative

Preserve stock for a later product

Comparison

Targets met and future shortages by scenario

Illustrative scenario, not measured customer results.
A useful role for an agent
What does this allocation preserve for the later production target?

An agent can explain a saved optimization result, show binding constraints, and compare it with the chosen baseline policy.

Keep the decision with the right person.

Planners validate model assumptions and quality requirements before acting on an allocation.

Designed around your business

Your data.
Your rules.
A connected system.

Capture the requirements and definitions in project context. Connect the relevant records. Use agents to develop the interfaces, calculations, tools, and workflows on managed infrastructure.

Product eligibilityMinimum ageEvaporation assumptionsMulti-period targets
Explore the platform

Barrel inventory

Age, quantities, location, and availability

Quality and product rules

Measurements, blend specifications, and minimum age

Planning horizon

Production targets and aging/loss assumptions

Applications, APIs, data, and agents on Vortexify.
Useful things to trackTarget attainmentEligible inventoryFuture shortage exposure
Your next system

Build around your work.

Start from your own requirements, use research and design references where helpful, and choose how your team wants to build.

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