The Problem
Optimization is only as good as the data underneath it.
An optimizer leans hard on every input, and the interactions between them create blind spots that can quietly undermine the result. And those values are mostly taken on trust: set once, copied forward, never checked.
One bad input throws the solve. An optimizer leans on every value at once, so a single outlier can skew the entire plan.
The numbers go unchecked. Most are set once and copied forward, never tested against anything.
In isolation, nothing looks wrong. A value that's fine on its own can still break in combination, so field-by-field checks miss it.
Dataplane Approach
From inputs that drift to a model that keeps them consistent.
Model the entities
Map SKUs, locations, and suppliers, and how they relate, into one shared model that defines what each input means.
model · define · relateBind every input
Connect ERP, WMS, and supplier feeds to that model so each value lands on the entity it describes.
connect · resolve · bindEnforce the constraints
Define consistency rules at the entity level so contradictions get caught and corrected before the optimizer sees them.
constrain · validate · enforceOutcomes
Where You Feel It
When the inputs agree, every dial moves the right way.
Better targets mean less stock that ages out.
Stock ends up where demand actually is.
Less capital tied up in stock you don't need.
More cash freed from the warehouse floor.