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We help mid-market retail and distribution teams connect messy systems, normalize operating definitions, and turn that into a decision-ready layer for analytics and AI.
Engagement model
A practical operating-layer workflow designed around the decision first, then the data required to support it.
01
map the decision and current systems
02
build definitions and data flows
03
activate dashboards, workflows, or AI
Most teams are already paying for the systems. The gap is that the systems do not agree.
The service model stays simple: connect the systems, normalize the operating layer, then activate the decisions that matter.
APIs and ingestion across ERP, commerce, warehouse, logistics, and finance systems where operating data is fragmented.
A shared schema for products, orders, inventory, procurement, and locations so teams stop redefining the same entity.
Dashboards, workflows, and AI surfaces built on the same operating truth rather than another custom export pipeline.
Aethrix is built for leaders who need one trusted view of what is selling, what is stuck, what should be bought next, and where margin is at risk.
For teams accountable for inventory, cash, procurement, and margin decisions
Decision-ready operating view
Inventory
one answer to stock position and risk
Cash
clearer exposure from excess and slow movers
Timing
purchasing decisions tied to real demand
Margin
visibility finance and operations can share
Customers are not buying AI as a slogan. They are buying fewer stockouts, less dead inventory, faster decisions, and a path out of manual reconciliation.
We start with the decisions and constraints first, then map the data required to support them.
The goal is not endless bespoke work. It is a deployment pattern that becomes cleaner every time.
Documentation, ownership, and clear operating definitions stay with your team, not inside a black box.
If the use case is right, we will show how the layer would be structured. If it is not, we will say so directly.