2 min read
Put the semantic layer before the algorithms
If your team can't agree what a 'sale' or 'on-hand' means, no model—however clever—will fix replenishment.
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AethrixOperational data layer for inventory decisions
Turn fragmented systems into decisions your team can trust.
Your team already knows which decision needs to be made. The problem is the data behind it lives in three systems, two spreadsheets, and someone's inbox. Aethrix gives operations, supply chain, and finance one clean layer — so the answer is ready before the meeting starts.
No rip and replace
Built around operating decisions
AI-ready from day one
People making decisions
Your Team
OperationsSupply ChainFinanceProcurement
Activation Layer
Aethrix
AI-ReadyDecision-DrivenAlways Connected
Systems you already use
Your Data
ERP / NetSuiteCommerceWMS / 3PLFinance Systems
People making decisions
Your Team
OperationsSupply ChainFinanceProcurement
Activation Layer
Aethrix
AI-ReadyDecision-DrivenAlways Connected
Systems you already use
Your Data
ERP / NetSuiteCommerceWMS / 3PLFinance Systems
4
system families — ERP, commerce, WMS, finance
1
shared layer your whole team trusts
0
new dashboard theater required
Systems we unify
You're already paying for NetSuite, Shopify, and your WMS.
They just don't agree on what 'on-hand' means when it counts.
NNetSuite
SSAP
DDynamics
SShopify
PPOS
WWMS
33PL
FFinance
EExcel
BBI
NNetSuite
SSAP
DDynamics
SShopify
PPOS
WWMS
33PL
FFinance
EExcel
BBI
Everything important, finally in one operating view
The first win is not more reporting. It is a trustworthy layer for the decisions your team already has to make every week.
One operating language
Products, orders, inventory, procurement, and locations mapped once so teams stop debating definitions.
Cross-system visibility
ERP, commerce, warehouse, and finance signals pulled into a layer that can survive leadership questions.
Decision workflows
Built around actions like reorder, transfer, buy, or exit inventory instead of another static dashboard.
Think of Aethrix the way you think of a shared language between departments. Finance calls it “on-hand.” Ops calls it “available stock.” Your WMS has a third number entirely. We align those definitions once — so every decision downstream starts from the same truth.
What gets installed first
Definitions your team can explain without a meeting
Before dashboards or AI, we align the entities and metrics that drive daily decisions: sellable stock, demand, open orders, lead time, allocation, landed cost, and margin.
- A shared map of SKUs, locations, suppliers, orders, and costs.
- Lineage that connects reports back to the systems of record.
- Decision outputs that point to reorder, transfer, buy, hold, or exit.
Decision layer
Semantic layer map
A shared map of the entities, signals, and constraints behind replenishment, stock exposure, procurement, and margin.
ERP
WMS
POS
Finance
Planning
AI
Shared operating layer
SKU
mapped across systems
Location
store, warehouse, 3PL
Margin
visible next to inventory
Why teams call us
The problem isn't missing tools. It's missing agreement.
Fragmented operating data, inconsistent definitions, and a planning process that falls back to spreadsheets every time someone questions a number.
Excel became the reconciliation layer
Sales, stock, procurement, and cost data live in different systems, so reporting only works after manual stitching.
AI projects stall before they start
Teams are told to clean data for months before they can test a real operational use case.
Core decisions are still guesswork
Reorder, transfer, buy, and exit decisions remain hard to answer consistently across the business.
Use cases
Start where decisions are already expensive
Aethrix is built for practical inventory and margin decisions, not abstract data transformation.
Replenishment optimization
Align what you buy with what actually sells—so cash stays available and shelves stay stocked.
Signal qualityDecision owner
Dead stock reduction
Surface slow movers early and reallocate before margin erodes across the network.
Signal qualityDecision owner
Procurement timing
Buy at the right moment for lead times and demand—not when spreadsheets say “eventually.”
Signal qualityDecision owner
Installed layer
Between systems of record and real decisions
Not another ERP. Not just a dashboard. Aethrix sits in the gap where fragmented operating data becomes a layer teams can use.
- Connect the systems that hold demand, stock, orders, suppliers, and costs.
- Normalize definitions before automation depends on them.
- Activate outputs in dashboards, workflows, planning tools, or AI surfaces.
Between systems of record and real decisions
Decision-ready operating view
$5M-$100M
typical revenue band in focus
2/3
still plan in spreadsheets
3
entry wedges already validated
1
shared operational truth
Shared definitionsLive
SKUMapped
LocationMapped
SupplierMapped
OrderMapped
Operator credibility
From operators who worked directly with Rajiv on analytics and implementation.
Aethrix is led by Rajiv Pardhan. These are signals from people who saw the work up close.
Operator signal
Actionable operating decisions
A
Operator reference“Rajiv has an exceptional ability to translate complex data insights into actionable business strategies. His leadership in our ML initiatives was instrumental in achieving significant cost reductions while improving customer satisfaction.”
Operator signal
Scalable data foundations
A
Operator reference“Working with Rajiv was transformative for our analytics capabilities. His expertise in building scalable data solutions and mentoring team members made him an invaluable asset to our organization.”
Insights
View all insightsPractical notes for teams living with the problem now.
Short, plain-language thinking on operational data, inventory, and AI readiness.
Ready to stop reconciling first and deciding second?
Tell us which operational question still takes too long to answer. We’ll map whether Aethrix is the right foundation — in one conversation.
FAQs
Common questions from teams evaluating implementation
Short answers to the questions we hear most before teams commit to implementation.
How long until we have a clean operating number we trust?
Most teams have a shared operating definition in place within 3–4 weeks. Full implementation — connected systems, normalized definitions, and a live decision layer — typically runs 4–6 weeks end to end.
Do we need an internal data team?
No. Aethrix provides complete implementation support, so teams can move forward without hiring a full in-house data function first.
What if our data is scattered across Excel, CSV, and PDFs?
We are used to fragmented operating data. We connect those inputs into a unified layer teams can trust for reporting, workflow decisions, and implementation.