Demand signals
Use product and sales history as inputs for forecasting.
AI ERP for eCommerce
AI ERP that understands the operation behind the dashboard.
Build AI on top of connected product, customer, supplier, inventory, sales, payment and reporting data—so recommendations have operational context.
ShopiERP•••
ASK SHOPIERP
Why did contribution fall this week?
SIGNAL 01Return activity increased
SIGNAL 02Shipping cost moved higher
SIGNAL 03One SKU is driving the change
RECOMMENDED ACTION
Review the affected SKU and campaign before scaling further. Evidence remains linked to the underlying operations.
THE OPERATIONAL PROBLEM
What breaks when the operation starts scaling?
A chatbot sitting beside fragmented systems still has fragmented context. Intelligence becomes more useful when orders, stock, shipping, returns and profit are connected.
INSIDE SHOPIERP
Not a feature list. Parts of the same operating context.
Stock risk
Combine inventory, alert quantities and sales activity to surface risk.
Product anomalies
Identify unusual return, sales or movement patterns.
Contact insights
Use customer/supplier history to provide context to operational questions.
Profitability explanation
Connect sales, cost, return and expense signals.
Recommended actions
Move from “what happened” to a prioritized next step.
HOW THE WORKFLOW CONNECTS
From record to transaction to movement to management answer.
The value is not each module in isolation. It is the same product, contact and transaction context surviving every step.
Observe
Collect structured operational events.
Connect
Relate events to products, contacts, locations and transactions.
Explain
Surface the drivers behind a change or exception.
Recommend
Suggest the next operational action with evidence.
01 • DEEPER DETAIL
AI quality depends on data quality
An AI layer cannot compensate for fragmented product, stock or transaction records. The ERP data model is the foundation.
- Products / SKUs
- Contacts
- Transactions
- Stock movements
- Payments
ShopiERP•••
ASK SHOPIERP
Why did contribution fall this week?
SIGNAL 01Return activity increased
SIGNAL 02Shipping cost moved higher
SIGNAL 03One SKU is driving the change
RECOMMENDED ACTION
Review the affected SKU and campaign before scaling further. Evidence remains linked to the underlying operations.
02 • DEEPER DETAIL
Operational anomalies are cross-module problems
A margin drop may come from returns, purchase cost, shipping or discounting. AI needs to inspect the surrounding operational context.
- Return rate
- COGS movement
- Shipping cost
- Discount activity
ShopiERP•••
ShopiERPCommerce Operating SystemProductsContactsPurchasesSalesStockPaymentsReportsAI
03 • DEEPER DETAIL
The useful output is an action, not a summary
Management needs to know what deserves attention next and why.
- Prioritized alerts
- Evidence behind the alert
- Suggested action
- Follow-up tracking
ShopiERP•••
ShopiERPCommerce Operating SystemProductsContactsPurchasesSalesStockPaymentsReportsAI
THE ARCHITECTURE DIFFERENCE
The same feature can exist in two products. The difference is how it connects.
DimensionDisconnected / traditionalShopiERP
AI contextPrompt + isolated dataConnected ERP operating history
OutputGeneric answerOperational explanation
SignalOne dashboardCross-module context
ValueChat experienceDecision support
WHO THIS IS FOR
For teams where operational complexity is already expensive.
Scaling DTC brandsMulti-store operatorsRegional eCommerce teams
RELATED CAPABILITIES
Keep following the workflow instead of stopping at one feature.
FAQ
Questions before the demo
No. Shopify or WooCommerce remain customer-facing while ShopiERP manages the operating layer behind them.
The platform is designed for multi-warehouse inventory and fulfillment workflows.
It is designed to forecast, detect, explain and recommend using connected commerce data.
Make the demo start with this exact workflow.
Instead of a generic tour, walk through the scenario from source record to transaction, movement and reporting.
Request a Demo