01
The operating truth comes first
A forecast is only useful when products, locations, orders, suppliers, lead times, and incoming supply agree. Spark starts by making that foundation visible and ready.
About Spark Inventory
Inventory planning shouldend in a decision.
Spark connects the records that describe an inventory operation with the reasoning and approval path behind what happens next—from onboarding through forecasting, purchasing, warehousing, and production.
Spark operating model
Evidence → decision → control
01
Understand
Products, orders, stock, supply, and history
02
Reason
Demand, timing, economics, and operating constraints
03
Prepare
A mapped import or reviewable operational action
04
Approve
A person decides what actually lands or executes
What guides the product
Built around the decision, not the demo
02
Every recommendation needs a path to action
Inventory intelligence should not end in another dashboard. Spark carries the demand evidence into a reviewable purchasing, fulfillment, or production decision.
03
AI does the work. People keep control.
Sparki and Spark MCP can inspect, map, validate, forecast, and prepare actions. Imports and operational writes remain previewable and approval-led.
Who Spark is for
Operators responsible for both availability and cash
The common thread is an inventory decision that has outgrown disconnected spreadsheets, store plugins, or reports without an execution path.
Read the inventory management guideStart with the operation you have
Bring the data. See the decision path.
Use Sparki in app or your own compatible assistant over MCP to inspect the current operation, prepare the onboarding plan, and show exactly what is ready for approval.