From inventory checks to settlement analysis, in a single question
Fuses sales, inventory, and settlement databases with market reviews and policy documents through an ontology, turning back-office data analysis into self-service.
Challenges
Retail & Commerce: Today's Challenges
Complex Settlement & Fee Structures
Per-partner fee rates and promotion cost-sharing are intertwined, making settlement verification take days.
Missed VIP Churn Signals
Purchase history and support records live in separate systems, so churn signals from key customers go unnoticed.
Slow Returns & Stockout Analysis
Understanding a spike in returns or the cause of a stockout requires manually cross-referencing data across systems.
Use Cases
Use cases drawn from real demonstration scenarios
Q.“Show me last weekend's luxury section sales versus the week before”
The ontology interprets the category and period conditions and returns the sales comparison instantly.
Q.“Verify this month's partner settlement amounts”
Returns settlement verification results reflecting fee rates and promotion cost-sharing rules, with the full calculation basis.
Q.“Which VIP customers are at high risk of churning?”
Combines purchase cycle changes with support history to flag at-risk customers and suggest actions.
Impact
Impact
Settlement verification
Who runs the analysis
Churn response
Reference — Ontology-based NL2SQL deployment experience with an e-commerce company
Retail & Commerce — want to see it with your own data?
We'll arrange a demo tailored to your data environment and a 4–6 week PoC.