Conversational Analytics for Retail Distribution
A retail distributor replaced static reports with a natural language analytics interface, demand forecasting, and automated replenishment, deployed in a 3-phase SaaS platform.
The challenge
Business users had no way to query their own data without analyst support. Existing reports were static, updated infrequently, and couldn't answer ad-hoc questions. There was no demand forecasting capability. Planning was reactive. B2B and B2C channels had different optimization needs but shared the same undifferentiated planning approach.
What we built
Phase 1 delivered a unified data structure connecting ERP, e-commerce, and sales systems, plus a chat-based analytics interface for natural language querying. Phase 2 added an AI forecasting engine for stockout prediction and demand planning. Phase 3 introduced a decision intelligence layer with what-if simulation, automated replenishment, and B2B/B2C channel optimization.
Outcomes
Business users query operational data without analyst support
Predictive alerts before inventory runs out
AI-driven replenishment recommendations
3-phase SaaS platform across analytics, forecasting, and intelligence
“Our team went from waiting for weekly reports to asking any question and getting an answer in seconds.”