D2C Retail Startup

Optimising inventory with demand forecasting and conversational assistance

Client

Series C direct-to-consumer retailer with multiple fulfilment centres

Timeframe

Deployed in 8 weeks

Stock-outs

-25%

Gross margin

+10%

Incremental annual revenue

10%

Need

Rapid growth strained the startup's supply chain. Forecasts generated in spreadsheets missed local promotions, leading to frequent stock-outs and markdowns.

Our Build

Our team built a forecasting engine that blends historical sales with real-time signals such as events, weather, and marketing, then surfaces recommendations through a chat-based assistant. Store and warehouse managers ask how much they should order and receive narrative guidance. Automated replenishment workflows trigger purchase orders and allocate inventory across the network.

Outcome

Stock-outs fell by 25% and gross margin improved by 10%. The retailer captured an estimated US$8 million in additional annual revenue while freeing managers to focus on customer experience.

"The AI assistant tells us what to order and why; it's like having a planning team in our pocket."

Operations lead, D2C retailer

Forecasting Engine

Historical sales blending

Real-time signal ingestion

Promotion-aware demand planning

Inventory allocation recommendations

Conversational Operations

Chat-based planning assistant

Narrative order guidance

Automated replenishment triggers

Warehouse and store manager workflows