Retail

Common challenges

• Promotion-driven demand spikes.
• High SKU counts with uneven velocity.
• Store-level variability and limited execution data.

What we deliver

• Store-level forecasting and replenishment optimization.
• Dynamic safety stock strategies for core vs. long-tail SKUs.
• Allocation logic that prioritizes service and margin impact.
• Agentic workflows: AI agents that monitor stock positions, trigger replenishment actions, and surface markdown risk by location before it becomes a write-off.

Typical outcomes

• Higher in-stock rates without overbuying.
• Reduced markdown exposure.
• Faster replenishment cycles.