Retail AI Solutions — Arc Collective

Use Cases

Pain Point: Data fragmented across e-commerce platforms, POS systems, supply chain tools, and marketing channels. No single source of truth for operational decisions.
Solution: AI connects and normalizes data across all channels — e-commerce, in-store POS, warehouse management, and marketing platforms — into a unified operational view.
Result: Real-time visibility across all channels. Decisions based on complete data, not partial snapshots from individual systems.

Pain Point: Massive SKU count makes manual category management impossible. Demand patterns buried in transaction data. Assortment decisions rely on merchant intuition.
Solution: AI analyzes SKU performance across locations, seasons, and customer segments. Surfaces category optimization opportunities, demand signals, and underperforming assortments.
Result: Data-driven assortment decisions. Better sell-through rates, reduced markdowns, and optimized shelf space allocation across store formats.

Pain Point: Replenishment, inter-store transfers, and allocation decisions made manually based on rules of thumb. Long decision cycles in a fast-moving retail environment.
Solution: AI automates routine supply chain decisions — replenishment triggers, store-to-store transfers, allocation priorities — based on real-time demand signals and inventory levels.
Result: Faster replenishment cycles, reduced stockouts, better inventory balance across locations. Human planners focus on strategic decisions.

How It Works

Connect

Integrate with POS, e-commerce, WMS, and marketing platforms. Unify data without replacing existing systems.

Unify

Normalize product, customer, and transaction data across channels into a single operational model.

Predict

AI forecasts demand, identifies optimization opportunities, and flags inventory imbalances.

Act

Automated replenishment, transfer, and allocation decisions execute in real time. Exceptions routed for human review.