Scenario Solutions / Retail
Retail

Use AI to reconstruct global operating decisions across people, products, and places

For large retail groups, brands, convenience chains, and e-commerce supply-chain enterprises, 01.AI helps customers build a cognitive retail brain across people, products, and places.

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Industry Pain Points

Demand-supply disconnect and inventory imbalance

Traditional forecasting models struggle with rapidly changing market demand, causing both stockouts of hit products and high inventory of slow-moving goods.

Operating strategies are fragmented

Marketing, pricing, channel, and advertising strategies are fragmented and lack global ROI evaluation, often leading to inefficient promotions and price wars.

People-product-place data is disconnected

POS, supply chain, membership CRM, public-domain traffic, and other data are disconnected, making global insight difficult.

Frontline operations depend on experience

The loss of supervisors, store managers, and merchandising managers directly affects store performance, and excellent management experience is difficult to standardize and replicate.

Retail scenario illustration

Solution

Built on 01.AI's enterprise AI decision hub TrueNorth, and combining multi-agent and ontology technologies, create a cognitive retail brain.

  • Build a retail business fact base

    Build a retail business fact base with ontology, integrating product master data, sales transactions, inventory turnover, user profiles, promotion strategies, and external environment data such as weather, holidays, and competitors. Ontology-based semantic alignment fundamentally reduces AI hallucination.

  • Deploy collaborative multi-agents

    • Demand Forecasting and Replenishment Agent: dynamically captures market signals and automatically simulates optimal inventory and replenishment paths.
    • Dynamic Pricing and Promotion Agent: simulates cognitive debate among heterogeneous agents over pricing strategies to find the best balance between profit and sales volume.
    • Intelligent Assortment and Display Agent: uses store-level profiles to realize precise shelf digitization with a one-store-one-strategy approach.
  • Create a decision loop

    Agents collaborate across domains, from detecting abnormal sales fluctuations to root-cause analysis, automatic supply-chain scheduling adjustment, and coordinated precision couponing, forming an end-to-end perception-judgment-execution-feedback decision loop.

Expected Outcomes

More Efficient Product Operations

Shift toward a demand-driven supply chain, reducing stockout rates and slow-moving inventory days while improving capital turnover.

More Precise Marketing

Enable dynamic pricing and precision marketing, with every unit of budget supported by full-chain ROI simulation.

Replicable Organizational Capability

Codify the experience of top store managers and assortment experts so frontline employees can obtain real-time operating guidance through natural language.

Use AI to reconstruct global operating decisions across people, products, and places.