Retail

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Product Demand Forecasting: Generates detailed demand distributions for product categories, aiding in precise inventory management and reducing lost sales.​

Operational Policy Evaluation: Assesses the impact of various AI policies on metrics like revenue, profits, and out-of-stock events, facilitating data-driven decision-making.​

Employee Task Scheduling: Simulates employee roles, availability, and task priorities to optimize workforce utilization and enhance operational efficiency.​

AI-Driven Restocking Prioritization: Integrating AI with simulation guides employee task prioritization, ensuring prompt restocking of high-demand products to minimize out-of-stock events.​

Customer Behavior Simulation: Models pedestrian agents with varying shopping behaviors, providing insights into customer interactions and store dynamics.​

Synthetic Data Generation: Simulation creates extensive, minute-by-minute product demand data over multiple years, enabling AI models to predict future demand accurately.​

AI Model Training and Validation: Provides a controlled environment to generate synthetic data for training AI models, ensuring robust and effective solutions ready for real-world deployment.​