Flowr — Scaling Up Retail Supply Chain Operations Through Agentic AI in Large Scale Supermarket Chains
Summary: arXiv:2604.05987v1 Announce Type: new
Abstract: Retail supply chain operations in supermarket chains involve continuous, high-volume manual workflows spanning demand forecasting, procurement, supplier coordination, and inventory replenishment, processes that are repetitive, decision-intensive, and difficult to scale without significant human effort. Despite growing investment in data analytics, the decision-making and coordination layers of these workflows remain predominantly manual, reactive, and fragmented across outlets, distribution centers, and supplier networks.
This paper introduces Flowr, a novel agentic AI framework for automating end-to-end retail supply chain workflows in large-scale supermarket operations. Flowr systematically decomposes manual supply chain operations into specialized AI agents, each responsible for a clearly defined cognitive role, enabling automation of processes previously dependent on continuous human coordination.
To ensure task accuracy and adherence to responsible AI principles, the framework employs a consortium of fine-tuned, domain-specialized large language models coordinated by a central reasoning LLM. Central to the framework is a human-in-the-loop orchestration model in which supply chain managers supervise and intervene across workflow stages via a Model Context Protocol (MCP)-enabled interface, preserving accountability and organizational control.
Key Features of Flowr
- Automated Workflow Management: Flowr automates various stages of the supply chain, from demand forecasting to inventory replenishment, reducing reliance on manual processes.
- Specialized AI Agents: Each AI agent within Flowr is tailored for specific cognitive tasks, improving efficiency and accuracy in decision-making.
- Human-in-the-Loop Supervision: Supply chain managers can oversee the entire process, ensuring that human judgment remains integral to operations.
- Model Context Protocol: The MCP-enabled interface allows for seamless interaction between AI agents and human managers, ensuring that accountability is maintained.
- Domain Independence: Flowr’s framework is versatile and can be adapted across various sectors, making it a valuable tool for large-scale enterprises beyond supermarket chains.
Impact on Retail Supply Chains
Evaluation of Flowr has shown significant improvements in several key performance indicators:
- Reduction in Manual Coordination Overhead: The framework has demonstrated a marked decrease in the time and effort required for manual coordination.
- Enhanced Demand-Supply Alignment: Proactive exception handling has led to better alignment between demand forecasting and supply chain capabilities.
- Scalability: Flowr enables large-scale supermarket operations to manage complex supply chains more effectively than traditional manual processes allow.
Flowr was validated in collaboration with a large-scale supermarket chain, showcasing its potential to revolutionize retail supply chain operations. This innovative framework offers a generalizable blueprint for agentic AI-driven supply chain automation across various enterprise settings, setting a new standard in the industry for operational efficiency and accountability.