Smita Gupta@SmitaGupta

Retail associates lose 23% of their shifts searching for product information, inventory data, and safety policies, costing large-format retailers an average of $1.2 million per store annually. Generic knowledge tools fail to address the complex access control and safety compliance required on the retail floor. BullsAI SAKS (Store Associate Knowledge System) is a purpose-built, role-aware, multi-agent AI knowledge platform designed to eliminate this gap. Engineered specifically for enterprise retail, BullsAI SAKS leverages a LangGraph multi-agent architecture to orchestrate specialist agents (Product, Inventory, Safety, and Policy) that instantly retrieve precise answers across a Retrieval-Augmented Generation (RAG) pipeline of more than 500,000 SKUs. Our system features a robust 7-tier Role-Based Access Control (RBAC) engine with strict store-level data isolation, ensuring that every user—from a trainee to a regional manager—only accesses appropriate, role-filtered information. By integrating deterministic tool use and a human-in-the-loop safety escalation protocol, BullsAI SAKS delivers highly accurate responses with a demonstrated 48-millisecond pipeline response time. Protected by comprehensive compliance standards, multi-layer PII detection, and a 100% tamper-proof audit trail, BullsAI SAKS empowers store associates to serve customers instantly, efficiently, and safely without ever having to leave the retail floor.

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