Intelligent Shelf Management with AI-Powered Retail Agents
The Challenge: Static Shelves in a Dynamic World
The retailer faced significant inefficiencies in managing in-store inventory and shelf operations, impacting sales, compliance, and customer satisfaction.
Key pain points included:
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Undetected Stockouts: Out-of-stock items were often only identified after customer complaints, leading to lost sales.
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Poor Planogram Compliance: Shelf layouts were inconsistently executed, reducing visual merchandising effectiveness.
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Time-Consuming Manual Audits: Manual shelf checks were slow, labor-intensive, and prone to human error.
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Inefficient Replenishment: Lack of real-time insights prevented dynamic optimization of stock levels and replenishment schedules.
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Limited Visibility: Minimal monitoring of shelf-level product movement hindered operational decisions and analytics.
These challenges highlighted the need for an intelligent, automated shelf management system capable of real-time monitoring, anomaly detection, and actionable insights to improve store performance.
The Amantra Solution: Autonomous Shelf Monitoring Agents
Amantra implemented an AI-powered shelf management system that combined computer vision, Large Language Models (LLMs), and intelligent agents trained on retail SOPs and planograms. This autonomous framework enabled real-time monitoring, anomaly detection, and actionable insights for store operations.
Key Capabilities:
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Real-Time Shelf Analysis: Agents analyzed live images from in-store cameras to monitor inventory and product placement.
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Anomaly Detection: Empty slots, misplaced items, and expired goods were automatically identified for immediate action.
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Planogram Compliance: Shelf layouts were continuously cross-referenced with digital planograms to ensure proper merchandising.
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Automated Task Assignment: Refill alerts and corrective tasks were generated and assigned to store staff in real time.
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Integration with ERP & Inventory Systems: Insights were fed into backend systems to optimize replenishment planning, inventory accuracy, and operational efficiency.
This intelligent shelf management framework transformed manual store audits into a continuous, automated, and data-driven process, improving compliance, product availability, and overall customer experience.
Key Features
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Computer Vision-Powered Shelf Scanning: Continuously captures shelf images to monitor product placement and stock levels.
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Agentic Planogram Compliance Check: Intelligent agents compare real-time shelf layouts against digital planograms to ensure merchandising standards.
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Real-Time Stock-Out Alerts: Automatic notifications for empty slots to prevent lost sales.
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Integration with WMS/ERP: Insights are synced with backend systems for optimized restocking and inventory planning.
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Self-Learning Agents: Agents continuously learn shelf patterns and improve detection accuracy over time.
Business Outcomes
| Metric | Before Amantra | After Amantra |
|---|---|---|
| Shelf Audit Frequency | Weekly | Daily (Automated) |
| Stockout Duration | ~12 hrs | < 1 hr |
| Planogram Compliance | ~60% | ↑ 95% |
| Manual Shelf Walks | 5 per day | ↓ 80% Reduced |
| Lost Sales due to OOS | High | ↓ 30% |
Client Testimonial
“Amantra turned our shelves into live dashboards. We no longer lose sales because we didn’t know a shelf was empty.” — Retail Operations Head, Hypermarket BrandWhy Retailers Need Smart Shelf Management
In the modern retail environment, shelves need to act like sensors—providing live feedback, enabling fast action, and ensuring maximum product availability. With Amantra agentic AI, retailers can:- Automate store audits
- Eliminate stock-out delays
- Maintain flawless planogram execution
- Empower staff with precise, real-time actions