Automated Inventory Count Using Computer Vision
Revolutionary computer vision system enabling 24/7 automated inventory tracking through autonomous robots and real-time AI analysis.
Key Results
Overview
A major retail chain with 200+ locations struggled with inventory accuracy and the massive labor costs of manual counts. Traditional methods required closing stores overnight, deploying large teams, and still resulted in significant errors. We developed an autonomous robotics solution powered by computer vision that continuously monitors inventory during normal business hours.
The Challenge
Manual inventory counts required closing stores, involved hundreds of staff hours, and had 15-20% error rates
Problem Statement
Each store required 20-30 staff members for overnight inventory counts twice per year, costing $50,000+ per location. The 15-20% error rate led to stockouts, overstock situations, and poor customer satisfaction. Management lacked real-time visibility into inventory levels across the chain.
The Solution
Deployed autonomous robots with computer vision for continuous, real-time inventory tracking without disrupting store operations
Our Approach
Designed autonomous robots with 360° camera arrays and LiDAR
Trained object detection models on 500,000+ product images
Developed shelf mapping and navigation algorithms
Built computer vision pipeline for product recognition and counting
Created real-time analytics dashboard for inventory management
Implemented predictive algorithms for stock-out prevention
Integrated with existing point-of-sale and ERP systems
Implementation Timeline
Phase 1: Pilot Development
4 monthsBuilt prototype robot with vision system and tested in controlled environment. Collected product imagery and trained initial recognition models.
Phase 2: Store Pilot
3 monthsDeployed 3 robots in pilot store, refined navigation algorithms, improved model accuracy, and validated count accuracy against manual counts.
Phase 3: Software Platform
4 monthsDeveloped cloud platform for fleet management, analytics dashboard, predictive algorithms, and ERP integration.
Phase 4: Rollout
6 monthsScaled to 50 stores with fleet of 150 robots. Trained store staff, optimized operations, and achieved full automation.
Technologies Used
We never imagined inventory counting could be this accurate and effortless. The robots work overnight while the store is closed, and we wake up to perfect counts every morning.
Michael Chen
VP of Operations, Global Retail Corporation