Computer Vision

Computer Vision

Project overview

Project overview

AI-powered computer vision automated inventory tracking, raising accuracy to 99.7%, cutting manual work by 95%, and reducing expired medicine waste by 98%.

AI-powered computer vision automated inventory tracking, raising accuracy to 99.7%, cutting manual work by 95%, and reducing expired medicine waste by 98%.

Challenges

Challenges

The challenge includes costly operations with 15% higher operational costs compared to automated systems, time-consuming processes where staff spend around 40 hours weekly on manual inventory tasks, and error-prone management with only a 63% accuracy rate in conventional inventory systems.

The challenge includes costly operations with 15% higher operational costs compared to automated systems, time-consuming processes where staff spend around 40 hours weekly on manual inventory tasks, and error-prone management with only a 63% accuracy rate in conventional inventory systems.

Our Approach

Deployed computer-vision capture workflows and integrated outputs into inventory systems.

Trained OCR and verification models to detect items, quantities, and expiry details accurately.

Automated exception handling for low-confidence reads to improve accuracy with feedback.

Automated exception handling for low-confidence reads to improve accuracy with feedback.

Impact Delivered

Impact Delivered

The solution, InventStory, uses automated capture through high-resolution cameras to record images of medicine boxes, applies AI analysis with computer vision and OCR to extract and verify data, and provides real-time updates by synchronizing with databases for immediate and accurate inventory management.

The solution, InventStory, uses automated capture through high-resolution cameras to record images of medicine boxes, applies AI analysis with computer vision and OCR to extract and verify data, and provides real-time updates by synchronizing with databases for immediate and accurate inventory management.

Download Case Study

Download Case Study

Download Case Study

Download Case Study

Download Case Study

Download Case Study

Download Case Study

Download Case Study

Download Case Study