How Brio achieved effective warehouse inventory management by using Google Cloud ML services for a leading enterprise Conglomerate
A leading Cement manufacturing conglomerate utilized Google Vision and Video intelligence-based models for effective and accountable inventory management. This prevented manual inventory checks, created an effective workflow system across all reporting verticals, saved costs, and promoted innovation.
Challenges
Solutions
- Inventory Stock: Managing stock of several cement sacks coming in and going out of the warehouse was ineffective.
- Inefficient Process: Existing manual methods were slow, error-prone, inadequate, and time-consuming.
- No Centralized System: A single data platform across various data verticals hindered effective comparison.
Brio leveraged Google Cloud’s Vision-based and Video-based Machine Learning Models to train a sack detection model. This helped them to achieve:
- AI-Powered Comparison: Google Vision ML automated SKU analysis and comparison.
- Centralized Platform: All the SKU information was housed in a single, searchable system.
- Automated Detection: The system automatically flagged potential issues with the cement sacks.
- Workflow Integration: Seamlessly integrated into existing design processes.
- Scalable Solution: Handled large volumes and accommodated future growth across various warehouses.
- Improved Efficiency: Automated process saved time and resources.
Business Impact
- Inventory Count: Significantly helped in getting the exact cement sacks going in and out of the warehouse.
- Cost Savings: Lower inventory costs, reduced storage expenses, and less wasted effort.
- Process workflow: Enabled accountability of cement sack stocks across a warehouse, and manufacturing plant.
