Client Overview
The client is one of Italy's largest beef importers, dealing with hundreds of shipments daily. The manual process of managing inventory, recording product details, and updating the ERP system was proving to be highly inefficient and prone to errors. They sought a solution that could automate these repetitive tasks, streamline operations, and enhance accuracy.
Challenges or Business Objectives
- Managing the manual, time-consuming process of stacking and summarizing inventory for hundreds of beef boxes.
- Reducing the high likelihood of human errors in data entry and inventory management.
- Automating the integration of product information into their ERP system to improve efficiency.
Strategy or Solution
- Conducted a thorough analysis of the client’s existing business processes.
- Developed and deployed a fully automated Logistic & Inventory system.
- Implemented OCR AI-based solutions to minimize human involvement in processing shipping slips.
- Integrated the automated system with the client’s ERP for seamless updates.
Development Method - Execution Method
- Analysis: Identified key areas for automation in the client’s processes.
- CNN Model: Developed a Deep Learning model to detect valid shipping slips in large image stacks.
- OCR Algorithms: Created intelligent OCR algorithms to extract and process key information, removing irrelevant data.
- ERP Integration: Enabled one-click updates to the ERP system for inventory and product details.
Impact We Made
- Productivity: Significantly boosted by automating repetitive tasks.
- Accuracy: Enhanced through the use of OCR AI, reducing errors in data processing.
- Operational Efficiency: Streamlined logistics and inventory management, leading to faster and more accurate processing.
Tech Strategy
- Utilized CNN Deep Learning for slip detection.
- Implemented OCR and AI algorithms for data extraction.
- Seamlessly integrated the system with the ERP.
- Designed a scalable architecture to accommodate future growth.
Conclusion:
CrossML successfully transformed the client’s logistics and shipment tracking processes by implementing a fully automated system that reduced manual work, increased accuracy, and streamlined operations. This project demonstrated CrossML's capability to understand complex business challenges and deliver tailored solutions that drive efficiency and scalability.
