Detailed success stories
Real stories from companies that transformed their logistics operations with LogisticsWMS. Discover how you can achieve similar results.
Porto Metalworks: 40% faster picking
Company
Porto Metalworks
Metalworks • 50 employees
Challenge
Porto Metalworks faced serious efficiency problems in their warehouse. With paper picking lists, non-optimized routes and a 30% error rate, the company was losing market competitiveness.
Solution
We implemented LogisticsWMS focusing on route optimization and guided picking. The system's AI analyzed historical patterns and created optimized routes, while the intuitive interface guided employees step by step.
Implementation
Implementation was phased and completed without stopping production. The LogisticsWMS team configured the system, integrated with the existing ERP and guided key employees.
Results
"LogisticsWMS completely revolutionized our operation. The team adapted in days and the results were immediate. I never thought we could be so efficient."
Lisbon Distributor: Zero training time
Company
Lisbon Distributor
Distribution • 25 employees
Challenge
With high staff turnover, Lisbon Distributor spent weeks training new employees. This resulted in high costs and productivity impact.
Solution
LogisticsWMS was configured with an ultra-intuitive interface and guided instructions. The AI adapts to each user's level, providing personalized guidance from day one.
Implementation
Customized setup in 24 hours, focusing on simplicity and usability. We created specific flows for new employees with real-time feedback.
Results
"Now anyone can do picking on their first day of work. It's amazing how the system naturally guides employees."
From Excel to Intelligent Planning
Company
Aveiro Importer
Import • 35 employees
Challenge
Aveiro Importer based all planning on outdated Excel sheets. Decisions were reactive and workload forecasting was non-existent.
Solution
We implemented LogisticsWMS AI for task duration forecasting and automatic planning. The system analyzes historical patterns and external factors to predict workloads.
Implementation
Gradual migration of Excel data to the intelligent system. AI configuration with 2 years of historical data for initial learning.
Results
"We went from reacting to problems to anticipating them. The system predicts work peaks and plans automatically. It's a total game changer."
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