Case studies
Project status
Completed
100%
Date
July 2017- December 2024
Optimizing production processes
We implemented a machine learning system to forecast production needs, resulting in a 20% improvement in production efficiency.
Within the "Optimizing Production Lines in Manufacturing" project, our company implemented cutting-edge artificial intelligence technologies to revolutionize the efficiency of manufacturing processes at a major automobile production plant.
Challenges and objectives
- Aim to increase overall productivity by 15%.
- Reduce defects by 25%.
- Optimize energy consumption to enhance environmental sustainability.
Solution
We developed and implemented a machine learning system for predicting and optimizing operational parameters of production lines.
Results
- Achieved a 17% increase in overall productivity, surpassing the target.
- Reduced defects by 28%, improving the quality of the final product.
- Optimized energy consumption by 12%, leading to a reduction in environmental impact.
Project status
Completed
100%
Date
May 2021 - November 2021
Automation of routine tasks in finance
Introducing a robotic processor to automate routine tasks in the finance department saved up to 30% of employees time.
Within the "Automation of Routine Tasks in Finance" project, our company implemented cutting-edge artificial intelligence technologies to enhance the efficiency of financial processes at a major financial institution.
Challenges and objectives
- Effectively automate routine financial operations to reduce human intervention.
- Increase accuracy in transaction processing and minimize the risk of financial errors.
- Reduce time spent on performing routine tasks.
Solution
We developed and implemented a machine learning-based automation system for processing routine financial operations, such as invoices, statements, and internal transactions.
Results
- Reduced time spent on routine tasks by 30%, allowing financial department employees to focus on more strategic aspects of their work.
- Increased accuracy in transaction processing by 25%, minimizing the possibility of financial errors.
- Improved overall efficiency of financial management through the optimization of time and resources.