Weoptit helped VR to study how locomotive maintenance schedule optimization can improve rolling stock usage, maintenance resource planning and help choose optimal  maintenance depots. The results aided VR in deciding whether to invest in a new maintenance depot.


Weoptit developed an Artificial Intelligence solution for automatically reading scanned PDF:s containing financial statements of companies. The solution reduced manual labor by 15% already in the first months after implementation.


Weoptit provided LVM a nationwide data-analysis concerning the impact of fuel taxation on Finnish logistics.


Weoptit developed for Vedia an order management system tailored for the logistics sector. 


Weoptit developed data-analytics tools to support Glucomodicum’s product development process. The tools are based on time-series analysis. In addition, a tailored data management system was developed.


Weoptit developed prediction and effectiveness analysis tools for an airline company. The tools help to make preparations and better decisions in a fast-paced operative environment.  Machine learning and data visualization technologies were utilized.

Retail Pricing

Weoptit’s solutions are used by several Finnish companies to track competitor prices online and to generate price recommendations.

EMPLOYEE Rostering

Weoptit has proven that high-quality rosters can be generated for nurses using an optimization-based system. This saves time and money, while enabling consideration of staff preferences better than before.

Vehicle Routes

Weoptit’s world-class routing algorithms have proved valuable for many of our customers. They have been integrated to several logistics planning systems used in Finland.

Production BottleneckS

Weoptit modeled the production process of a factory. Using the model we simulated several future demand scenarios and their impact on production. The  insights helped the client make well-informed investment decisions in their facility.