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 a data analytics tool using our own algorithms. The tool will help determine the prices of used cars and give accurate suggestions to the sales personnel. “The solution helps buyers handle large volumes of cars quickly, acts as a backup mechanism and identifies potential emergencies” – Mikki Inkeroinen, CDO Kamux Oyj

Alma talent

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 developed a solution that reads data and inputs it back in the correct format to Remeos system. We developed a new algorithm that evens out the waste pick up frequency on a weekly basis. The solution takes into consideration key factors and forms optimal routes for each day in a large city-wide area.


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.

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.