Fresh Servant - machine learning to boost production

Fresh Servant, the market leader in consumer-packaged salads, is increasingly using machine learning-based sales forecasts and efficient application development in its growing business. With the solutions implemented by Pinja, business is now managed in a data-driven and resource-efficient way.

The cooperation in brief

Data warehouse for better reporting

The cooperation between Fresh Servant and Pinja began in early 2020, starting with a data warehouse and reporting development project. Fresh Servant’s business data were already available for a long period of time, for example in the ERP system, but the project automated the cleaning and transformation of the data into a format that allows more efficient use and analysis: from figures to information, and finally to action.

Application development took demand and production planning to a new level

Demand and production planning, previously handled in Excel, was transferred to applications that communicate with both the client’s ERP and the data warehouse, thanks to a collaboration between Fresh Servant and Pinja. This improved the manageability of the design work, and reduced manual work and dependency on people.

Cooperation extended to machine learning and forecasting

In spring 2022, the collaboration was extended to include machine learning and demand forecasting. In the future, it will be possible to plan production, procurement and human resources more accurately, thus improving cost efficiency and reducing waste.

Pinja’s implementations have been successful in all respects. The successful applications have given us a whole new range of opportunities to develop other activities more broadly.

Juha Tiitto, Planning and Development Manager, Fresh Servant

Application development facilitates everyday work, and improves the flow of information

Fresh Servant, a provider of ultra-fresh food solutions for store shelves and professional kitchens, is guided by three core principles: the product it offers its customers must be tasty, beneficial to health and of high quality. These principles have helped the business grow consistently, right up to today’s digital management of data and effective knowledge management.

Fresh Servant’s collaboration with Pinja started in early 2020 with the development of a data warehouse and reporting and expanded relatively quickly into application development and machine learning and forecasting. The expansion from one area to the next of efficient data processing has been quite natural and logical, as all developments are ultimately interlinked.

“We’ve been keen to invest in development because automating routine operations improves speed and accuracy, among other things. At the same time, it brings more depth to the work,” says Carita Haapasalmi of Pegasso Oy, who leads Fresh Servant’s data and tool development.

The app development has helped Fresh Servant to move demand and production planning from Excel to mobile applications. The applications communicate with Fresh Servant’s ERP system and the underlying data warehouse, helping reduce manual work and diversify operations. The development work brought relief to previously difficult and cumbersome data management.

“Pinjans have clearly wanted to look at things from our point of view, and produced value-adding solutions. I also appreciate their solution-oriented approach, and the cooperation has broadened our views too,” says Juha Tiitto, Head of Design and Development at Fresh Servant.

One of the key benefits of the development work is that demand planning data can now be shared seamlessly across all internal processes. The applications also make practical work easier by enabling the acknowledgement of faults on the production lines using tablets. This allows us to collect valuable data on production line failures and faster processing of cause-and-effect relationships.

“Pinja’s implementations have been successful in all respects. The successful applications have given us a whole new range of opportunities to develop other activities more broadly,” Titto says.

Machine learning extends the time span of forecasts

The latest area of collaboration between Fresh Servant and Pinja is the use of machine learning to predict sales. Initially, Fresh Servant used people to do it, then mathematical formulae based on previous year’s sales figures. The development project introduced machine learning, and the forecasts introduced in fall 2022 have taken the forecasting work in a very promising direction. Demand forecasts already proved to be more accurate than those produced by hand and mathematical calculations during the testing phase.

“We are in the early stages of development, but we already see machine learning increasing the variety of demand forecasts, extending the time horizon of forecasting and deepening our understanding,” Tiitto says.

In a mutual machine learning development project between Fresh Servant and Pinja, different machine learning methods have been tested and iterated together to see which one works best for which customer group and product. Machine learning-based forecasts can minimize manual work, but also take information entered by people into account, such as campaigns to boost sales, where appropriate. The door is also open to the possibility of applying machine learning to other areas of business in the future.

The cooperation between Fresh Servant and Pinja, which started with data warehouses and reporting development, and gradually expanded to application development, machine learning and forecasting, has shown a natural progression. As a result, Fresh Servant’s key business data are used to comprehensively and in a variety of ways improve production efficiency, supply security and sales development – and ultimately to maintain and improve customer satisfaction.

“We sourced the whole package from Pinja, because they already had a good understanding of the food industry, and they know our data and processes well. It’s easy to trust their expertise. The solutions provided by Pinja also communicate with each other,” reducing our work, says Haapasalmi.


Machine learning refers to the area of artificial intelligence where a machine improves its performance by learning autonomously from data. The purpose of machine learning is to make software work better based on the data it receives and the user’s actions. From a technical point of view, machine learning is a set of algorithms that are fed structured data so that a task can be performed without programming.

Fresh Servant in a nutshell

78 MEUR turnover in 2021

500 employees in 2022, in nearly 40 countries

100 % Finnish work in three different locations

Similar success stories

HUS – operations management reporting provides a real-time snapshot to support daily management

Hospital District of Helsinki and Uusimaa, or HUS, Finland’s largest healthcare operator, uses a visual tool for its operations management…


Fast deployment of effective KPI reporting across country borders

Fresh Servant

Fresh Servant, a trusted supplier to retailers and professional kitchens, specializes in quality fresh food and a range of products…


Akseli, Atria’s knowledge management portal, is the result of a long collaboration between Pinja and Atria