TLDR: Norwegian startup Digel is implementing a generative AI platform at Hoff SA’s potato processing facilities in Gjøvik. This pilot project aims to integrate large language models with industrial data from machinery, sensors, and technical documentation to enhance troubleshooting, process analysis, and overall operational efficiency in the potato sector.
In a pioneering move for Norway’s potato processing industry, local startup Digel has initiated a pilot program to deploy its generative AI platform within the production facilities of Hoff SA in Gjøvik. This initiative represents one of the earliest attempts to directly apply generative AI to day-to-day factory operations in the country’s vital potato sector. Hoff SA, a cooperative owned by Norwegian potato growers, stands as a significant player in the national potato processing landscape, handling a substantial portion of the country’s potato intake and producing a diverse range of finished and semi-processed products for retail, foodservice, and industrial use. This varied production environment makes Hoff an ideal testbed for Digel’s innovative AI system.
The core objective of the pilot is to assess the capacity of AI tools to bolster process stability and efficiency at Hoff’s facilities. The findings from this project are expected to provide valuable insights into how similar technologies could be scaled across the broader potato processing sector to optimize production workflows and resource utilization. Digel’s platform distinguishes itself by connecting large language models (LLMs) directly to operational data generated by industrial machinery, sensors, and technical documentation. This contrasts with conventional AI models, which are primarily trained on publicly available text, often lacking direct relevance to factory environments.
During the pilot phase at Gjøvik, engineers and operators are actively involved in structuring production information and linking it to real-time equipment and sensor data. The system allows for the comprehensive modeling of production lines, attaching relevant documentation, and integrating technical records, thereby creating a unified, AI-readable representation of plant operations. Once configured, Digel’s AI agents can access both historical and live data streams to assist with troubleshooting and in-depth process analysis. This empowers operators to pose questions in natural language, such as ‘Why is production slower now?’ or ‘Why are there so many faults in the compressor?’, and receive context-aware responses grounded in the plant’s specific data.
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For potato processors like Hoff SA, which manage large volumes of potatoes seasonally, even marginal improvements in uptime, energy consumption, or yield can translate into significant gains in cost-efficiency. Digel positions its platform as a crucial tool to help manufacturers identify and capitalize on these opportunities by leveraging their proprietary operational data. Digel, a Norwegian startup founded in 2024, comprises five employees with specialized backgrounds in cybernetics, robotics, and industrial IT, drawing expertise from institutions like NTNU and USN. The company is headquartered at RunwayFBU, Aker’s innovation hub at Fornebu, and is dedicated to making generative AI practical and accessible for industrial applications.
