One of Europe's largest forest owners adopts AI technology to manage forest lands
July 15, 2020 – Tornator, one of the Europe’s largest private forest owners and sustainability leaders, starts commercial adaptation of Linda Forest service from CollectiveCrunch in Finland and Estonia.
Tornator piloted and tested CollectiveCrunch’s Linda Forest solution in the past months. The piloting and testing successfully concluded in June 2020 for Tornator’s Finnish and Estonian forest lands.
Linda Forest makes use of satellite, LIDAR and process data and utilizes state-of-the-art AI to predict forest inventories. Using Linda Forest, Tornator can reduce its need for field visits, has access to current forestry inventory data at the click of a button, and can plan its harvesting operations more efficiently.
Tornator is a leader in sustainable and responsible use of forest lands. Linda Forest contributes to Tornator’s leadership in the industry. Kimmo Kortelainen, Planning Manager at Tornator Oyj says: “Digitalisation is key to our commercial and sustainability ambitions. Adopting Linda Forest is an exciting step forward for us and after finalizing the validation we will make the decision of commercial implementation with our business processes.”
Janne Järnstedt, Technical Product Manager at CollectiveCrunch, has been working closely with Tornator on this implementation: “Tornator is a leader in the industry and an important confirmation of our approach. We are looking forward to building a solid relationship.”
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CollectiveCrunch is an AI leader in the forestry industry. We collect climate, geo and process data and crunch this information into AI models for better prediction of forest inventories and forest management parameters.
Our product is called Linda Forest and is delivered via a SaaS platform. Using Linda Forest our customers make better buying and selling decisions, use wood-based raw material more efficiently, and overall reduce their costs. Currently focussed on Nordic and Baltic countries we will adopt the solution to Northern America, Russia and other forestry markets. Moreover, the solution can be adopted to new opportunities such as prediction of forest fire risk.