CollectiveCrunch Raises €1.4 Million in Funding  

by Kay Aloha Villamor in March 16th, 2023

CollectiveCrunch, an Espoo, Finland-based creator of the AI-powered Linda platform that enables sustainable forestry at scale, raised €1.4 million in funding led by Nidoco AB.

The funds will be used to continue global expansion and portfolio development, with a focus on the forest carbon market.

“We’re thrilled that our investors trust our team and technology amid these challenging economic times,” said CollectiveCrunch Co-Founder Rolf Schmitz. “With a business strategy designed for efficient growth—and an expanded solution portfolio that features core products adapted to serve a variety of needs—we're uniquely positioned to support the digital transformation of the forestry industry.”

CollectiveCrunch develops products that reduce timelines in forest inventories and offer accurate insights into biodiversity and carbon stocks. Since its establishment in 2016, the organization has carved up a presence in Europe, the United States, and Latin America. 

Recently, CollectiveCrunch was approved by Verra, a nonprofit company that runs standards in social and environmental markets, including the Verified Carbon Standard (VCS) Program, the world’s most popular carbon accounting program. 

Company: CollectiveCrunch Oy

Raised: €1.4M

Round: Unknown 

Funding Month: March 2023

Lead Investors: Nidoco AB

Additional Investors:

Company Website:

Software Category: Forestry Software

About the Company: Founded in 2016 by Rolf Schmitz, Jarkko Lipponen, and Christof Danzl, CollectiveCrunch is a green tech startup that is committed to building a sustainable future for forestry. CollectiveCrunch originated from the idea that they could make a difference by combining climate and geo data with state-of-the-art analytics to develop new insights. CollectiveCrunch develops products that significantly reduce timelines in forest inventories and enable transparent and accurate insights into biodiversity and carbon stocks. The company collects climatic, geo, and process data and turns it into AI models to improve the forecasting of forest inventories and tracking of carbon storage in forests for carbon trading markets.


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