Deep FRST is harnessing AI for profitable and sustainable forestry – based on science
DeepFRST has developed a patent pending algorithm to digitize forest management – one of the oldest and most mission-critical industries on the planet.

Forests are complex ecosystems and forest utilization is a large global business. Due to the complexity the amount of economic and ecological variables in forestry becomes extremely large. Thus, optimization of the use of forest resources has previously relied on simplified and restricted models, leading to suboptimal decisions.

In recent years, the accuracy of forest inventory data has become increasingly more accurate. DeepFRST AI optimization algorithm is the first one in the world to be able to truly optimize high dimensional cross-disciplinary models in forest management and to take advantage of the detailed data available.

“Where the previous state-of-the-art scientific models for optimizing forest management took days or even weeks to compute, the DeepFRST algorithm can find the same solution in only a few minutes,” says Professor Olli Tahvonen from the Faculty of Agriculture and Forestry, University of Helsinki.

DeepFRST is developing a B2B software for forest valuation and optimal management. DeepFRST aims to help its customers, private and institutional forest owners, forest investors, and forest managers to increase returns on forest assets, perform carbon accounting (in trees and soil), and fight climate change and biodiversity loss. By harnessing the latest scientific breakthroughs in AI research and forest science, the DeepFRST solution significantly outperforms any existing silvicultural optimization methods.

Background of DeepFRST

The current work by the DeepFRST researchers from the University of Helsinki and Aalto University is a continuum and an outcome of decades of interdisciplinary research between resource economists ecologists and mathematicians. The founding team of five researchers, including two professors Olli Tahvonen from University of Helsinki and Pekka Malo from Aalto University, has expertise in AI, economics, mathematics, and forest sciences.

DeepFRST received Business Finland’s Research to Business funding to prepare for the commercialization of their AI algorithm and plans to launch in year 2023. As a science-based startup, DeepdFRST has the technical expertise to build a product, but – unlike others – DeepFRST also has the commercialization skills to bring the amazing tech to the market.

Problem

Forest owners need to know: “What’s the optimal management strategy for my forest?”

Solution

Our AI technology revolutionizes forest planning:

  • Follow cash flow projections and asset valuation
  • Reach your mix of timber revenues, carbon sink and biodiversity optimally
  • Calculate your forest’s carbon sink
  • Understand the costs of increasing carbon sink and/or biodiversity
  • Reduce risks (disasters, insects, prices, etc.)
  • Find your optimal solution in no time

Join us

Interested in collaboration or funding of DeepFRST? Contact us:

Website

Olli Tahvonen
Professor, University of Helsinki
olli.tahvonen@helsinki.fi

Vesa-Pekka Parkatti
Postdoctoral researcher, University of Helsinki
vesa-pekka.parkatti@helsinki.fi

Pekka Malo
Professor, Aalto University
pekka.malo@aalto.fi

Antti Suominen
Doctoral student, Aalto University
antti.suominen@aalto.fi

Philipp Back
Postdoctoral researcher, Aalto University
philipp.back@aalto.fi