Forest Data Platform · Estonia

The Forest Knows.
Now We Do Too.

REKU is a forest data platform that uses autonomous mini-harvesters to thin forests with precision — generating the world's most comprehensive proprietary 3D forest dataset.

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3D Digital Twin

Per hectare processed

AI-native

Learning from every stand

EU Aligned

Digiforest project

The Problem

A Generation of Forest Knowledge Is About to Disappear

Industrial damage at scale

20-tonne harvesters cause irreversible soil compaction, disrupt root networks, and cut wrong trees — degrading forest health for decades.

Knowledge walking out the door

Retiring forest wardens carry irreplaceable decision-making knowledge — which tree to cut, when, and why — with no systematic way to capture or transfer it.

Europe's thinning backlog grows

Conventional methods cannot scale to meet Europe's growing forest management obligations. The backlog compounds every season.

The Solution

We Asked Why Before We Built How

REKU encodes decades of expert thinning knowledge into autonomous systems. Our mini-harvesters perform precision thinning — cutting the right tree, at the right time, for the right reason.

Every hectare processed generates a 3D dataset that compounds in value with scale. The operational work and the data asset are inseparable — that's the moat.

How It Works

Three Steps. One Compounding Asset.

Deploy

Usewood platform

Autonomous mini-harvester enters the forest stand. Lightweight and mobile, it avoids the soil damage caused by conventional machinery.

See

DeepForestry drone sensors

Real-time 3D Digital Twin and forest inventory data generated per hectare. LiDAR and multispectral sensors capture every tree's position, diameter, and health.

Learn

REKU AI

Every hectare trains REKU's models. The dataset compounds with scale — more hectares means better decisions, more valuable data, and a wider competitive moat.

The Data Moat

Every Hectare Thinned Is a Dataset No One Else Owns

Operational revenue funds data collection. Data collection creates the asset. The asset generates licensing revenue. Three channels reinforce one moat.

National Forest Agencies

RMK — Estonian State Forest Management Centre

Governments face mandatory forest inventory obligations. REKU delivers verified, high-resolution data at scale — faster and more accurate than ground surveys.

Carbon Markets

Verified biomass quantification

Precise 3D biomass data from every processed hectare enables high-integrity carbon credit verification — a market demanding exactly this kind of ground-truth.

Global OEMs

AI model licensing

Forest machinery manufacturers need AI that understands forest stand dynamics at scale. REKU's dataset is the training data they cannot build themselves.

Partners & R&D

Built on Deep Partnerships

In alignment with the EU Digiforest project

DeepForestry

3D Sensing & Digital Twin

Usewood

Autonomous Harvester Platform

Estonian University
of Life Sciences

Forest Research

University of Tartu

AI Research

AIRE

Estonian AI & Robotics Centre

Team

People Who Have Done This Before

Andres Lainela

Founder

Erle Leemet

Co-Founder

Lauri Leemet

Engineering

Clevon background

Tiit Kosenkranius

Forest Operations

40+ years of forest management. 100+ Usewood machines shipped across Europe.

Richard

Machine Operator

"His knowledge of which tree to cut — and why — is the intellectual foundation of REKU."
— On Tiit Kosenkranius

Traction

Early Signal

Investor Interest

Timmu Tõke

Founder, Ready Player Me

Interest from Timmu Tõke, founder of Ready Player Me — one of Europe's most recognized deep-tech builders.

Market Validation

Largest Private Forest Owner

Estonia

Estonia's largest private forest owner has expressed interest in REKU's precision thinning services.

R&D Partnerships

Two Universities + AIRE