REGENA revolutionizes the Farm to Fork to Finance (3F) value chain of Regenerative Agriculture with the power of Machine Learning

Our Expertise

Dedicated in Research and Development of natural capital valuation methods, as well as generalized and tailored-made financial, banking and insurance instruments that respond to the needs of the circular economy.

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Natural Capital Valuation

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Symbiotic Networks Digitization

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Ecological Finance Engineering

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Natural Capital Valuation

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Symbiotic Networks Digitization

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Ecological Finance Engineering

Join our Carbon Farmers in 8 Countries

Join our Carbon Farmers in 8 Countries

11 Regenerative and Carbon farms the EU and MENA regions
10 business partners and in the EU and MENA regions
12 different test crops under climate and pest stresses

Why Regenerative Carbon Farming?

Via Carbon Farming you can optimize and monetize the full range of your Environmental and Soil Health Assets as Carbon Credits!

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    Optimize Soil Nutrients (C,N,P) absorption

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    Optimize Microbial Consortia for Ecosystem Services

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    Reduce Petrochemical Fertilizers via Biomasses

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    Reduce Insurance Costs via Resistant Varieties

What REGENA Solves

We optimize your Carbon “Farm to Fork to Finance” (FFF) value chain with the power of Machine Learning by Qu.A.L.Ity Standards

Farmers asking

How to validate CF accurately and fast? 47%
What to measure for CF certification? 68%
How to maximize carbon credits? 59%
How can I use my carbon credits? 72%
How can I receive carbon finance? 87%

For Qu.A.L.Ity

For Qu.A.L.Ity

1

Quantification

  • 12 test crops
  • 7 databases
  • 32 variables
  • 19 EUSO SDIs
  • 5-stage LCA
  • 15 Impacts
  • 92 Eco-Services

2

Additionality

  • 37 bio-synergies
  • 7 Fertilizer types
  • 3 Agronomy types
  • Soil Health Profiles
  • Weather / Climate
  • Resistant Varieties
  • Micro-Organisms

3

Long -Term

  • Cross Validation
  • Ambient Intel
  • Nutrient Balances
  • ML Optimization
  • Digital Assets
  • Blockchain
  • Expert Advisor

4

 SustainabilIty

  • Nature-based
  • Farms’ Symbiosis
  • Derivatives
  • Smart Contracts
  • Micro Eco-finance
  • Bank GAR ↑
  • Farm / Bank ESG ↑

1

Quantification

12 test crops

7 databases

32 variables

19 EUSO SDIs

5-stage LCA

15 Impacts

92 Eco-Services

2

Additionality

37 bio-synergies

7 Fertilizer types

3 Agronomy types

Soil Health Profiles

Weather / Climate

Resistant Varieties

Micro-Organisms

3

Long -Term

Cross Validation

Ambient Intel

Nutrient Balances

ML Optimization

Digital Assets

Blockchain

Expert Advisor

4

 SustainabilIty

Nature-based

Farms’ Symbiosis

Derivatives

Smart Contracts

Micro Eco-finance

Bank GAR ↑

Farm / Bank ESG ↑

How REGENA Works

We optimize your Carbon “Farm to Fork to Finance” (FFF) value chain with the power of Machine Learning by Qu.A.L.Ity Standards

Carbon Farming SDGs

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Step 1

We Validate you as Carbon Farmer
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Step 2

We value your Carbon Farming assets
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Step 3

We build your “Green Finance” contract

REGENA Farms’ Performance

35% Lower lifecycle impacts

Lower lifecycle impacts 35%

47% higher annual income

higher annual income 47%

32% better Credit Rating

better Credit Rating 32%

Carbon Farming Markets Intelligence

Carbon Farming Markets Intelligence

Regena Modules

REGENA Validation

Goal: Compare accurately your Baseline to your Regenerative Carbon Farming scenarios and optimize your crop composition for maximum results

 

REGENA Machine Learning Inputs

  • Agronomical Practices: Cover crops, tillage or no-tillage
  • Biomasses: Substitution of petro-chemical fertilizers
  • Micro-organisms: Metabolic response to biomasses
  • Resistant Varieties: Against extreme weather and pests
  • Weather and Climate: Temperature, precipitation, wind
  • Energy and Water: Fuels, Water use and CO2 emissions
  • Modelling: Standard field of 1000m2 at each country

REGENA Lifecycle Analytics

Goal: Quantify and monetize your lifecycle environmental benefits from reduced impacts and capitalize your Carbon Farming assets for future investments

 

REGENA Machine Learning Inputs

  • Pilots: 11 farms in the EU / MENA region on 5 Stages
  • Tested Crops: 12 crops with real data for 5 Stages
  • Method: Product Environmental Footprint (PEF)
  • Impacts: Resource Depletion; Ecosystem Degradation
  • Stages: 5 Stages; Scopes 1, 2 and 3
  • Inventories: Sima-Pro; EcoInvent; One-Click LCA
  • Normalization: CO2 eq. by the IPCC AR 6
  • Scenarios: Global and national trade of potatoes

REGENA Ecological Finance Engineering

Goal: Risk-adjusted discounted lifecycle value of atmospheric CO2 removal and Carbon Credits from Soil Organic Carbon (SOC) growth

 

REGENA Machine Learning Inputs

  • Pilots: 11 farms in the EU / MENA region
  • Methods: Microbial, rotation and cover crops on C, N, P
  • Benchmark Metric: EUSO SDI Soil Organic Carbon
  • Modelling: Improvement of initial SOC values
  • Standard: CICES v5.1; Carbon sequestration
  • Monetary Value: EU Emissions Trading Scheme (ETS)
  • Contract: SOC increase risk-adjusted NPV

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