Our company operates in the fintech and blockchain industry, specifically in the Tokenization of Real World Assets in the Regenerative Finance and Real Finance niches.

As a platform service, we Tokenize Assets for Regenerative Projects to tap into greater liquidity markets and open financial access to many more, and we want to leverage the latest A.I. technology to gain market advantage. Applications of this technology include a Regenerative Impact A.I. Calculator and Estimator Tool that uses recommended and invented algorithms, predictive analytics like lifetime values, fraud detections, and classifications.

The required outcome of the Estimator Tool is to allow the user to make an informed decision based on Dollar Value Profitability and Cost savings on wether creating a Regenerative Impact Project (i.e. Regenerative Agriculture, Reforestation, Biodiversity enhancement) and or switching a current status quo or resource extraction method or project toward becoming Regenerative.

The student needs to become well and extensively researched on what constitutes a Regenerative Impact Project, what is required to qualify, what actions need to be taken, what considerations are in place etc.

The user will enter required data into specified fields about their property, assets and project,

SOME INPUT FIELDS:

Current Property Value

Size of property

Continent and country

Property location (google earth KML file of property borders)

Ecosystem (grassland, forest, jungle, coastal, desert, other (allow for manual input))

Business (Agriculture, Grazing, Orchards, Reforestation, Other (allow for manual input))

Annual Profit

Annual Costs

Cost of Fertilizer

Cost of Pesticides / chemicals

Insurance Premium

Then

The Estimator Tool needs to factor in a few current and future values like:

Property Value (based location, industry, sales)

Geosatellite imagery

Digital measurement, reporting and verification tech data (DMRV)

Business Operational and Revenue value

Current Profit margins

Cost that could be reduced or removed if switched to Regenerative methods

Natural Capital Value

Payments for Ecosystem Services value

Ecological and Climate Data in that specific region

Risk Premium, i.e. Harvest, livestock or Crop insurance

Value of possible Carbon Sequestration credits

Value of possible Biodiversity credits

Value of water or storm runoff credits

Value of Mitigation Banking credits

Value of United Nations SDGs

Value of ESG

Short, Medium and Long Term net positive value to surrounding ecosystem (how does this benefit the surrounding area, people, climate, food production, quality of life, clean soil, water, clean air etc.)

The increased dollar value and quality of products that have been grown using regeneravitve methods

regenerative methods require little or no fertilizer, little or no pesticides / chemicals

regenerative methods require more intensive farming techniques that add costs

( for example, regenerative grazing requires mobile electric fences

regeneraive agriculture requires better soil management,rotational crops, cover crop planting etc. )

equals ===

Regenerative Impact Assessment Score

1. Cost of switching to regenerative, not switching to regenerative
2. possible Profit with regenerative impact methods
3. ESG score, UN SDGs met
4. Short, medium, long term value to local ecosystem and population
5. Impact Value

We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to create our A.I. dataset. Students will develop an AI / ML model related to any of the aforementioned applications.

This will involve several different steps for the students, including:

• Conducting background research on our existing products and the dataset.
• Analyzing our current dataset requirements and implementing.
• Researching the latest AI / ML techniques and how they could be applied to our data.
• Developing an AI / ML model that provides unique outcomes or insights into our data.
• Providing multiple solutions that can be applied to solve the same problem.

By the end of the project, students should demonstrate:

• Understanding of the available dataset
• Understanding of the latest AI / ML techniques
• Identification of ways in which AI / ML can be applied to our company

Bonus steps would include:

• Providing multiple versions of potential models

Final deliverables should include

• A final report on the dataset, the problem solved, methodologies and approaches, outcomes and results, and recommended next steps.
• Source materials such as code and workbooks.

Students will connect directly with us for mentorship throughout the project. We will be able to provide answers to questions such as:

• Our current products and applications of AI / ML
• The current data set and guidance in navigating it
• Current industry standard approaches to AI / ML
• Input on choices, problems or anything else the students might encounter.