FDI - Farmers Data intelligence

Support farmers in recording and understanding their data. Providing action plans and sustainability support as well as highlighting areas for improvement of efficiency, profitability and resiliance.

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Inspiration

The need to use AI tools to solve and boost some precious existent ecosystem that just need to be modernised - agriculture jumped into our minds as it has underpinned human development, it sustains us and provides primary resources. Now that humans have finally created new resource (AI) its our duty to reward nature that first established us.

What it does

It provides a link between the ancient agricultural systems and the complex new modern technology and AI solutions, which can boost the whole ecosystem, facilitating supply chains, having societal benefits and reducing enviromental impacts. The farmers will be able to access information on their farm efficiency, compare against benchmarked data and present opportunities to improve their system or access markets, farm payment schemes and products more relevant to them, which would otherwise require specialist knowledge. This system reduces manual input from the farmers, increasing engagement which is a core bottleneck in all farm management technology. This solution offers an opportunity for wider adoption, providing national scale insights and contributing to national sustainability goals. We have also outlined a hardware solution for providing realtime insights into soil health metrics, which will drive inputs and better inform farmers on their applications.

How we built it

Codex was used for developing the web app with Eleven labs for vocal chat bots, and open AI for the text chat bot.
By processing data from publicly available datasets (ESA, Copernicus, DEFRA, EU Comission, etc), supply chains and the farmer themselves, we can reduce the input burden for farmers, and providing clear opportunities for farm advancement.
To design the in field soil monitor mock up we used CAD and OpenAI to develop and analyse the internal structure of such devices.

Challenges we ran into

Understanding how to use AI to produce resources that are simple and human friendly - to improve life and jobs. Creating a very user friendy app and reports is our main goal to show them the real impact and justify costs and revenues.
The agricultural sector needs to be modernised, but farmers are generally highly protective of their data, and they lack both the time and skills to enter data into the complex software available to them. Techology has advanced, but the farmers have been left behind. Using AI solutions such as these vocal chat bots or a user friendly app, we support smoother data entry from farmers who are reluctant manually enter data. Manual data collection and input is essential for all current farm management solutions.

Hardware-financed subscription model: we front the full hardware cost (~€700/field) and install it for free, with no upfront deposit from the farmer - avoiding the expense barrier that normally prevents technology uptake on farm. For the first 24-36 months, the farmer pays an elevated annual subscription (e.g. €399.99/year for a single field) that bundles hardware amortization into the service fee. Once the hardware cost is recovered (around month 18-24 based on the elevated rate), the subscription automatically drops to a lower software-only tier (e.g. €249.99/year), reflecting that ongoing costs are now just maintenance (batteries last 5+ years). This creates a clear, farmer-friendly story: "we invest in your field first, you only pay more while we're recovering that investment, then your price drops for good." With this software advisory services will be able to support more farmers and reduce analysis and data input aspects of their workflows.

Accomplishments that we're proud of

We were not a team before today - each of us has a separate background (legal, design, research, security, marketing) - but we have progressed massively and produced an MVP and created a group around an idea to solve a global problem that is currently not being adressed.
We have been able to create tasks and approaches to solving the problem that suits each of our skill sets in a very short timeframe.
So we apply for
~Open AI credits for development of the web app and text chat bot (to access and gain insights from their data)
~ Elevenlabs for the use of the vocal chatbot (to reduce the farmer data input burden).
~ Cash prize to develop the hardware devices, expand research, and involve team members to engage farmers to build trust. (plus prosecco)

What we learned

How to bring everyone up to date with a problem that is not generally in their field, and how each of our backgrounds can offer approaches to solutions differently.
We have learned to focus the ideas towards key stakeholders, and to make sure that we were not spreading the idea too thinly across too many ideas.
We better understand how the different AI tools can provide different servces, and we can use them more efficiently to achieve the specific goals.
We have better defined the product goals and USP, identifying the core potential for our solution. Last but not least, we learned to manage time and have fun in a new process and a new idea.

What's next for FDI - Farmers Data intelligence

Get funding for further development of the software and potential supporting hardware for data collection. Get a partner for hardware development.
Expanding the team into specialists to support farmer interpretation of data and for developing the software.
Research more data sources, and expanding the advisory potential.
Explaining the benefit to the farm and the cost for onboarding farmers and supply chains.

Built With

  • cad
  • claude
  • codex
  • copernicus
  • elevenlabs
  • exein
  • farmcarboncalculator
  • gemini
  • higgsfield
  • openai
  • sentinal
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