Summary
- Profile Type
- Research & Development Request
- POD Reference
- RDRDE20260701017
- Term of Validity
- 16 July 2026 - 16 July 2027
- Company's Country
- Germany
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- All countries
General information
- Short Summary
- A regional public-law institution providing agricultural advisory services is seeking a strong lead partner for a Horizon Europe project under HORIZON-CL6-2027-03-GOVERNANCE-04. The aim is to further develop and pilot a trustworthy AI-assisted solution for providing well-founded, context-sensitive and impartial advice in agriculture and forestry. As a public-law body, the German institution can contribute real-world pilot and validation environments.
- Full Description
-
A public-law institution with a statutory mandate to support agriculture and the professionals working within the sector, intends to participate in a Horizon Europe consortium under topic HORIZON-CL6-2027-03-GOVERNANCE-04. They are offering a project idea focussing on the further development and piloting of an AI-powered assistance system designed to support agricultural advisors, farmers, and forestry enterprises by providing reliable, context-aware, and impartial assistance for technical, operational, and procedural decision-making. The objective is to deliver a practical, high-maturity solution that strengthens competitiveness, sustainability, and resilience. The solution is intended to support, not replace, human advisors and decision-makers.
The relevance of the initiative is reflected in the scale of the sector. Within the remit of this organisation, approximately 33,570 farms manage around 1.49 million hectares of agricultural land, including about 1.07 million hectares of arable land. The sector employs approximately 117,200 workers and includes specialized production systems such as 4,470 dairy farms and 6,630 pig farms. This scale requires scalable, data-driven governance and advisory solutions capable of addressing a very large number of operational queries and decision-making processes each year.
The organisation does not intend to assume the role of project coordinator. Instead, it seeks to contribute as a practice, testing, validation, and knowledge transfer partner. As a public-law institution with statutory responsibilities and direct links to advisory services and agricultural practice, they bring real-world requirements from farming operations, professional advisory services, and administrative procedures into the project.
The proposed project could build on a conceptualized AI assistance system that could be further developed into a proactive, data-driven, and conversational support platform. The system would capture farm-level data, integrate domain-specific applications and procedures, analyze documents, perform plausibility checks, and recommend appropriate actions. Multimodal inputs, geospatial data, curated expert knowledge, and human-in-the-loop approaches could be combined to create an assistance system supporting advisory services, application processes, and decision-making.
A particular emphasis for the organisation belongs to transparent, neutral, and trustworthy advice. Quality and reliability needs to be ensured through curated knowledge repositories, editorial quality assurance processes, and clearly defined escalation mechanisms. Any data obtained by the German organisation through its statutory administrative and regulatory functions may only be used for advisory purposes with the explicit consent of the respective client or data subject.
The project will strengthen sustainability, competitiveness, and resilience by improving the basis for decision-making, reducing complexity, and streamlining operational and administrative processes. The solution is designed with scalability and transferability to European agricultural systems in mind.
The German organisation can contribute real-world use cases, access to target groups, and established advisory and procedural structures. To ensure broad European relevance, partners from additional Member States and from the forestry sector are sought. The project will also include training and capacity-building activities aimed at enhancing AI literacy and competencies among relevant stakeholders.
The consortium is seeking an experienced project coordinator, as well as partners with expertise in AI development, data engineering, interoperability, forestry, social sciences, evaluation, and pilot implementation. The German large public agricultural advisory and regulatory organisation will contribute to co-creation, field testing, validation, impact assessment, dissemination, and knowledge transfer activities. - Advantages and Innovations
-
The proposed solution could combine trusted knowledge access, multimodal AI, and process-oriented assistance. It goes beyond a generic chatbot by supporting real advisory, application, and reporting processes through structured follow-up questions, document and evidence analysis, plausibility checks, and the preparation of transparent and actionable next steps.
A key innovation lies in the combination of domain-specific accuracy with comprehensive, tailored, and impartial advisory support. Quality, timeliness, and neutrality needs to be ensured through curated knowledge repositories, editorial quality assurance, transparent source attribution, and human-in-the-loop mechanisms. In this way, the solution would address key requirements for trustworthy, context-aware, and effective AI-driven support.
Another important advantage could be the integration of existing and newly available data from both public and private sources. The system should be designed to combine structured and unstructured information, geospatial data, and documents, enabling better-informed decisions, fewer errors, reduced follow-up requests, and higher-quality submissions and records. Furthermore, the solution should in the end be interoperable and transferable to other European advisory, funding, and administrative environments.
The distinctive USP of the regional agricultural advisory authority lies in its unique combination of direct access to agricultural practice, institutional trust, advisory expertise, and close involvement in the interpretation and implementation of regulatory frameworks as a public-law body. This enables the organisation not only to assess the technical performance of the solution but, more importantly, to validate its practicality, usability, and trustworthiness in real-world operational settings. - Stage of Development
- Concept stage
- Sustainable Development Goals
- Goal 17: Partnerships to achieve the Goal
- Goal 12: Responsible Consumption and Production
- Goal 9: Industry, Innovation and Infrastructure
- IPR status
- No IPR applied
Partner Sought
- Expected Role of a Partner
-
The organisation seeks partners that can complement and strengthen its capabilities in coordination, technology development, European-scale piloting, scientific evaluation, and market uptake. First and foremost, a highly experienced Horizon Europe coordinator is sought to lead consortium building, shape the strategic direction of the proposal, structure the work packages, align partner contributions, oversee project management, and develop the exploitation and scaling strategy. As the project is envisaged as an Innovation Action with a strong focus on real-world deployment and uptake, partners with a proven track record in bringing solutions to at least TRL 8, industrial-grade development, pilot implementation, and demonstrable deployment capacity are particularly encouraged to join.
In addition, the consortium needs technology partners capable of developing and piloting a trustworthy, cost-efficient, and scalable AI solution for advisory services in agriculture and forestry. Relevant expertise includes AI engineering, Retrieval-Augmented Generation (RAG), knowledge graphs, multimodal processing of text, documents, images, audio, and potentially video, as well as explainable AI, robust system architectures, and secure operations. Partners with capabilities in data engineering are also sought, particularly those able to unlock and integrate existing and new public and private data sources, develop curated and interoperable datasets, create interfaces and data spaces, and implement privacy-preserving approaches such as data minimisation, pseudonymisation, access-control frameworks, and other trustworthy data governance mechanisms.
Another key partner profile consists of organisations with forestry expertise and practical forestry application experience. As the call explicitly addresses both agriculture and forestry, partners are required that can contribute forestry-specific use cases, provide access to end users, and support validation and piloting in real forestry advisory and operational environments.
Equally important are scientific and research partners specialising in methodology, impact assessment, and evaluation. These partners should be able to measure and demonstrate the effectiveness of the solution, including user acceptance, time savings, error reduction, advisory quality improvements, and contributions to resilience and sustainability. They should also support the development of robust evidence demonstrating the added value of the proposed solution compared to existing approaches.
The consortium also specifically seeks Social Sciences and Humanities (SSH) partners with expertise in legal and ethical aspects of AI, gender dimensions, education and capacity building, train-the-trainer concepts, behavioural research, user acceptance, and skills development. These partners will play a key role in strengthening awareness, understanding, competencies, and the responsible use of AI among advisors, farmers, forest managers, and other rural stakeholders.
Furthermore, European pilot, dissemination, and AKIS-related organisations are welcome, particularly those with access to advisory networks, agricultural and forestry end users across multiple countries, and communication channels that can support broad adoption and uptake. Partners able to create synergies with relevant Horizon Europe and other EU initiatives, European agricultural data spaces, Copernicus- and Galileo-related applications, and practice-oriented testing, field trial, or demonstration environments will be especially valuable. - Type and Size of Partner
- SME 50 - 249
- University
- R&D Institution
- SME <=10
- SME 11-49
- Type of partnership
- Research and development cooperation agreement
Call details
- Framework program
- Horizon Europe
- Call title and identifier
-
HORIZON-CL6-2027-03-GOVERNANCE-04-AI supporting informed advice for farmers and foresters to improve competitiveness and sustainability
- Anticipated project budget
-
ca. 5-6 Mio. EUR
- Coordinator required
-
Yes
- Deadline for EoI
- Deadline of the call
- Project duration in weeks
-
156
- Web link to the call
- https://cordis.europa.eu/programme/id/HORIZON_HORIZON-CL6-2027-03-GOVERNANCE-04
- Horizon Europe
Dissemination
- Technology keywords
- 01003003 - Artificial Intelligence (AI)
- Market keywords
- 09005 - Agriculture, Forestry, Fishing, Animal Husbandry & Related Products
- 02007021 - Other Artificial intelligence related
- Sector Groups Involved
- Digital
- Agri-Food
- Targeted countries
- All countries