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Strategic Analysis
To build a winning proposal for @HORIZON-CL4-2027-04-DIGITAL-EMERGING-05, the consortium must bridge high-level AI capabilities with practical industrial integration across varied manufacturing scale levels (SMEs to Tier-1s). The proposal should centre on a modular, open-source-aligned Integration Kit supported by robust digital twin testbeds and clear certification guidelines that directly reduce the total cost of ownership and technical risk for adoption.
TRL 4 → 7
A deployable, modular integration framework, validated through at least three real-world industrial pilots covering different reference scenarios to demonstrate that the approach can be adapted to varied industrial needs and company sizes, including both SMEs and larger manufacturers. This framework should provide, for example, a common software layer, standard interfaces to connect to existing workflow and legacy system, possibly also to connect various robot components, coordinate multiple robots and link them with additional AI tools and IoT environments, as well as tested configuration templates and clear guidelines to ensure safe and efficient use.
An Integration Kit, building on this framework, which offers ready-to-use modules, example configurations and practical tools that help system integrators and companies to set up, test and run AI-enabled robotics solutions more quickly and with reduced technical effort.
Where relevant, high-fidelity digital twin testbeds should be linked to each pilot, allowing safe and realistic testing and training before deployment, and supporting a smooth transition from virtual models to actual production lines.
Reusable, datasets (compliant with relevant regulation and IP protection) and practical benchmark tasks, made available to the wider robotics and AI community, to support further development and comparison of new solutions while respecting European data protection rules.
A clear Step-by-Step Adoption Guide aimed at SMEs and other end-users, providing easy-to-follow instructions, practical checklists and examples to help companies plan, budget and implement AI-driven robotics in a safe and cost-effective way, even if they have limited in-house expertise, and including guidance to navigate regulatory compliance and certification.
Concrete contributions to relevant open standards and clear guidance on certification pathways, to help ensure compliance with European regulations and build trust in the safe use of AI in robotics. Projects are expected to make full use of existing robotics resources and assets made available through the AI-on-Demand Platform, such as the EuroCORE repository and other relevant shared tools, to maximise synergies, avoid duplication of efforts and ensure broad dissemination and reuse of results within the European AI and robotics community.
Wider and faster deployment of robotics, bridging the gap between technology providers and end-users.
Development and implementation of modular and interoperable integration frameworks and solutions, including standardized protocols for data, training and safety testing, evaluation and validation of robotic solutions in key use cases
Improved competitiveness of European industries, notably SMEs via the development of advanced robotics systems, intelligent planning and control systems, user feedback rendering techniques and cutting-edge AI innovations
No expected impacts identified for this destination.
Apply AI Strategy
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described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes.
Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.
described in Annex B of the Work Programme General Annexes.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide.
In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, it is important to avoid a situation of technological dependency on a non-EU source, in a global context that requires the EU to take action to build on its strengths, and to carefully assess and address any strategic weaknesses, vulnerabilities and high-risk dependencies which put at risk the attainment of its ambitions. For this reason, participation is limited to legal entities established in Member States, Iceland and Norway and the following additional associated countries: Canada, Israel, Republic of Korea, New Zealand, Switzerland, and the United Kingdom. In addition, entities established in third countries which may become associated to Horizon Europe during 2026 and 2027 may be eligible to participate in this topic if the third country is identified for this topic as an eligible country in the List of Participating Countries in Horizon Europe at the time of submission of the application[[See the List of Participating Countries in Horizon Europe available at https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/common/guidance/list-3rd-country-participation_horizon-euratom_en.pdf.]]. In any case, the association agreement to the Programme must apply by the time of the signature of the grant agreement.
For the duly justified and exceptional reasons listed in the paragraph above, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, may not participate in the action unless it can be demonstrated, by means of guarantees positively assessed by their eligible country of establishment, that their participation to the action would not negatively impact the Union’s strategic assets, interests, autonomy, or security. Entities assessed as high-risk suppliers of mobile network communication equipment within the meaning of ‘restrictions for the protection of European communication networks’ (or entities fully or partially owned or controlled by a high-risk supplier) cannot submit guarantees.[[ The guarantees shall in particular substantiate that, for the purpose of the action, measures are in place to ensure that: a) control over the applicant legal entity is not exercised in a manner that retrains or restricts its ability to carry out the action and to deliver results, that imposes restrictions concerning its infrastructure, facilities, assets, resources, intellectual property or know-how needed for the purpose of the action, or that undermines its capabilities and standards necessary to carry out the action; b) access by a non-eligible country or by a non-eligible country entity to sensitive information relating to the action is prevented; and the employees or other persons involved in the action have a national security clearance issued by an eligible country, where appropriate; c) ownership of the intellectual property arising from, and the results of, the action remain within the recipient during and after completion of the action, are not subject to control or restrictions by non-eligible countries or non-eligible country entity, and are not exported outside the eligible countries, nor is access to them from outside the eligible countries granted, without the approval of the eligible country in which the legal entity is established.]]
Described in Annex B of the Work Programme General Annexes.
described in Annex C of the Work Programme General Annexes.
are described in Annex D of the Work Programme General Annexes.
are described in Annex F of the Work Programme General Annexes and the Online Manual.
described in Annex F of the Work Programme General Annexes.
described in Annex G of the Work Programme General Annexes.
described in the [specific topic of the Work Programme]
Application form templates — the application form specific to this call is available in the Submission System
Standard application form (HE RIA, IA)
Evaluation form templates — will be used with the necessary adaptations
Standard evaluation form (HE RIA, IA)
Guidance
Model Grant Agreements (MGA)
Call-specific instructions
Ownership Control Declaration Annex
HE Main Work Programme 2026-2027 – 1. General Introduction
HE Main Work Programme 2026-2027 – 7. Digital, Industry and Space
HE Main Work Programme 2026-2027 – 15. General Annexes
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764
EU Financial Regulation 2024/2509
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Funding & Tenders Portal Terms and Conditions
Funding & Tenders Portal Privacy Statement
Guidance on participation in EU calls with ownership and control restrictions
Evaluators will strictly assess whether the project delivers concrete, deployable software assets rather than theoretical AI models. They will prioritize:
Everything the call asks for, seen from the call's point of view. Each line shows what answers it, and which partner carries it.
This matrix lists everything the call asks for: outcomes, impacts, scope, the requirements buried in the call text, and policy alignment. Sign up free and GrantForge tracks each line against the concept you build.
| Requirement | Covered by | Carried | Status |
|---|---|---|---|
| Scope activities | |||
| SC1A deployable, modular integration framework, validated through at least three real-world industrial pilots covering different reference scenarios to demonstrate that the approach can be adapted to varied industrial needs and company sizes, including both SMEs and larger manufacturers. This framework should provide, for example, a common software layer, standard interfaces to connect to existing workflow and legacy system, possibly also to connect various robot components, coordinate multiple robots and link them with additional AI tools and IoT environments, as well as tested configuration templates and clear guidelines to ensure safe and efficient use. | · | · | Sign up to track |
| SC2An Integration Kit, building on this framework, which offers ready-to-use modules, example configurations and practical tools that help system integrators and companies to set up, test and run AI-enabled robotics solutions more quickly and with reduced technical effort. | · | · | Sign up to track |
| SC3Where relevant, high-fidelity digital twin testbeds should be linked to each pilot, allowing safe and realistic testing and training before deployment, and supporting a smooth transition from virtual models to actual production lines. | · | · | Sign up to track |
| SC4Reusable, datasets (compliant with relevant regulation and IP protection) and practical benchmark tasks, made available to the wider robotics and AI community, to support further development and comparison of new solutions while respecting European data protection rules. | · | · | Sign up to track |
| SC5A clear Step-by-Step Adoption Guide aimed at SMEs and other end-users, providing easy-to-follow instructions, practical checklists and examples to help companies plan, budget and implement AI-driven robotics in a safe and cost-effective way, even if they have limited in-house expertise, and including guidance to navigate regulatory compliance and certification. | · | · | Sign up to track |
| SC6Concrete contributions to relevant open standards and clear guidance on certification pathways, to help ensure compliance with European regulations and build trust in the safe use of AI in robotics. Projects are expected to make full use of existing robotics resources and assets made available through the AI-on-Demand Platform, such as the EuroCORE repository and other relevant shared tools, to maximise synergies, avoid duplication of efforts and ensure broad dissemination and reuse of results within the European AI and robotics community. | · | · | Sign up to track |
| Expected outcomes | |||
| EO1Wider and faster deployment of robotics, bridging the gap between technology providers and end-users. | · | · | Sign up to track |
| EO2Development and implementation of modular and interoperable integration frameworks and solutions, including standardized protocols for data, training and safety testing, evaluation and validation of robotic solutions in key use cases | · | · | Sign up to track |
| EO3Improved competitiveness of European industries, notably SMEs via the development of advanced robotics systems, intelligent planning and control systems, user feedback rendering techniques and cutting-edge AI innovations | · | · | Sign up to track |
| Other requirements | |||
| REQ1Energy-efficient AI and carbon-aware strategies (Green AI)Integration frameworks must promote the use of energy-efficient AI models and hardware ('Green AI'), alongside carbon-aware deployment and operational strategies for robotic systems. | · | · | Sign up to track |
| REQ2Synergies with AI-on-Demand Platform and EuroCORE repositoryProjects are expected to make full use of existing robotics resources and assets made available through the AI-on-Demand Platform, such as the EuroCORE repository, to maximize synergies and reuse results. | · | · | Sign up to track |
| REQ3Cohesion activities with the ADRA PartnershipAs this topic implements the co-programmed European Partnership on AI, Data and Robotics (ADRA), all proposals are expected to allocate tasks for cohesion activities with ADRA. | · | · | Sign up to track |
| REQ4Contribution to open standards and certification pathwaysProjects should contribute to open and widely recognized standards and provide clear guidance on certification pathways to ensure compliance with European regulations. | · | · | Sign up to track |
| REQ5FAIR reusable datasets and benchmark tasksProjects must make reusable datasets and practical benchmark tasks available to the wider robotics and AI community, ensuring compliance with European data protection rules and IP protection. | · | · | Sign up to track |
| Expected impacts | |||
| No expected impacts in this call. | |||
| Underlying policies | |||
| POL1apply ai strategyThe Apply AI Strategy is central to this call, focusing on the deployment of AI in healthcare to improve screening, diagnosis, and patient outcomes. It emphasizes the creation of a European network of AI-powered screening centres. | · | · | Sign up to track |
The binding rules of this call. Items marked auto are verified by GrantForge from the call and the template. The others are yours to confirm.
LMIC entities auto-eligible
Low/middle-income country entities are automatically eligible for funding.
EU space data infrastructures
If the project uses satellite-based Earth observation, positioning, navigation or timing data/services, beneficiaries must use Copernicus and/or Galileo/EGNOS. Other sources may be added but not substitute EU infrastructures.
Civil applications only
Horizon Europe funds exclusively civil applications. Research with exclusive military or dual-use application is excluded.
Gender Equality Plan
Having a Gender Equality Plan (GEP) is an eligibility criterion for public bodies, research organisations, and higher education institutions from Member States and Associated Countries.
Open Science
Mandatory open access to peer-reviewed scientific publications and responsible management of research data (FAIR principles, DMP required).
4 key insights you must internalise before writing. Each is grounded in the call text and tells you what evaluators will actually look for. Share these with your consortium before drafting.
Participation is strictly limited to Member States and specific associated countries like Canada, Israel, and the UK. Any consortium member controlled by a non-eligible country must provide security guarantees, and entities flagged as high-risk mobile network suppliers are outright banned. You must vet your partners' ownership structures before forming the consortium to avoid disqualification at the eligibility check.
Source: Eligibility rules
The proposal must validate its integration framework across at least three real-world industrial pilots. Crucially, these pilots cannot be uniform; they must cover different reference scenarios and span varied company sizes, explicitly including both SMEs and larger manufacturers. Failure to structure the consortium with this diverse end-user mix will severely impact the implementation score.
Source: Scope / Expected Outcomes
Evaluators are explicitly instructed to assess whether the project delivers concrete, deployable software assets. Proposals focusing on theoretical AI model development rather than practical, modular integration kits and step-by-step adoption guides for SMEs will fail the pre-award evaluation.
Source: Evaluation criteria (pre-award)
Projects must not build their integration frameworks in isolation. Evaluators will look for strong, concrete alignment with the AI-on-Demand platform and the EuroCORE repository. You must explicitly budget and plan for reusing these existing robotics resources to demonstrate resource reuse and avoid duplication of effort.
Source: Evaluation criteria (pre-award)
Talk to the Grant Coach to build your concept. There is no set order: start wherever your project starts. The sections below mirror what the conversation produces, and your coverage tracks the progress. You can refine everything once your project workspace is created.
The problems this call frames, and who they affect. Your concept and plan address them.
Industrial end-users face high financial and technical hurdles when attempting to integrate modern AI algorithms into legacy manufacturing workflows and multi-vendor robot fleets.
Uncertainty surrounding compliance with European AI safety regulations and lack of standardized testing pathways deter rapid industrial deployment of autonomous systems.
Small and medium-sized enterprises seeking cost-effective, easily deployable AI-driven robotics to modernize production lines without deep in-house expertise.
System integrators that configure, install, and service AI-enabled robotics solutions for industrial clients using standardized integration kits.
Academic institutions and researchers in robotics and AI benefiting from open benchmark datasets, EuroCORE tools, and published integration standards.
The long-term impacts your project should drive, and the policies they serve.
Enhanced productivity and flexibility in manufacturing through accelerated deployment of AI-driven robotics, specifically empowering SMEs to adopt advanced automation.
Establishment of open benchmarks, compliant datasets, and contributions to EU standards via the AI-on-Demand Platform and EuroCORE repository.