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Strategic Analysis
A winning proposal under this RAISE pilot must position the consortium at the vanguard of AI-driven autonomous experimentation, uniting trustworthy agentic AI with modular robotics to deliver end-to-end closed-loop discovery specifically focused on novel food systems, precision fermentation, or alternative proteins. Success hinges on demonstrating a fully functional, cross-laboratory pilot demonstrator that proves substantial acceleration of discovery timelines, reproducibility gains, and concrete interoperability protocols that can generalize to other scientific domains.
TRL 2 → 6
Based on programme defaults
Autonomous/semi-autonomous and adaptive AI systems (including agentic AI) that connect with laboratory instruments and robotics and can autonomously plan, act, learn and adapt within a scientific environment, within a validated safe pipeline;
Assistive and interactive safe AI-managed robotic systems that automate diverse experiments and can be applied to a diverse hardware setup;
Scalable automation solutions and networked AI systems that enable collaborative experimentation across multiple labs and networks of labs (including different geographic locations), supporting the simultaneous execution of large volumes of experiments;
Systems that provide real-time data processing and analytics, enabling immediate feedback and dynamic adjustments during experiments;
Standards and protocols to ensure interoperability between different laboratory instruments, robotics, and AI systems;
Intuitive user interfaces for enhanced human-machine interaction;
AI-driven predictive maintenance systems to optimize equipment uptime and resource utilization;
Exploration of how scientific automation technologies can be adapted for use in various scientific disciplines beyond those in the scope of this call.
Development of closed-loop scientific experimentation systems that integrate automation with AI-driven, trustworthy decision-making processes in existing laboratory environments;
Accelerated scientific discovery with increased efficiency and reproducibility;
Improved scientific productivity;
Advancement of laboratory automation, including development of best practices, challenges, and opportunities for accelerating R&D;
Prototype functional demonstrators that showcase the integration of automation with AI-driven decision-making, enabling the development of closed-loop scientific experimentation systems.
No expected impacts identified for this destination.
No EU policy alignment identified for this call.
Specific requirements
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).
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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.
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
Information on financial support to third parties (HE)
Information on clinical studies (HE)
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 – 14. Horizontal Activities
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
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Evaluators will rigorously focus on:
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 | |||
| SC1Autonomous/semi-autonomous and adaptive AI systems (including agentic AI) that connect with laboratory instruments and robotics and can autonomously plan, act, learn and adapt within a scientific environment, within a validated safe pipeline; | · | · | Sign up to track |
| SC2Assistive and interactive safe AI-managed robotic systems that automate diverse experiments and can be applied to a diverse hardware setup; | · | · | Sign up to track |
| SC3Scalable automation solutions and networked AI systems that enable collaborative experimentation across multiple labs and networks of labs (including different geographic locations), supporting the simultaneous execution of large volumes of experiments; | · | · | Sign up to track |
| SC4Systems that provide real-time data processing and analytics, enabling immediate feedback and dynamic adjustments during experiments; | · | · | Sign up to track |
| SC5Standards and protocols to ensure interoperability between different laboratory instruments, robotics, and AI systems; | · | · | Sign up to track |
| SC6Intuitive user interfaces for enhanced human-machine interaction; | · | · | Sign up to track |
| SC7AI-driven predictive maintenance systems to optimize equipment uptime and resource utilization; | · | · | Sign up to track |
| SC8Exploration of how scientific automation technologies can be adapted for use in various scientific disciplines beyond those in the scope of this call. | · | · | Sign up to track |
| Expected outcomes | |||
| EO1Development of closed-loop scientific experimentation systems that integrate automation with AI-driven, trustworthy decision-making processes in existing laboratory environments; | · | · | Sign up to track |
| EO2Accelerated scientific discovery with increased efficiency and reproducibility; | · | · | Sign up to track |
| EO3Improved scientific productivity; | · | · | Sign up to track |
| EO4Advancement of laboratory automation, including development of best practices, challenges, and opportunities for accelerating R&D; | · | · | Sign up to track |
| EO5Prototype functional demonstrators that showcase the integration of automation with AI-driven decision-making, enabling the development of closed-loop scientific experimentation systems. | · | · | Sign up to track |
| Other requirements | |||
| REQ1Comprehensive data management, sharing, and privacy systemsProposals will incorporate comprehensive data management systems capable of handling collection, storage, processing, and sharing of experimental data, ensuring data security and privacy. | · | · | Sign up to track |
| REQ2Security and robustness by designSystems should incorporate an appropriate level of security and robustness by design. | · | · | Sign up to track |
| REQ3Human oversight for safety and ethical complianceProposals should demonstrate retrofitting of existing labs with AI-driven systems incorporating human oversight and interaction to ensure accuracy, safety, and ethical compliance. | · | · | Sign up to track |
| REQ4AI-driven resource optimisation and environmental footprint minimisationSystems could incorporate AI-driven resource optimisation modules that actively minimise energy, reagent, and material consumption during automated experimentation cycles. | · | · | Sign up to track |
| REQ5International collaboration encouragedInternational collaboration is encouraged under this call. | · | · | Sign up to track |
| Expected impacts | |||
| No expected impacts in this call. | |||
| Underlying policies | |||
| No underlying policies in this call. | |||
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.
Proposals must design the intelligence layer to integrate with existing laboratory outfitting. A project architecture that relies on a complete redesign of the physical lab space will violate the core scope requirements. Consortia must focus on retrofitting current instruments with AI-driven software systems.
Source: Scope
Evaluators will rigorously check for orchestrated multi-lab distributed workflows using federated cloud or edge infrastructure. A single-site demonstrator will not score well; consortia must deploy across different geographic locations using explicit open communication standards like SiLA 2 or AnIML.
Source: evaluation_pre_award
The evaluation explicitly penalizes standard lab automation scripts in favor of true closed-loop autonomy. The proposal must prove that its agentic AI can autonomously formulate hypotheses, execute physical runs, and analyze real-time sensor streams without constant manual reprogramming.
Source: evaluation_pre_award
While the tangible demonstrator must operate in demanding food-related use cases like precision fermentation, evaluators require verifiable transferability to other scientific domains. The proposal must include concrete interoperability protocols and a clear roadmap proving the architecture can generalize beyond food systems.
Source: evaluation_pre_award
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