HORIZON-JU-CHIPS-2025-IA-two-stage-FT2: AI-assisted…

On this page · 4 sections→

01Who wins calls like this
02Call scope
03Eligibility & conditions
04Official source

Who wins calls like this

Based on projects the EU funded on the same subject in this programme.

Who leads the winning projects

Other50%
Universities25%
SMEs13%
Research centres13%

€8.4Mtypical EU grant per project

Most common lead countriesGreece, Romania, Netherlands, Sweden, Austria

Projects funded on similar topics

HEARTSHelvetic AI Resources, Technologies and Services (Swiss AI Factory Antenna)
HORIZON-JU-EUROHPC-2025-AIFA-01 · 2026 · Official record ↗
€5.0M
PharosPharos: The Greek AI Factory for accelerating AI innovation
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗
€15.0M
RO AI FactoryRomanian EuroHPC AI Factory at ICI Bucharest
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2026 · Official record ↗
€4.0M
AIFA-ICEAI Factory Antenna of Iceland to LUMI AI Factory
HORIZON-JU-EUROHPC-2025-AIFA-01 · 2026 · Official record ↗
€5.0M
AI-ATApplication for an AI Factory in Austria
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗
€15.0M
AI2FAI Factory France
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗
€15.0M
MIMERThe Swedish AI Innovation Factory
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗
€9.8M
NLAIFNetherlands AI Factory, building on Netherlands EuroHPC AI Facility
HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2026 · Official record ↗
€7.1M

Organisations that keep winning here

Each one links to its EU funding record and the partners it works with: a starting list for building a consortium.

What this call funds

Expected Outcome:The project is expected to contribute to the following outcomes:

Advanced AI-assisted methods and tools, including generative AI, for the automation of software engineering tasks, from enhancing human efficiency and optimizing resource utilization to enabling complex data/problems analysis/interpretation and supporting intelligent decision-making. Such engineering tasks often involve multiple domains (e.g., modelling, control, data management, communication, mechatronics, etc.) and stakeholders, with the burden of daunting legacy integration, refactoring (e.g., to re-design and replace obsolete technology), and the compliance with specific standards, regulations and certifications.
Open and extensible AI-assisted integrated platform, based on methodologies including AI-support, AI-based tools and toolchains, following a well-defined engineering process, including the integration with legacy tools. The platform shall provide flexible usage in small and large multi-domain and multi-stakeholder engineering teams, impacting existing and upcoming ECS engineering automation tools and their usage.
Showcasing and evaluation for software-defined vehicles of efficiency enhancements in terms of cost and time for complex data/knowledge management, resource optimization, energy consumption, interoperability, product/process quality/trustworthiness, learning curve and usability, over the whole lifecycle, from design, through deployment, operations, and maintenance, to the product end-of-life and recycling, and its evolution.
Best practices and small proof-of-concept studies for other sectors, e.g. medical/pharmaceutical and/or digital industry.

Eligibility & conditions+

General conditions

1. Admissibility Conditions: Proposal page limit and layout

described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.

2. Eligible Countries

described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

3. Other Eligible Conditions

described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

4. Financial and operational capacity and exclusion

described in Annex C of the Work Programme General Annexes.

5a. Evaluation and award: Award criteria, scoring and thresholds

are described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

5b. Evaluation and award: Submission and evaluation processes

are described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

5c. Evaluation and award: Indicative timeline for evaluation and grant agreement

described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

6. Legal and financial set-up of the grants

described in Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU and in Annex G of the Work Programme General Annexes.

HORIZON-JU-CHIPS-2025-IA-FT2

Model Grant Agreements (MGA)

HE MGA

Call-specific instructions

Annex 1 Appendix 5 of the Multi Annual Work Programme of Chips JU.

Information on financial support to third parties (HE)

Additional documents:

Multi Annual Work Programme 2023 - 2027 Chips JU

HE Programme Guide

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

Official source

Confirm the current call documents and submission conditions with the funding authority.

View on EU portal ↗

Source: EU Funding & Tenders Portal · synced 2026-11-09

Who wins calls like this

Based on projects the EU funded on the same subject in this programme.

Who leads the winning projects

Other50%
Universities25%
SMEs13%
Research centres13%

€8.4Mtypical EU grant per project

Most common lead countriesGreece, Romania, Netherlands, Sweden, Austria

Projects funded on similar topics

HEARTSHelvetic AI Resources, Technologies and Services (Swiss AI Factory Antenna)

HORIZON-JU-EUROHPC-2025-AIFA-01 · 2026 · Official record ↗

€5.0M

PharosPharos: The Greek AI Factory for accelerating AI innovation

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗

€15.0M

RO AI FactoryRomanian EuroHPC AI Factory at ICI Bucharest

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2026 · Official record ↗

€4.0M

AIFA-ICEAI Factory Antenna of Iceland to LUMI AI Factory

HORIZON-JU-EUROHPC-2025-AIFA-01 · 2026 · Official record ↗

€5.0M

AI-ATApplication for an AI Factory in Austria

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗

€15.0M

AI2FAI Factory France

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗

€15.0M

MIMERThe Swedish AI Innovation Factory

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2025 · Official record ↗

€9.8M

NLAIFNetherlands AI Factory, building on Netherlands EuroHPC AI Facility

HORIZON-JU-EUROHPC-2025-AI-01-IBA-01 · 2026 · Official record ↗

€7.1M

Organisations that keep winning here

Each one links to its EU funding record and the partners it works with: a starting list for building a consortium.

What this call funds

Expected Outcome:The project is expected to contribute to the following outcomes:

Advanced AI-assisted methods and tools, including generative AI, for the automation of software engineering tasks, from enhancing human efficiency and optimizing resource utilization to enabling complex data/problems analysis/interpretation and supporting intelligent decision-making. Such engineering tasks often involve multiple domains (e.g., modelling, control, data management, communication, mechatronics, etc.) and stakeholders, with the burden of daunting legacy integration, refactoring (e.g., to re-design and replace obsolete technology), and the compliance with specific standards, regulations and certifications.
Open and extensible AI-assisted integrated platform, based on methodologies including AI-support, AI-based tools and toolchains, following a well-defined engineering process, including the integration with legacy tools. The platform shall provide flexible usage in small and large multi-domain and multi-stakeholder engineering teams, impacting existing and upcoming ECS engineering automation tools and their usage.
Showcasing and evaluation for software-defined vehicles of efficiency enhancements in terms of cost and time for complex data/knowledge management, resource optimization, energy consumption, interoperability, product/process quality/trustworthiness, learning curve and usability, over the whole lifecycle, from design, through deployment, operations, and maintenance, to the product end-of-life and recycling, and its evolution.
Best practices and small proof-of-concept studies for other sectors, e.g. medical/pharmaceutical and/or digital industry.

AI-assisted Methods and Tools for Engineering Automation

Who wins calls like this

Projects funded on similar topics

Organisations that keep winning here

What this call funds

General conditions

Official source

Get told when calls like this open.

AI-assisted Methods and Tools for Engineering Automation

Who wins calls like this

Projects funded on similar topics

Organisations that keep winning here

What this call funds

General conditions

Official source

Get told when calls like this open.