dAIEDGE is a European Network of Excellence (NoE) focused on distributed, trustworthy, efficient, and scalable AI at the edge. Its goal is to strengthen Europe’s innovation and AI capabilities, especially within the European AI ecosystem, and support strategic planning for future AI developments.

What Is Offered?

• Up to €600,000 in funding will be distributed among up to 10 selected proposals (max. €60,000 per project).

• Funding supports R&D activities addressing one of the 13 Industrial Challenges defined by the dAIEDGE Consortium.

• Beneficiaries can also access and contribute to the dAIEDGE Virtual Lab.

• Selected teams will receive technical mentoring throughout two stages of the support programme.

• The call is open from 14 August 2025 (09:00 CET) to 14 October 2025 (15:00 CET).

Who Can Apply?

Eligible applicants include:

• Legal entities (individual or 2-member consortiums) such as:

  • SMEs (including Startups)

  • Research and Technology Organisations (RTOs)

  • Academic institutions

Applicants must be legally registered in:

• EU Member States or their Overseas Countries and Territories

• Horizon Europe Associated Countries (e.g., Norway, Ukraine, UK, etc.)

Not eligible: Entities under EU sanctions, Hungarian public interest trusts, and dAIEDGE consortium members or their affiliates.

Eligible Activities

Funded activities must:

• Focus on solving one of 13 predefined Industrial Challenges (e.g., federated learning, on-device training, low-power AI, generative AI, edge deployment).

• Start at Technology Readiness Level (TRL) 2-3 and aim to reach TRL 4-5.

• Demonstrate a clear European dimension, with tangible impact on Europe’s society or economy.

Topics (Industrial Challenges) Include:

1. Energy-efficient federated learning

2. On-device training for resource-limited devices

3. Ultra-low-power speech enhancement

4. Bayesian AI agents for smart environments

5. Semantic/hyperspatial world models for edge systems

6. Binary neural networks for FPGAs

7. Generative AI for digital map configuration

8. Privacy-first health monitoring at the edge

9. Federated learning in browsers

10. Off-chip weight storage for AI hardware

11. Vehicle detection on PYNQ-Z1

12. Real-time ViT on FPGA SoC

13. Object detection using generative AI at the edge