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EA-CDD – Edge Agentic AI for Critical Design Decisions

Reference number
Coordinator Intended Future AB
Funding from Vinnova SEK 150 000
Project duration January 2026 - April 2026
Status Ongoing
Venture Advanced digitalization - Industrial needs-driven innovation
Call Collaborations with the US in AI, digital infrastructure and cyber security

Important results from the project

All goals were achieved and expectations exceeded. We established collaboration with University of South Carolina and Center for Industry Solutions, gaining access to robotics labs and humanoid robots. All planned meetings were conducted during NVIDIA GTC and Nordic Innovation House, plus unplanned meetings with investors and researchers. A new pitch deck was produced and development of our self-learning agent architecture began. The project also led to seed round discussions with two investors.

Expected long term effects

The project laid the foundation for MIMIQ, a Step 2 project where our self-learning Agentic AI is deployed on edge hardware inside humanoid robots at University of South Carolina. The robot learns by observing and conversing with specialists, like a new hire learning from a senior colleague. The goal is to create a new category of industrial AI: a self-improving digital expert employee in physical form. The collaboration also opens the path to a seed round and establishing a US subsidiary.

Approach and implementation

The project had three work packages. In AP1 we mapped partners, prepared demos and booked meetings. In AP2 all meetings were conducted during NVIDIA GTC and Nordic Innovation House. The timeline was followed exactly. Unexpectedly we had more meetings than planned, including with VCs and researchers we had not anticipated, giving a broader network and stronger outcomes. In AP3 the partnership agreement and Step 2 application were finalised. Collaboration with Vinnova and NIH worked excellently.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 6 May 2026

Reference number 2025-04707