Imagine a factory where robots and human workers act like a team in a meeting, each having a vote on how to handle a task. Instead of one boss or a rigid program deciding everything, a digital system balances everyone's needs—like energy use and worker safety—to find the best compromise. It's like a digital mediator that ensures the production line stays flexible without ignoring the people on the floor.
Production lines are often too rigid and rely on top-down decisions that ignore real-time human insights or energy constraints. This leads to inefficiency and a lack of trust among workers.
A Democratic AI-based Decision Support System (DAI-DSS) prototype and a Low Code / No Code platform for configuring AI services and user interfaces.
If you are a car manufacturer dealing with complex environment interactions and constant re-arrangements—this project developed a Democratic AI-based Decision Support System that optimizes production while granting human workers and machines a say in the process.
If you are a robot plant provider dealing with the need for continuous re-arrangements in production—this project developed a multi-agent system that uses digital twins to optimize processes based on technical, business, and social parameters.
If you are a software provider dealing with slow configuration of resource allocation—this project developed a Knowledge Provisioning Ecosystem that allows users to compose AI services and interfaces using a Low Code / No Code platform.
Based on available project data, no specific commercial pricing or cost per license is provided; the project was funded by an EU contribution of EUR 2,979,375.
The project uses a multi-agent system and digital twins to optimize production processes, with use cases specifically challenged by a car manufacturer and a robot plant provider to ensure industrial applicability.
Based on available project data, specific licensing terms are not listed, but the project involves a consortium of 9 partners including industry and research entities.
The system uses a connectivity meta model that has demonstrated the ability to connect management software, such as the EAM tool ADOIT, with LLMs from OpenAI and Mistral.
The project includes a process to assess decision models against legal, ethical, security, and safety concerns to ensure only compliant models are used for decision making.
The consortium is well-balanced for commercialization, featuring 9 partners across 6 countries. With an industry ratio of 44% (including 4 industry partners and 2 SMEs), there is a strong bridge between the academic research from universities and the practical needs of the automotive and robotics sectors.
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Contact us to explore licensing opportunities for the DAI-DSS prototype.
