An innovative Greek startup specializing in the development of AI-driven decision support systems and data analytics solutions for workforce management is preparing a proposal under the Eurostars 3 call 11. The company has strong experience in developing data-driven solutions that leverage machine learning and behavioural insights to support task allocation and organisational decision-making.



The aim of the Eurostars project is to develop an innovative AI-powered software solution designed to integrate seamlessly into existing Human Capital Management (HCM) systems, enabling organizations to make more objective and meritocratic decisions in job task assignment, team formation, hiring and promotions, based on psychocognitive profiles of individuals.



By combining validated psychological and cognitive assessment methodologies with predictive machine learning models, the system will identify which individuals are best suited for specific tasks or projects. The approach promotes inclusivity, especially for neurodivergent individuals, by recognizing diverse cognitive strengths that traditional human resources (HR) tools often overlook, while always prioritizing data security and GDPR compliance. The solution will incorporate real-time analytics, explainable AI modules, and an interoperability toolkit for HCM platforms (e.g., SAP, Oracle, Dynamics). The overall objective is to develop a scalable and powerful data-driven tool, that supports fair, transparent, efficient and future-proof workforce management.



The Greek company will act as the project coordinator and will lead the development of the core AI-based HCM solution, including the psychocognitive profiling framework and machine learning algorithms. It will oversee data strategy and ethics, ensuring GDPR compliance, and coordinate the consortium's scientific and project management activities. The company will also lead end-user piloting and validation to test and refine the solution in real-world settings.



To complete the consortium, the company is seeking two additional partners from Eurostars-eligible countries. Ideal partners are an AI/software company that will contribute to the development of the machine learning and system architecture components, and an industry partner that will provide access to workforce data and support pilot testing and validation in real organisational environments. The proposal is currently under development, with a deadline for expression of interest set for 01/07/2026.

Advantages and Innovations

The project introduces an AI-powered solution that enhances Human Capital Management (HCM) systems by integrating validated psychological and cognitive assessments with machine learning. It supports companies in making fair, data-driven decisions related to task assignment, while promoting inclusivity, particularly, for neurodivergent individuals. Designed to integrate with existing HCM platforms, the tool prioritizes GDPR compliance and ethical data use, and provides real-time, explainable insights that help align individual strengths with organizational needs, ultimately improving engagement and satisfaction.

Technical Specification or Expertise Sought

The Greek start-up is looking for one to two partners from Eurostars-eligible countries, active in the technology and engineering sectors, with complementary expertise in the following areas.



In particular, the company is looking for an industry or end-user partner, such as a private company, capable of providing access to relevant workforce data and organisational environments. This partner should be able to support the secure and anonymised collection of employee data, contribute to data processing activities, and participate in testing and validation of the solution in real-world conditions.



In parallel, a technology partner is sought, preferable an SME with experience in software development and machine learning, particularly in data-driven applications. Expertise in predictive analytics and AI-based systems will be considered an asset, supporting the development and optimisation of the machine learning components. Experience in survey implementation, data analysis workflows, and/or the integration of psychological or cognitive assessment methodologies will be considered an advantage.



Expected Role of a Partner:



Partners will participate in the project under a research and development cooperation agreement, contributing according to their expertise and role within the consortium.



The industry or end-user partner is expected to provide access to anonymised workforce data and relevant organisational environments, supporting the collection and processing of data in compliance with data protection and ethical standards. This data will serve as input for training the machine learning algorithm at the core of the project, which is designed to optimize role alignment and task assignment. This partner will also contribute to the pilot testing and validation of the solution in real-world conditions.



The technology company is expected to contribute to the development and training of the machine learning models, as well as to support the implementation of software components and data-driven functionalities, contributing to the development of the predictive framework underpinning the solution.



Depending on their expertise, partners will also support activities such as survey implementation, data analysis processes, and the integration of cognitive or behavioural assessment approaches. All partners will collaborate closely with the coordinator to ensure ethical data usage, methodological robustness, and the practical applicability of the solution in real organisational contexts.



Should you have any questions, feel free to contact Mar Coromina mcoromina@secartys.org | 623 35 59 80, and we'll do our best to help you.