PROSYNC

Project ID: AEI-010500-2025-80

Participants: Oslice Technology, Topdigital Consulting, Capital Biomasa, Cluster TIC Asturias, Universidad de Málaga, onTech innovation

Funded by: Ministerio de Industria y Turismo (Programme to support business incubators in order to contribute to improving the competitiveness of small and medium-sized enterprises)

Project type: Experimental development

keywords: Agentic AI, digital transformation

This project aims to design and conduct industrial research on a functional prototype of a smart digital platform geared towards the technological transformation of SMEs and freelancers, using a strategic diagnostic system based on advanced artificial intelligence techniques. Its objective is to analyze digital maturity in production processes, detect critical areas for improvement, and identify transformation routes tailored to the characteristics of each company’s industrial environment.

The solution will be based on a modular architecture in the prototyping phase, consisting of an explainable AI engine trained with structured data derived from real experiences in technology consulting, and an adaptive logic system that will enable the construction of personalized itineraries around five key areas of industrial digitalization: operational cybersecurity, industrial data management, production process optimization, digital marketing channels and artificial intelligence applied to industry.

The proposal does not start from an existing solution, but will develop a new integrated system, currently non-existent on the market, through the integration of emerging technologies such as natural language processing, semantic classification and supervised learning, applied to real industrial contexts.

During the project, progress will be made from a fragmented technological base towards a prototype platform validated in a relevant environment, using industrial simulation environments or functional laboratories to validate the behavior of the system in conditions close to real ones. This will allow observation of the behavior of the AI engine, the consistency of its recommendations, the adaptability of the itineraries generated and the efficiency of the matching model with technological solutions from the industrial ecosystem.

The platform will also include an experimental ICT matching system, which will connect diagnosed technological needs with specialized industrial suppliers, through a multi-criteria algorithm currently in the testing phase, assessing technical specialization, previous experience and sector suitability. Development will be geared towards a microservices-based cloud architecture, with a focus on interoperability with existing industrial systems, complying with security and data protection regulatory frameworks relevant to connected industrial environments, such as ENS, ISO 27001, and GDPR.

Principal investigator (UMA):

• Eduardo Guzmán

Researchers (UMA):

• María Victoria Belmonte
• Mónica Trella
• José del Campo