Artificial intelligence, advanced modelling and two new international certifications. OpenEconomics has successfully completed the project co-funded under the Calabria Regional Programme ERDF ESF+ 2021–2027, Action 1.3.1 Advanced Services, achieving 91% of the approved investment and paving the way for a new generation of tools for complex data analysis.
The project, delivered in partnership with specialist firms HN Excellence and RINA Service, had a clear objective: to build an AI-driven document management system capable of transforming heterogeneous documentation into structured data. To achieve this, the team worked on advanced data extraction technologies, multi-agent architectures and rigorous validation methodologies, with an architecture designed for industrialisation through AIOps (Artificial Intelligence for IT Operations) and MLOps (Machine Learning Operations) services.
The project went beyond document processing. In parallel, OpenEconomics mapped out a roadmap to advance its macroeconomic modelling framework, built on Social Accounting Matrices, by integrating predictive models, territorial downscaling through Graph Neural Networks and new economic forecasting services. The ambition is considerable: a Digital Twin of the regional and national economy — a virtual, dynamic representation of the real economic system — capable of simulating the impact of shocks, such as a fiscal policy change or a major public investment, before they are implemented.
The final results speak for themselves: 91% of the investment completed, activities validated by the managing authority, and a methodological and technological asset base now fully consolidated. To this, the attainment of ISO 14001 and ISO 45001 certifications adds further evidence of the robustness of the company's management systems.
OpenEconomics will now continue along the path of industrialising its document ecosystem and advancing its macroeconomic models, with the goal of providing businesses and public bodies with intelligent tools to analyse, simulate and manage complex data.
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