Digitization of government archives and AI-based data asset processing
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A central administrative institution set itself the goal of digitizing and reusing hundreds of thousands of pages of documents spanning several decades. A significant portion of the documents existed only in physical form, and accessing them required considerable human and time resources.
The project involved a large-scale digitization process based on industrial OCR technology, supplemented by natural language processing algorithms. These were used to automatically categorize the materials, identify entities (people, places, dates), and organize them into a time-based searchable structure.
Big data analytical models were applied to the structured database. AI models analyzing changes over time in various social, economic, and legislative processes revealed previously unseen correlations.
An interactive, dashboard-based visualization tool was developed for decision-makers, which also provided predictive functions, e.g., trend forecasts, regional comparisons, and time-based change analysis.
Achievements:
60 years of historical documents now digitally searchable
The time needed to obtain information has been reduced from weeks to minutes.
New strategic analyses and long-term forecasts have become possible
The results of the analysis were directly incorporated into public policy planning.
