CASE STUDY — UNITED NATIONS & FSI
News Classifier
Turn scattered news into structured, validated insight
Sector:
United Nations, FSI &
Beyond
Focus:
AI-Powered News Classification
BUSINESS CHALLENGE
Manual news monitoring limiting scalability
Organizations relying on daily news monitoring to detect relevant policies, regulations, or market-moving events across regions often depend on largely manual processes, clipping, scraping, and CSV-based tagging, which limits scalability and slows the identification of relevant content.
SOLUTION IMPLEMENTED
An AI system classifying and validating policy-related news at scale
Developed an AI-powered system to automatically classify and validate policy- and regulation-related news across multiple languages and regions. Users can upload large batches of links and download validated results directly from the web app, with multilingual classification and editable criteria accelerating the detection of relevant content.
TECNOLOGÍA
Built to classify, validate, and visualize news at scale
PLATAFORMA DE DATOS
Azure Storage Account
Azure Storage Account to store and manage classified news and historical results securely across all monitored sources.
AI
Azure Foundry
Azure AI Foundry for multilingual classification, summarization, and validation of policy-related news content
VISUALIZATION
Azure Container Apps & Power BI
Web app hosted on Azure Container Apps with Power BI dashboards to visualize and monitor classification results.
Results & ROI
What changed once the system went live
EFFICIENCY
Reduced manual classification time by over 60%, enabling faster detection of relevant content across all monitored regions.
QUALITY
Improved accuracy and consistency through automated validation and standardized classification criteria across languages and regions.
SCALABILITY
Processes large multilingual content volumes without additional resources, ensuring sustainable delivery within existing budget constraints.
