AI-Powered Cultural Tourism Experience

Implementation Time:
1 months
Solution Provider:

Cultural heritage in Belgrade is rich but fragmented, often overlooked by both locals and tourists due to a lack of centralized, engaging, and adaptive presentation. Traditional static guides and linear tours fail to meet the expectations of today’s digitally native users, who seek personalized, immersive, and interactive experiences.

AI-Powered Solution:

Beotura leverages artificial intelligence to dynamically tailor cultural content and tour recommendations based on user preferences, behavior patterns, location data, and language. Using machine learning and natural language processing, the platform transforms passive heritage information into smart, story-driven experiences — increasing user engagement, accessibility, and the visibility of lesser-known cultural sites.

What it is:
Beotura’s AI solution is a personalized recommendation and content delivery system that enhances the cultural tourism experience in Belgrade. It uses machine learning and natural language processing (NLP) to suggest relevant heritage sites and tours, adapt narratives based on user profiles, and enrich storytelling with intelligent, context-aware insights.

Key Capabilities:

  • Smart recommendations for heritage sites and thematic tours

  • Dynamic content adaptation based on user interests, location, and language

  • NLP-driven storytelling, turning raw historical data into engaging narratives

  • Image and text recognition to support interactive exploration through user input (e.g., scanning a building or entering a phrase)

  • How it is Developed

    The AI system was developed in phases:

    1. Data Collection & Curation:
      A comprehensive dataset of over 140 cultural sites was compiled, including metadata (e.g., historical period, themes, geolocation, media files) and narrative content written in collaboration with historians and educators.

    2. Model Training:

      • A content-based recommendation model was trained using user interaction data (clicks, time spent, preferences) and content tags.

      • NLP models (using tools like spaCy or BERT) were used to analyze and enrich historical text for tone, theme, and context adaptation.

      • Optional computer vision models allow users to identify landmarks via photos (pilot phase).

    3. Integration with Mobile & Web Platform:
      AI modules are integrated via REST APIs with Beotura’s mobile app and web backend, ensuring real-time content delivery and recommendation updates.

    🚀 How it is Deployed

    • Cloud-based Deployment:
      The AI models are hosted on a scalable cloud infrastructure (e.g., AWS, Azure, or GCP), allowing for real-time processing and recommendations.

    • Mobile and Web Integration:
      The system is embedded into both the iOS/Android app and the web interface. Users receive personalized tour suggestions and dynamic content directly within the app, without needing any technical knowledge.

    • User Feedback Loop:
      The platform collects anonymized user interaction data (with consent) to continuously retrain and improve AI models for higher relevance and accuracy.

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Implementation Time

1 months

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