The problem
Destination data is scattered across portals, Google, in-house websites and spreadsheets. The quality varies, translations are missing and nobody knows which version is correct. Decisions are therefore based on out-of-date or incomplete information.
Our approach
- Three-stage quality control: raw data is checked, cleaned and enriched using AI (the Medallion approach).
- A range of reputable sources side by side: Google Places, OpenStreetMap, official websites and tourism portals.
- AI translations with built-in quality control; internally measured error rate below 5 per cent.
- Freshness and changes for each data point are monitored automatically.
- Updating frequency aligned with strategy and budget.
The evidence
Figures: reference date July 2026, verified periodically.
- A dynamic, unlimited POI and calendar database for each destination: compiled, validated, translated and continuously updated.
- Over 144,000 knowledge snippets feed into the chatbot and content production.
- Specialist agents monitor data quality and synchronisation around the clock.
- Review analysis based on tens of thousands of reviews; only current reviews are displayed, none older than two years.
KPIs: what you measure
Translation coverage (%)
Data freshness
Margin of error for AI-generated content (%)
Validated data sources
Related modules
Would you like to see how this works for your organisation?
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