Olery provides hospitality-focused predictive analytics and AI-driven data analysis tools that help cities and tourism enterprises make data‑driven decisions.
Funding
Funding not disclosed
Founders
Product
Problem
Tourism authorities and hospitality businesses lack comprehensive, real‑time insight into visitor sentiment and competitive positioning because reviews are scattered across numerous travel sites and languages, making it difficult to benchmark performance or identify growth opportunities.
Solution
Olery aggregates and analyzes over 2 billion reviews from major travel platforms such as Booking.com, TripAdvisor, and Google, delivering a unified hospitality dataset covering hotels, restaurants, attractions, and destinations worldwide. Its AI‑driven sentiment analysis translates multilingual review text into standardized scores for attributes like cleanliness, service, and overall experience. The platform provides predictive analytics and benchmarking tools that reveal how a city or property is perceived relative to competitors and highlights target tourist regions for growth. Users access these insights through APIs, dashboards, and customizable reports, enabling data‑driven decisions to improve guest experiences and drive sustainable revenue.
Target Audience
Primary customers are city tourism boards, hotel chains, restaurant groups, and attraction operators seeking actionable intelligence on visitor sentiment and competitive performance.
Features
- Consolidated hospitality dataset of over 1.5 million active properties with global coverage at country, regional, and city levels
- Multilingual sentiment analysis (15+ languages) that converts review text into numeric scores for specific hospitality attributes
- Predictive analytics and competitive ranking dashboards that benchmark destinations and properties against peers
- API and SDK access for seamless integration of review data, sentiment scores, and analytics into existing systems
- Customizable reporting tools and visualizations to track visitor sentiment trends and identify high‑potential tourist source markets