AI Review Management System for Hotels and Restaurants

We design and deploy artificial intelligence systems: from prototype to production-ready solutions. Our team combines expertise in machine learning, data engineering and MLOps to make AI work not in the lab, but in real business.
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AI Review Management System for Hotels and Restaurants
Medium
~1-2 weeks
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Development of AI System for Review Management for Hotels and Restaurants

Reviews on Booking, TripAdvisor, Yandex Maps, Google Maps determine hotel occupancy and restaurant traffic. An AI system helps monitor, analyze, and professionally respond to reviews at scale.

What the System Automates

Monitoring: collection of new reviews from all platforms in one interface. Notifications when new reviews appear, especially low ratings.

Analysis: aspect-based sentiment — what specifically is praised or criticized. Food, service, cleanliness, location, value for money — each aspect separately.

Response Generation: AI creates a personalized response to each review, considering tone and specific mentioned details. Manager reviews and publishes.

Analytics: trends over time periods, competitor comparison, identification of recurring problems.

Platform Integrations

  • Booking.com: Property Partner API (access through partner program)
  • TripAdvisor: Management Center API
  • Google Business Profile API: google-my-business-api
  • Yandex Maps: Yandex.Business API
  • 2GIS: Business API

Response Generation

def generate_review_response(review: Review) -> str:
    system_prompt = f"""You are the manager of {review.property_name}.
Response style: professional, warm, not templated.
Always: thank for the review, address specific details,
for negative — acknowledge the problem and explain what was done/will be done."""

    prompt = f"""Write a response to the review:
Rating: {review.rating}/10
Text: {review.text}
Date: {review.date}"""

    return llm.generate(prompt, system=system_prompt, max_tokens=200)

Key: the response should reference specific details from the review — "We're glad you enjoyed the mountain view from room 304" is better than "Thank you for your review".

Reputation Management KPIs

  • Average rating on each platform (monthly trend)
  • Response rate: % of reviews with responses (target > 90%)
  • Response time: average time to respond (target < 24 hours)
  • Sentiment score by aspects: what improved, what worsened
  • Review velocity: is the number of reviews growing