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AI Travel Search Assistant (Booking.com Wrapper)

Overview

We are building an AI-powered conversational travel search layer on top of Booking.com inventory. Instead of using traditional filters, travelers will describe what they want in free text, and our system will translate their intent into structured Booking.com search queries and return highly relevant ranked results.

This repository represents a pre-launch / under-development product.

What problem we solve

Finding the right accommodation often requires multiple filter selections, trial-and-error searches, and long decision cycles. Users usually know what they want — they just can’t express it efficiently using checkboxes.

We let users write:

  • “quiet beach resort for a family with two kids”
  • “business hotel near the conference center, late check-in, strong Wi-Fi”
  • “romantic boutique hotel in the old city, under $250/night”

The assistant understands the intent and constraints, then searches Booking.com accordingly.

How it works (high level)

  1. User submits a free-text request.
  2. NLP/LLM parses intent → preferences, constraints, and priorities.
  3. We map intent to Booking.com API parameters.
  4. We fetch results and re-rank them based on fit to intent.
  5. We present a concise, personalized shortlist.

Promotion model

We do not promote a specific property. We promote Booking.com listings broadly through a smart discovery experience that improves relevance and time-to-booking.

Status

  • Current stage: Pre-launch / MVP in development
  • Next milestone: First working prototype integrating Booking.com API

Planned roadmap

See: /docs/roadmap.md

Contact

For partnership / API access:

About

AI conversational travel search that translates free-text intent into Booking.com queries.

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