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Paris Travel Guide & AI

Paris Travel Guide & AI

TicketLens GmbH

Travel免费v2026.4
App Store
评分

4.7

392 条评分

星级

★★★★★

最近更新

2025年12月21日

发布日期

2009年6月9日

更新内容

v2026.4

- Our AI assistant has been significantly upgraded to deliver faster answers and better recommendations. - Bug fixes

应用信息

开发者
TicketLens GmbH
分类
Travel
价格
免费
版本
2026.4
App ID
316996121

简介

Turn Paris into a playlist of must-do moments—powered by AI. Stroll grand boulevards, compare tours & tickets in one place, and build a personal itinerary in seconds. The micro-summary • AI Travel Assistant – ask anything and get a smart, step-by-step game plan • Attraction-only focus – iconic landmarks, world-class museums, secret passages, Seine cruises & more • Tickets, tours & activities – compare options and book right inside the app • Favorites – save every place or activity and craft your perfect itinerary ----- WHY 5 + MILLION TRAVELERS CHOOSE US AI-POWERED INSPIRATION Skip endless web searches. Chat with the built-in assistant to uncover hidden courtyards in Le Marais, decide which museum pass fits your schedule, or auto-build a three-day itinerary optimized for metro lines and timed-entry slots. SEARCH, COMPARE & BOOK Filter by category—legendary monuments, rooftop viewpoints, day-trips to Versailles, cultural experiences—and instantly see ticketed tours and activity bundles. Side-by-side comparisons put prices, durations, and what’s included in one view; book the winner in two taps. PLAN YOUR PERFECT DAY Pin must-see attractions and rearrange on the fly. Need a last-minute tweak? Ask the AI to reshuffle around weather, crowd levels, or sunset Seine-cruise times—no spreadsheets required. ----- Whether you’re a first-timer or a seasoned visitor, our AI-enhanced guide turns Paris into a personalized adventure—no restaurant listings, no hotel clutter, just pure must-do magic. Download now and build the trip that’s 100 % you!

下载量预测

专业 · 预览

预估总下载量

29K20K56K
保守估计乐观估计

95

低 / 月

141

预估 / 月

272

高 / 月

基于392 条评分
假设评分率1.4%
应用年龄206 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。