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Reef Expert: Fish & Coral

Reef Expert: Fish & Coral

Yihong Lim

Lifestyle免费v1.6
App Store
评分

4.6

45 条评分

星级

★★★★★

最近更新

2026年1月14日

发布日期

2025年9月17日

更新内容

v1.6

This version of Reef Expert introduces detailed analysis and bug fixes

应用信息

开发者
Yihong Lim
分类
Lifestyle
价格
免费
版本
1.6
App ID
6751739535

简介

Losing fish or corals to preventable issues? Reef Expert: Fish & Coral Care is your AI-powered reef assistant, available 24/7 to keep your saltwater aquarium thriving. With expert guidance at your fingertips, you’ll avoid costly mistakes and protect your marine life whether it’s diagnosing a sick fish, caring for stressed corals, or optimizing your reef tank’s health. With Reef Expert, you can: • Upload fish or coral photos for instant AI health assessments • Get personalized care recommendations tailored to your tank setup • Check fair fish and coral price ranges before you buy to avoid overpaying • Ask AI Reef Expert Chat any reef-related question for fast, accurate answers Reef Expert isn’t just for emergencies, it’s your daily companion for optimal reef care. Our AI learns from your specific conditions, delivering more accurate, tailored advice the more you use it. Why Reef Expert? • Prevent fish and coral losses before they happen • Boost coral growth and maintain fish health • Get reliable, expert-level advice without waiting on forums or store visits Download Reef Expert today and experience the power of AI-driven reef care. Whether you’re saving a sick fish, nurturing delicate corals, or preventing problems before they start. We’ve got you covered. Privacy Policy: https://reefexpert.github.io/legal/privacy-policy.html Terms of Service: https://reefexpert.github.io/legal/terms-of-service.html Subscription Information: Reef Expert offers weekly and annual plans. • Reef Expert Weekly Pro: $9.99/week, auto-renews weekly • Reef Expert Annual Pro: $79.99/year, auto-renews annually Manage or cancel anytime in your App Store account settings after purchase.

下载量预测

专业 · 预览

预估总下载量

3K2K6K
保守估计乐观估计

281

低 / 月

417

预估 / 月

804

高 / 月

基于45 条评分
假设评分率1.4%
应用年龄8 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。