ZReviewTender fetches app reviews from the App Store and Google Play Console using the new Stability API, and resends them to Slack or integrates with your workflow.

Node.js library written in TypeScript for sending App Store app reviews to Slack.

Automate replies to Google Play Store reviews with OpenAI's GPT-3.5-turbo-powered Python script that fetches recent app reviews and generates responses

Analyze App Store and Google Play reviews with an analyze-first skill for agents and API workflows.

Sample code to demonstrate how to use the Store Review Plugin in Xamarin.Forms

AppPulse — 感知每一条用户心声 | 输入 App 名字，自动抓取全球 App Store & Google Play 评论，AI 多维分析，生成可视化洞察报告

> End-to-end RAG pipeline that turns Google Play app reviews into a production-ready, searchable knowledge base using Thordata scrapers and embeddings.

AI-powered pipeline that transforms raw mobile game reviews into actionable product intelligence. Features LLM-based classification, priority scoring, and executive health KPIs. Built with FastAPI, Streamlit, and OpenAI to automate sentiment analysis, fraud detection, and trend tracking for game ops.

A sentiment analysis model for Microsoft Office app reviews, leveraging advanced text preprocessing and deep learning architectures to accurately classify user sentiments

Manage App Store Connect from your terminal — metadata, screenshots, reviews, TestFlight, IAP, releases. A Claude Code skill.

Automated app review monitoring and user feedback analysis system built with n8n, AI, and Notion

Classifier for app reviews on a scale of 1 to 5 using Gated Recurrent Unit (GRU).

End-to-end pipeline for collecting, preprocessing, and analyzing app reviews to determine user sentiment using Python.

This project analyzes Google Play Store app reviews using a daily batch-based AI pipeline. It extracts common user issues and feedback from reviews and generates a trend analysis report showing how these topics change over time. The system is designed to help product teams quickly identify recurring problems and emerging trends.

Topic Modeling on “Coupang” App Reviews [Korean Text Processing]

Review relic for iOS, for integrating Review relic into your iOS application.

Intelligent, non-intrusive in-app review prompting to maximize your app's ratings on iOS, macOS, tvOS, and watchOS.

Masterseminal paper (University of Wuerzburg)

This project analyzes Google Play Store app reviews using a daily batch-based AI pipeline. It extracts common user issues and feedback from reviews and generates a trend analysis report showing how these topics change over time. The system is designed to help product teams quickly identify recurring problems and emerging trends.

AI-powered app review intelligence system — sentiment analysis, trend detection, issue prioritisation & PDF reports built with Python, Streamlit & HuggingFace