Subscription analytics and monetization platform for mobile apps
RevenueCat operates a subscription management platform for iOS, Android, and web, built on Django, Flask, and PostgreSQL with native SDKs across Apple and Google ecosystems. The hiring mix—heavily weighted toward engineering and product, with emerging data and security roles—reflects an engineering-led roadmap now expanding into AI features (LTV prediction, subscription revenue assistant, agentic capabilities) and statistical rigor (experiment design, significance testing). The platform is shifting from pure subscription infrastructure toward actionable retention intelligence and lifecycle automation.
RevenueCat provides subscription analytics and monetization tools for mobile app developers. The platform connects to iOS App Store, Google Play, and web payment channels, offering dashboards, SDKs, and APIs to manage recurring revenue, analyze cohorts, and optimize paywalls. Founded in 2017 and headquartered in Brandon, Florida, the company serves app publishers ranging from indie developers to large studios. Recent project activity signals expansion into AI-driven revenue forecasting, paywall automation, and payout factoring—moving beyond analytics into decision support and financial operations.
Backend: Django, Flask, PostgreSQL. Frontend: React, Vue, Angular, JavaScript. Mobile: Swift, SwiftUI, Kotlin, Jetpack Compose, iOS SDK, Android SDK. Analytics: Looker. Integrations: Stripe, Apple App Store, Google Play. Recently adopting: Figma for design tooling.
Active projects include an AI assistant for subscription revenue, LTV prediction, experiment design and statistical significance, agentic features, paywall automation UI, daily payouts factoring, and lifecycle marketing automation to improve retention and reduce churn.
RevenueCat's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.