Most teams rely on assumptions, fragmented research, or opinion. Appnalysis is a decision-support platform for the mobile sector and the AI assistants teams now use to make app decisions. We don't just surface evidence about how iOS and Android apps are built, monetisation, technology stack, SDKs, accessibility, security signals, and store performance. We explain what it means for the decision in front of you, so you can decide with confidence.
Every signal comes with the analysis behind it, not just the number.
Four primary audiences: Agencies, Product Teams, Enterprise, and Ecosystem & Policy.
Ask questions in plain language at /ask, export to Looker Studio, Power BI, Excel, or any OData-compatible tool, or attach Appnalysis directly to ChatGPT, Claude, Cursor, and other AI assistants via the Model Context Protocol.
Yes. Appnalysis analyses any live iOS or Android app, so you can see where it ranks in the App Store and Google Play charts, how those rankings have moved, what it costs and how it is monetised, what reviewers actually say, and then all the way down to how it is built: the SDKs, frameworks, permissions, trackers and architecture behind it. Ask in plain language and you get an interpreted, citation-backed answer, not a raw data dump.
App analysis is the practice of studying mobile apps to understand what they are built with, how they perform in the market, and how they compare against competitors. It combines App Store and Google Play data, ranking history, review signals, SDK and framework detection, and monetisation patterns into evidence a team can act on. Appnalysis automates this discipline as an agentic mobile app intelligence platform, so agencies, product teams and analysts can answer questions in minutes rather than weeks.
Mobile app intelligence is structured, decision-ready insight into how iOS and Android apps are built and behave in the real world, drawn from real app binaries, App Store and Google Play signals, and broader ecosystem sources. It covers features, SDKs, frameworks, monetisation, security signals, and architecture, not just downloads or revenue estimates. Appnalysis delivers mobile app intelligence as an AI agent so teams can ask questions in plain English and get answers grounded in real evidence, without navigating dashboards.
App analytics usually refers to in-app or application performance monitoring tools such as Firebase, Amplitude, Mixpanel, Datadog, or New Relic. Those measure your own app's usage and performance from an SDK embedded inside it. App intelligence works from the outside in: it analyses real published apps across the market, including competitors you don't own, to answer how apps are actually built, monetised, and evolving. Appnalysis is app intelligence, not app analytics.
Technographic data describes the technologies a product is built with and buys, rather than the company behind it or the people who use it. Applied to mobile, it means what a shipped app is actually made of: the framework or native toolchain, the analytics and attribution SDKs, the payment and subscription infrastructure, ad networks, and the third parties each of those brings with it. A store listing tells you what a company wants to be seen as; the build tells you what it committed to. Appnalysis detects that stack on live iOS and Android apps and tracks when it changes. See /insights/what-is-mobile-app-intelligence#app-technographics.